Wed, 29 Jan 2020

New package RClickhouse with initial version 0.5
Package: RClickhouse
Type: Package
Title: A 'DBI' Interface to the 'Yandex Clickhouse' Database Providing Basic 'dplyr' Support
Version: 0.5
Encoding: UTF-8
Authors@R: c( person("Christian", "Hotz-Behofsits", email = "christian.hotz-behofsits@wu.ac.at", role = c("aut", "cre")), person("Peter", "Knaus", email = "peter.knaus@wu.ac.at", role = c("aut")), person("Daniel", "Winkler", email = "daniel.winkler@wu.ac.at", role = c("aut")), person("Clemens", "Danninger", email="cran@b8000h.org", role = c("aut")), person("Simon", "Stiebellehner", email="simon.stiebellehner@gmail.com", role = c("aut")), person("Dan", "Egnor", role = c("aut")), person("Vlad", "Losev", email = "vladl@google.com", role = c("aut")), person("Keith", "Ray", email = "keith.ray@gmail.com", role = c("aut")), person("Zhanyong", "Wan", email = "wan@google.com", role = c("aut")), person("Markus", "Heule", email = "mheule@google.com", role = c("aut")), person("Oliver", "Flasch", email = "oflasch@gmail.com", role = c("aut")), person(family = "Google", role = c("cph")), person("Yann", "Collet", role = c("cph")) )
Description: 'Yandex Clickhouse' (<https://clickhouse.yandex/>) is a high-performance relational column-store database to enable big data exploration and 'analytics' scaling to petabytes of data. Methods are provided that enable working with 'Yandex Clickhouse' databases via 'DBI' methods and using 'dplyr'/'dbplyr' idioms.
License: GPL-2
SystemRequirements: C++11
Imports: dplyr (>= 0.7.0), dbplyr (>= 1.0.0), methods (>= 3.3.2), DBI (>= 0.6.0), Rcpp (>= 0.11.0), yaml (>= 2.1.14), bit64
LazyData: true
RoxygenNote: 7.0.1
NeedsCompilation: yes
Depends: R (>= 3.3)
Suggests: testthat
Collate: 'RcppExports.R' 'RClickhouse.R' 'ClickhouseDriver.R' 'ClickhouseConnection.R' 'ClickhouseResult.R' 'dbplyr-helpers.R' 'dplyr.R' 'zzz.R'
URL: https://github.com/IMSMWU/RClickhouse
BugReports: https://github.com/IMSMWU/RClickhouse/issues
LinkingTo: Rcpp
Packaged: 2020-01-29 03:12:50 UTC; chris
Author: Christian Hotz-Behofsits [aut, cre], Peter Knaus [aut], Daniel Winkler [aut], Clemens Danninger [aut], Simon Stiebellehner [aut], Dan Egnor [aut], Vlad Losev [aut], Keith Ray [aut], Zhanyong Wan [aut], Markus Heule [aut], Oliver Flasch [aut], Google [cph], Yann Collet [cph]
Maintainer: Christian Hotz-Behofsits <christian.hotz-behofsits@wu.ac.at>
Repository: CRAN
Date/Publication: 2020-01-29 10:30:02 UTC

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New package mixsqp with initial version 0.3-17
Encoding: UTF-8
Type: Package
Package: mixsqp
Version: 0.3-17
Date: 2020-01-28
Title: Sequential Quadratic Programming for Fast Maximum-Likelihood Estimation of Mixture Proportions
Authors@R: c(person("Youngseok","Kim",role="aut", email="youngseok@uchicago.edu"), person("Peter","Carbonetto",role=c("aut","cre"), email="peter.carbonetto@gmail.com"), person("Mihai","Anitescu",role="aut"), person("Matthew","Stephens",role="aut"), person("Jason","Willwerscheid",role="ctb"), person("Jean","Morrison",role="ctb"))
URL: https://github.com/stephenslab/mixsqp
BugReports: https://github.com/stephenslab/mixsqp/issues
Depends: R (>= 3.3.0)
Description: Provides an optimization method based on sequential quadratic programming (SQP) for maximum likelihood estimation of the mixture proportions in a finite mixture model where the component densities are known. The algorithm is expected to obtain solutions that are at least as accurate as the state-of-the-art MOSEK interior-point solver (called by function "KWDual" in the 'REBayes' package), and they are expected to arrive at solutions more quickly when the number of samples is large and the number of mixture components is small. This implements the "mix-SQP" algorithm (without the low-rank approximation) described in Y. Kim, P. Carbonetto, M. Stephens & M. Anitescu (2018) <arXiv:1806.01412>.
License: MIT + file LICENSE
Imports: stats, irlba, Rcpp (>= 0.12.15)
Suggests: REBayes, Rmosek, testthat, knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
LazyData: true
NeedsCompilation: yes
VignetteBuilder: knitr
RoxygenNote: 7.0.2
Packaged: 2020-01-28 17:39:25 UTC; pcarbo
Author: Youngseok Kim [aut], Peter Carbonetto [aut, cre], Mihai Anitescu [aut], Matthew Stephens [aut], Jason Willwerscheid [ctb], Jean Morrison [ctb]
Maintainer: Peter Carbonetto <peter.carbonetto@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-29 09:50:03 UTC

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Tue, 28 Jan 2020

New package soilDB with initial version 2.5
Package: soilDB
Type: Package
Title: Soil Database Interface
Version: 2.5
Date: 2020-01-27
Authors@R: c(person(given="Dylan", family="Beaudette", role = c("cre", "aut"), email = "dylan.beaudette@usda.gov"), person(given="Jay", family="Skovlin", role = c("aut")), person(given="Stephen", family="Roecker", role = c("aut")) )
Author: Dylan Beaudette [cre, aut], Jay Skovlin [aut], Stephen Roecker [aut]
Maintainer: Dylan Beaudette <dylan.beaudette@usda.gov>
Description: A collection of functions for reading data from USDA-NCSS soil databases.
License: GPL (>= 3)
LazyLoad: yes
Depends: R (>= 3.0.0)
Imports: aqp, grDevices, graphics, stats, utils, plyr, xml2, sp, reshape2, raster, curl, lattice
Suggests: rgdal, jsonlite, RODBC, httr, rgeos, rvest, testthat, stringr, latticeExtra, RCurl, XML, ggplot2, gridExtra, viridis
Repository: CRAN
URL: http://ncss-tech.github.io/AQP/
BugReports: https://github.com/ncss-tech/soilDB/issues
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-27 19:50:39 UTC; Dylan.Beaudette
Date/Publication: 2020-01-28 20:40:02 UTC

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New package FPDclustering with initial version 1.4.1
Package: FPDclustering
Type: Package
Title: PD-Clustering and Factor PD-Clustering
Version: 1.4.1
Date: 2020-01-28
Author: Cristina Tortora [aut, cre, cph], Noe Vidales [aut], Francesco Palumbo [aut], and Paul D. McNicholas [fnd]
Maintainer: Cristina Tortora <grikris1@gmail.com>
Description: Probabilistic distance clustering (PD-clustering) is an iterative, distribution free, probabilistic clustering method. PD-clustering assigns units to a cluster according to their probability of membership, under the constraint that the product of the probability and the distance of each point to any cluster centre is a constant. PD-clustering is a flexible method that can be used with non-spherical clusters, outliers, or noisy data. PDQ is an extension of the algorithm for clusters of different size. GPDC and TPDC uses a dissimilarity measure based on densities. Factor PD-clustering (FPDC) is a recently proposed factor clustering method that involves a linear transformation of variables and a cluster optimizing the PD-clustering criterion. It works on high dimensional datasets.
Depends: ThreeWay ,mvtnorm,R (>= 3.5)
Imports: ExPosition,cluster,rootSolve
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2020-01-28 18:15:17 UTC; cristina
Repository: CRAN
Date/Publication: 2020-01-28 20:50:05 UTC

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New package HURDAT with initial version 0.2.3.1
Package: HURDAT
Type: Package
Title: Hurricane Re-Analysis Project
Version: 0.2.3.1
Authors@R: c( person("Tim", "Trice", email = "tim.trice@gmail.com", role = c("aut", "cre")), person("Chris", "Landsea", email = "Chris.Landsea@noaa.gov", role = c("aut", "dtc")))
Depends: R (>= 3.5)
Description: Scraped dataset of the Hurricane Research Division's Hurricane Re-Analysis Project known as HURDAT. Storm details are available for most known hurricanes and tropical storms for the Atlantic and northeastern Pacific ocean (northwestern hemisphere). See <http://www.aoml.noaa.gov/hrd/hurdat/Data_Storm.html> for more information.
URL: https://github.com/timtrice/HURDAT
BugReports: https://github.com/timtrice/HURDAT/issues
License: MIT + file LICENSE
Language: en-us
LazyData: TRUE
Imports: dplyr, purrr, readr, rlang, rvest, tidyr, xml2
Suggests: covr, devtools, knitr, testthat, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-01-21 14:17:45 UTC; rstudio-user
Author: Tim Trice [aut, cre], Chris Landsea [aut, dtc]
Maintainer: Tim Trice <tim.trice@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-28 14:20:11 UTC

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New package iNEXT with initial version 2.0.20
Package: iNEXT
Type: Package
Title: Interpolation and Extrapolation for Species Diversity
Version: 2.0.20
Author: T. C. Hsieh, K. H. Ma and Anne Chao
Description: Provides simple functions to compute and plot two types (sample-size- and coverage-based) rarefaction and extrapolation of species diversity (Hill numbers) for individual-based (abundance) data or sampling-unit- based (incidence) data. (Hsieh, Ma and Chao 2014) <doi: 10.1111/2041-210X.12613>.
License: GPL (>= 3)
URL: http://chao.stat.nthu.edu.tw/wordpress/software_download/
Maintainer: T. C. Hsieh <euler96@gmail.com>
Depends: R (>= 3.4)
Imports: stats, graphics, ggplot2, reshape2
BugReports: https://github.com/JohnsonHsieh/iNEXT/issues
LazyLoad: yes
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, gridExtra, ggthemes
VignetteBuilder: knitr
ByteCompile: true
NeedsCompilation: no
Packaged: 2020-01-28 12:36:16 UTC; johnson
Repository: CRAN
Date/Publication: 2020-01-28 13:10:04 UTC

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New package SDEFSR with initial version 0.7.21
Package: SDEFSR
Type: Package
Title: Subgroup Discovery with Evolutionary Fuzzy Systems
Version: 0.7.21
Date: 2020-01-28
Authors@R: c(person("Angel M.", "Garcia", email = "agvico@ujaen.es", role = c("aut", "cre")), person("Pedro", "Gonzalez", email = "pglez@ujaen.es", role = c("aut", "cph")), person("Cristobal J.", "Carmona", email = "ccarmona@ujaen.es", role = c("aut", "cph")), person("Francisco", "Charte", email = "francisco@fcharte.com", role = "ctb"), person("Maria J.", "del Jesus", email = "mjjesus@ujaen.es", role = c("aut", "cph")) )
Maintainer: Angel M. Garcia <agvico@ujaen.es>
Description: Implementation of evolutionary fuzzy systems for the data mining task called "subgroup discovery". In particular, the algorithms presented in this package are: M. J. del Jesus, P. Gonzalez, F. Herrera, M. Mesonero (2007) <doi:10.1109/TFUZZ.2006.890662> M. J. del Jesus, P. Gonzalez, F. Herrera (2007) <doi:10.1109/MCDM.2007.369416> C. J. Carmona, P. Gonzalez, M. J. del Jesus, F. Herrera (2010) <doi:10.1109/TFUZZ.2010.2060200> C. J. Carmona, V. Ruiz-Rodado, M. J. del Jesus, A. Weber, M. Grootveld, P. González, D. Elizondo (2015) <doi:10.1016/j.ins.2014.11.030> It also provide a Shiny App to ease the analysis. The algorithms work with data sets provided in KEEL, ARFF and CSV format and also with data.frame objects.
URL: https://github.com/aklxao2/SDR
Depends: R (>= 3.0.0)
License: LGPL (>= 3)
LazyData: TRUE
Imports: grDevices, methods, parallel, stats, utils
Suggests: ggplot2, knitr, shiny (>= 0.11)
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Author: Angel M. Garcia [aut, cre], Pedro Gonzalez [aut, cph], Cristobal J. Carmona [aut, cph], Francisco Charte [ctb], Maria J. del Jesus [aut, cph]
Packaged: 2020-01-28 11:51:26 UTC; agvico
Encoding: UTF-8
Repository: CRAN
Date/Publication: 2020-01-28 12:40:10 UTC

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New package QRM with initial version 0.4-20
Package: QRM
Version: 0.4-20
Date: 2020-01-27
Title: Provides R-Language Code to Examine Quantitative Risk Management Concepts
Authors@R: c(person("Bernhard", "Pfaff", email = "bernhard@pfaffikus.de", role = c("aut", "cre")), person("Marius", "Hofert", email = "marius.hofert@math.ethz.ch", role = "ctb"), person("Alexander", "McNeil", email = "mcneil@math.ethz.ch", role = "aut", comment = "S-Plus original (QRMlib)"), person("Scott", "Ulmann", role = "trl", comment = "First R port as package QRMlib"))
Author: Bernhard Pfaff [aut, cre], Marius Hofert [ctb], Alexander McNeil [aut] (S-Plus original (QRMlib)), Scott Ulmann [trl] (First R port as package QRMlib)
Maintainer: Bernhard Pfaff <bernhard@pfaffikus.de>
Description: Provides functions/methods to accompany the book Quantitative Risk Management: Concepts, Techniques and Tools by Alexander J. McNeil, Rudiger Frey, and Paul Embrechts.
Depends: R (>= 2.10.0), gsl, Matrix, mvtnorm, numDeriv, timeSeries
Imports: Rcpp (>= 0.11.1), mgcv, methods, timeDate
LinkingTo: Rcpp
LazyData: Yes
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-01-27 21:39:02 UTC; bp
Repository: CRAN
Date/Publication: 2020-01-28 09:20:03 UTC

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Mon, 27 Jan 2020

New package soobench with initial version 1.9.12
Package: soobench
Title: Single Objective Optimization Benchmark Functions
Description: Collection of different single objective test functions useful for benchmarks and algorithm development.
Author: Olaf Mersmann <olafm@p-value.net>, Bernd Bischl <bernd_bischl@gmx.net>, Jakob Bossek <jakob.bossek@tu-dortmund.de> and Leonard Judt <judt@gmx.net>
Maintainer: Eric Kalosa-Kenyon <eric@opsani.com>
License: BSD_2_clause + file LICENSE
LazyData: yes
Version: 1.9.12
Suggests: rgl, testthat
RoxygenNote: 7.0.2
NeedsCompilation: yes
Packaged: 2020-01-27 18:43:02 UTC; eric
Repository: CRAN
Date/Publication: 2020-01-27 23:00:02 UTC

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Sun, 26 Jan 2020

New package shinypanels with initial version 0.5.0
Package: shinypanels
Type: Package
Title: Shiny Layout with Collapsible Panels
Version: 0.5.0
Date: 2020-01-19
Authors@R: person(given = "Juan Pablo", family = "Marin Diaz", role = c("aut", "cre"), email = "jpmarindiaz@gmail.com")
Maintainer: Juan Pablo Marin Diaz <jpmarindiaz@gmail.com>
Description: Create 'Shiny Apps' with collapsible vertical panels. This package provides a new visual arrangement for elements on top of 'Shiny'. Use the expand and collapse capabilities to leverage web applications with many elements to focus the user attention on the panel of interest.
URL: http://github.com/datasketch/shinypanels
Depends: R (>= 3.1.2)
Imports: htmltools, glue, shiny, shinyjs
Suggests: rlang, testthat
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-19 14:54:47 UTC; jpmarindiaz
Author: Juan Pablo Marin Diaz [aut, cre]
Repository: CRAN
Date/Publication: 2020-01-26 10:30:08 UTC

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New package ksharp with initial version 0.1.0.1
Package: ksharp
Title: Cluster Sharpening
Version: 0.1.0.1
Authors@R: person("Tomasz", "Konopka", email = "tokonopka@gmail.com", role = c("aut", "cre"))
Author: Tomasz Konopka [aut, cre]
Maintainer: Tomasz Konopka <tokonopka@gmail.com>
Description: Clustering typically assigns data points into discrete groups, but the clusters can sometimes be indistinct. Cluster sharpening adjusts an existing clustering to create contrast between groups. This package provides a general interface for cluster sharpening along with several implementations based on different excision criteria.
Depends: R (>= 3.5.0)
Imports: methods, stats
License: MIT + file LICENSE
URL: https://github.com/tkonopka/ksharp
BugReports: https://github.com/tkonopka/ksharp/issues
LazyData: true
Suggests: cluster, dbscan, knitr, Rcssplot (>= 1.0.0), rmarkdown, testthat
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-18 15:56:31 UTC; tkonopka
Repository: CRAN
Date/Publication: 2020-01-26 10:10:02 UTC

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New package ddi with initial version 0.1.0
Package: ddi
Type: Package
Title: The Data Defect Index for Samples that May not be IID
Version: 0.1.0
Authors@R: c(person(given = "Shiro", family = "Kuriwaki", role = c("aut", "cre"), email = "shirokuriwaki@gmail.com", comment = c(ORCID = "0000-0002-5687-2647")))
Description: Implements Meng's data defect index (ddi), which represents the degree of sample bias relative to an iid sample. The data defect correlation (ddc) represents the correlation between the outcome of interest and the selection into the sample; when the sample selection is independent across the population, the ddc is zero. Details are in Meng (2018) <doi:10.1214/18-AOAS1161SF>, "Statistical Paradises and Paradoxes in Big Data (I): Law of Large Populations, Big Data Paradox, and the 2016 US Presidential Election." Survey estimates from the Cooperative Congressional Election Study (CCES) is included to replicate the article's results.
Encoding: UTF-8
URL: https://github.com/kuriwaki/ddi
BugReports: http://github.com/kuriwaki/ddi/issues
License: GPL (>= 2)
LazyData: true
RoxygenNote: 7.0.2
Depends: R (>= 2.10)
Suggests: testthat (>= 2.1.0), dplyr, tibble
NeedsCompilation: no
Packaged: 2020-01-19 18:19:38 UTC; shirokuriwaki
Author: Shiro Kuriwaki [aut, cre] (<https://orcid.org/0000-0002-5687-2647>)
Maintainer: Shiro Kuriwaki <shirokuriwaki@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-26 10:50:02 UTC

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New package dccvalidator with initial version 0.1.0
Package: dccvalidator
Title: Metadata Validation for Data Coordinating Centers
Version: 0.1.0
Authors@R: c(person(given = "Kara", family = "Woo", role = c("aut", "cre"), email = "kara.woo@sagebase.org"), person(given = "Sage Bionetworks", role = "cph"), person(given = "Nicole", family = "Kauer", role = "aut", email = "nicole.kauer@sagebase.org"), person(given = "Kelsey", family = "Montgomery", role = "aut", email = "kelsey.montgomery@sagebase.org"), person(given = "Dean", family = "Attali", role = "cph"))
Description: Performs checks for common metadata quality issues. Used by the data coordinating centers for the 'AMP-AD' consortium (<https://adknowledgeportal.synapse.org>), 'PsychENCODE' consortium (<http://www.psychencode.org>), and others to validate metadata prior to data releases.
License: MIT + file LICENSE
URL: https://sage-bionetworks.github.io/dccvalidator, https://github.com/Sage-Bionetworks/dccvalidator
Depends: R (>= 3.4), shinyBS
Imports: config, ggplot2, glue, golem, jsonlite, jsonvalidate, knitr, markdown, purrr, readr, readxl, reticulate, rlang, shiny, shinydashboard, shinyjs, skimr, stats, stringr, tibble, tools, utils, visdat
Suggests: covr, rmarkdown (>= 1.16.2), testthat, withr
VignetteBuilder: knitr
ByteCompile: true
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
SystemRequirements: synapseclient (pypi.org/project/synapseclient)
NeedsCompilation: no
Packaged: 2020-01-18 17:45:11 UTC; kwoo
Author: Kara Woo [aut, cre], Sage Bionetworks [cph], Nicole Kauer [aut], Kelsey Montgomery [aut], Dean Attali [cph]
Maintainer: Kara Woo <kara.woo@sagebase.org>
Repository: CRAN
Date/Publication: 2020-01-26 10:10:05 UTC

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New package caracas with initial version 0.0.1
Package: caracas
Version: 0.0.1
Title: Computer Algebra
Authors@R: c( person(given = "Mikkel Meyer", family = "Andersen", email = "mikl@math.aau.dk", role = c("aut", "cre", "cph")), person(given = "Søren", family = "Højsgaard", email = "sorenh@math.aau.dk", role = c("aut", "cph")) )
Maintainer: Mikkel Meyer Andersen <mikl@math.aau.dk>
Encoding: UTF-8
Description: Computer algebra via the 'SymPy' library (<https://www.sympy.org/>). This makes it possible to solve equations symbolically, find symbolic integrals, symbolic sums and other important quantities.
Depends: R (>= 3.0)
Imports: reticulate (>= 1.14)
Suggests: testthat (>= 2.1.0), knitr, rmarkdown
License: GPL
SystemRequirements: Python (>= 3.6.0)
URL: https://github.com/r-cas/caracas
BugReports: https://github.com/r-cas/caracas/issues
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-19 15:15:11 UTC; mikl
Author: Mikkel Meyer Andersen [aut, cre, cph], Søren Højsgaard [aut, cph]
Repository: CRAN
Date/Publication: 2020-01-26 10:30:11 UTC

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New package birankr with initial version 1.0.0
Package: birankr
Title: Ranking Nodes in Bipartite and Weighted Networks
Version: 1.0.0
Authors@R: c(person("Brian", "Aronson",email = "bdaronson@gmail.com", role = c("aut", "cre")), person("Kai-Cheng", "Yang", email = "yangkc@iu.edu", role = "aut"))
Description: Highly efficient functions for estimating various rank (centrality) measures of nodes in bipartite graphs (two-mode networks). Includes methods for estimating HITS, CoHITS, BGRM, and BiRank with implementation primarily inspired by He et al. (2016) <doi:10.1109/TKDE.2016.2611584>. Also provides easy-to-use tools for efficiently estimating PageRank in one-mode graphs, incorporating or removing edge-weights during rank estimation, projecting two-mode graphs to one-mode, and for converting edgelists and matrices to sparseMatrix format. Best of all, the package's rank estimators can work directly with common formats of network data including edgelists (class data.frame, data.table, or tbl_df) and adjacency matrices (class matrix or dgCMatrix).
Depends: R (>= 3.4.0), Matrix, data.table
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-18 21:50:44 UTC; admin
Author: Brian Aronson [aut, cre], Kai-Cheng Yang [aut]
Maintainer: Brian Aronson <bdaronson@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-26 10:30:13 UTC

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Sat, 25 Jan 2020

New package switchr with initial version 0.14.2
Package: switchr
Type: Package
Title: Installing, Managing, and Switching Between Distinct Sets of Installed Packages
Version: 0.14.2
Author: Gabriel Becker[aut, cre]
Maintainer: Gabriel Becker <gabembecker@gmail.com>
Copyright: Genentech Inc
Description: Provides an abstraction for managing, installing, and switching between sets of installed R packages. This allows users to maintain multiple package libraries simultaneously, e.g. to maintain strict, package-version-specific reproducibility of many analyses, or work within a development/production release paradigm. Introduces a generalized package installation process which supports multiple repository and non-repository sources and tracks package provenance.
Imports: tools, RJSONIO, RCurl
Depends: methods
SystemRequirements: git, svn
License: Artistic-2.0
URL: https://github.com/gmbecker/switchr
BugReports: https://github.com/gmbecker/switchr/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-25 22:41:09 UTC; gabrielbecker
Repository: CRAN
Date/Publication: 2020-01-25 23:20:02 UTC

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Fri, 24 Jan 2020

New package BAS with initial version 1.5.5
Package: BAS
Version: 1.5.5
Date: 2020-1-24
Title: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling
Authors@R: c(person("Merlise", "Clyde", email="clyde@duke.edu", role=c("aut","cre", "cph"), comment=c("ORCID=0000-0002-3595-1872") ), person("Michael", "Littman", role="ctb"), person("Quanli", "Wang", role="ctb"), person("Joyee", "Ghosh", role="ctb"), person("Yingbo", "Li", role="ctb"), person("Don", "van de Bergh", role="ctb"))
Depends: R (>= 3.0)
Imports: stats, graphics, utils, grDevices
Suggests: MASS, knitr, ggplot2, GGally, rmarkdown, roxygen2, dplyr, glmbb, pkgdown, testthat, covr
Description: Package for Bayesian Variable Selection and Model Averaging in linear models and generalized linear models using stochastic or deterministic sampling without replacement from posterior distributions. Prior distributions on coefficients are from Zellner's g-prior or mixtures of g-priors corresponding to the Zellner-Siow Cauchy Priors or the mixture of g-priors from Liang et al (2008) <DOI:10.1198/016214507000001337> for linear models or mixtures of g-priors from Li and Clyde (2019) <DOI:10.1080/01621459.2018.1469992> in generalized linear models. Other model selection criteria include AIC, BIC and Empirical Bayes estimates of g. Sampling probabilities may be updated based on the sampled models using sampling w/out replacement or an efficient MCMC algorithm which samples models using a tree structure of the model space as an efficient hash table. See Clyde, Ghosh and Littman (2010) <DOI:10.1198/jcgs.2010.09049> for details on the sampling algorithms. Uniform priors over all models or beta-binomial prior distributions on model size are allowed, and for large p truncated priors on the model space may be used to enforce sampling models that are full rank. The user may force variables to always be included in addition to imposing constraints that higher order interactions are included only if their parents are included in the model. This material is based upon work supported by the National Science Foundation under Division of Mathematical Sciences grant 1106891. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
License: GPL (>= 3)
URL: https://www.r-project.org, https://github.com/merliseclyde/BAS
BugReports: https://github.com/merliseclyde/BAS/issues
Repository: CRAN
NeedsCompilation: yes
ByteCompile: yes
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.0.2
Packaged: 2020-01-24 21:57:29 UTC; mclyde
Author: Merlise Clyde [aut, cre, cph] (ORCID=0000-0002-3595-1872), Michael Littman [ctb], Quanli Wang [ctb], Joyee Ghosh [ctb], Yingbo Li [ctb], Don van de Bergh [ctb]
Maintainer: Merlise Clyde <clyde@duke.edu>
Date/Publication: 2020-01-24 22:50:14 UTC

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New package fad with initial version 0.2-1
Package: fad
Type: Package
Title: Factor Analysis for Data
Version: 0.2-1
Date: 2020-01-16
Authors@R: c( person("Somak", "Dutta", , "somakd@iastate.edu", c("aut", "cre")), person("Fan", "Dai", , "fd43@iastate.edu", "aut"), person("Ranjan", "Maitra", , "maitra@iastate.edu", "ctb") )
Maintainer: Somak Dutta <somakd@iastate.edu>
Description: Compute maximum likelihood estimators of parameters in a Gaussian factor model using the the matrix-free methodology described in Dai et al. (2019) <doi:10.1080/10618600.2019.1704296>. In contrast to the factanal() function from 'stats' package, fad() can handle high-dimensional datasets where number of variables exceed the sample size and is also substantially faster than the EM algorithms.
License: GPL-3
URL: https://github.com/somakd/fad
BugReports: https://github.com/somakd/fad/issues
Encoding: UTF-8
Depends: R (>= 3.0.2), methods, RSpectra (>= 0.16-0)
Imports: Matrix (>= 1.1-0), Rcpp (>= 0.11.5)
LinkingTo: Rcpp
LazyData: true
NeedsCompilation: yes
Suggests: knitr
VignetteBuilder: knitr
RoxygenNote: 7.0.2
Packaged: 2020-01-17 00:28:47 UTC; somakd
Author: Somak Dutta [aut, cre], Fan Dai [aut], Ranjan Maitra [ctb]
Repository: CRAN
Date/Publication: 2020-01-24 18:20:02 UTC

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New package chilemapas with initial version 0.1.4
Package: chilemapas
Type: Package
Title: Mapas de las Divisiones Politicas y Administrativas de Chile (Maps of the Political and Administrative Divisions of Chile)
Version: 0.1.4
Authors@R: c( person("Mauricio", "Vargas", role = c("aut", "cre"), email = "mvargas@dcc.uchile.cl"), person("Roberto", "Salas", role = "ctb"), person("Joshua", "Kunst", role = "ctb"), person("Juan", "Correa", role = "dtc"), person(given = "Ricardo", family = "Aravena", role = c("ths")), person(family = "Pontificia Universidad Catolica de Chile", role = "cph"), person(family = "Instituto Nacional de Estadisticas (INE)", role = "dtc"), person(family = "Subsecretaria de Desarrollo Regional (SUBDERE)", role = "dtc"), person(family = "Biblioteca del Congreso Nacional de Chile (BCN)", role = "dtc") )
URL: https://pachamaltese.github.io/chilemapas/
BugReports: https://github.com/pachamaltese/chilemapas/issues
Description: Mapas terrestres con topologias simplificadas. Estos mapas no tienen precision geodesica, por lo que aplica el DFL-83 de 1979 de la Republica de Chile y se consideran referenciales sin validez legal. No se incluyen los territorios antarticos y bajo ningun evento estos mapas significan que exista una cesion u ocupacion de territorios soberanos en contra del Derecho Internacional por parte de Chile. Esta paquete esta documentado intencionalmente en castellano asciificado para que funcione sin problema en diferentes plataformas. (Terrestrial maps with simplified toplogies. These maps lack geodesic precision, therefore DFL-83 1979 of the Republic of Chile applies and are consider to have no legal validity. Antartic territories are excluded and under no event these maps mean there is a cession or occupation of sovereign territories against International Laws from Chile. This package was intentionally documented in asciified spanish to make it work with problem on different platforms.)
License: GPL-3
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.0.2
Depends: R(>= 3.5.0), sf
Imports: rmapshaper, dplyr, magrittr, stringr, rlang
Suggests: knitr, rmarkdown, ggplot2, testthat
NeedsCompilation: no
Packaged: 2020-01-17 15:29:48 UTC; mvargass
Author: Mauricio Vargas [aut, cre], Roberto Salas [ctb], Joshua Kunst [ctb], Juan Correa [dtc], Ricardo Aravena [ths], Pontificia Universidad Catolica de Chile [cph], Instituto Nacional de Estadisticas (INE) [dtc], Subsecretaria de Desarrollo Regional (SUBDERE) [dtc], Biblioteca del Congreso Nacional de Chile (BCN) [dtc]
Maintainer: Mauricio Vargas <mvargas@dcc.uchile.cl>
Repository: CRAN
Date/Publication: 2020-01-24 18:50:02 UTC

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New package BioProbability with initial version 1.0
Package: BioProbability
Type: Package
Title: Probability in Biostatistics
Version: 1.0
Author: Alejandro Saavedra-Nieves, Paula Saavedra-Nieves
Maintainer: Paula Saavedra-Nieves <paula.saavedra@usc.es>
Description: Several tools for analyzing diagnostic tests and 2x2 contingency tables are provided. In particular, positive and negative predictive values for a diagnostic tests can be calculated from prevalence, sensitivity and specificity values. For contingency tables, relative risk and odds ratio measures are estimated. Furthermore, confidence intervals are provided.
License: GPL-2
NeedsCompilation: no
Packaged: 2020-01-16 08:26:39 UTC; alexs
Repository: CRAN
Date/Publication: 2020-01-24 18:10:07 UTC

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New package USgrid with initial version 0.1.0
Package: USgrid
Type: Package
Title: The Demand and Supply for Electricity in the US
Version: 0.1.0
Authors@R: person("Rami", "Krispin", email = "rami.krispin@gmail.com", role = c("aut", "cre"))
Maintainer: Rami Krispin <rami.krispin@gmail.com>
Description: Provides a set of regular time-series datasets, describing the US electricity grid. That includes the total demand and supply, and as well as the demand by energy source (coal, solar, wind, etc.). Source: US Energy Information Administration (Dec 2019) <https://www.eia.gov/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.2)
Imports: tsibble(>= 0.8.5)
Suggests: knitr, lubridate, rmarkdown, devtools, plotly, remotes, tidyr, testthat, usethis
URL: https://github.com/RamiKrispin/USgrid
BugReports: https://github.com/RamiKrispin/USgrid/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-16 16:41:54 UTC; ramikrispin
Author: Rami Krispin [aut, cre]
Repository: CRAN
Date/Publication: 2020-01-24 17:20:06 UTC

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New package signnet with initial version 0.5.0
Package: signnet
Title: Methods to Analyse Signed Networks
Version: 0.5.0
Authors@R: person(given = "David", family = "Schoch", role = c("aut", "cre"), email = "david.schoch@manchester.ac.uk")
Description: Methods for the analysis of signed networks. This includes several measures for structural balance as introduced by Cartwright and Harary (1956) <doi:10.1037/h0046049>, blockmodeling algorithms from Doreian (2008) <doi:10.1016/j.socnet.2008.03.005>, various centrality indices, and projections of signed two-mode networks introduced by Schoch (2020) <doi:10.1080/0022250X.2019.1711376>.
Depends: R (>= 3.2.0)
URL: https://github.com/schochastics/signnet
BugReports: https://github.com/schochastics/signnet/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: igraph, Rcpp, Matrix
RoxygenNote: 7.0.2
Suggests: testthat (>= 2.1.0), covr, ggplot2, ggraph, knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-16 13:10:02 UTC; david
Author: David Schoch [aut, cre]
Maintainer: David Schoch <david.schoch@manchester.ac.uk>
Repository: CRAN
Date/Publication: 2020-01-24 17:20:02 UTC

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New package santoku with initial version 0.3.0
Package: santoku
Type: Package
Title: A Versatile Cutting Tool
Version: 0.3.0
Authors@R: person(given = "David", family = "Hugh-Jones", role = c("aut", "cre"), email = "davidhughjones@gmail.com")
Author: David Hugh-Jones [aut, cre]
Maintainer: David Hugh-Jones <davidhughjones@gmail.com>
Description: A tool for cutting data into intervals. Allows singleton intervals. Always includes the whole range of data by default. Flexible labelling. Convenience functions for cutting by quantiles etc.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: covr, testthat (>= 2.1.0), knitr, microbenchmark, rmarkdown
LinkingTo: Rcpp
Imports: Rcpp, assertthat
URL: https://github.com/hughjonesd/santoku, https://hughjonesd.github.io/santoku/
BugReports: https://github.com/hughjonesd/santoku/issues
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-16 12:26:54 UTC; david
Repository: CRAN
Date/Publication: 2020-01-24 17:10:02 UTC

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New package round with initial version 0.12-1
Package: round
Version: 0.12-1
Date: 2020-01-15
Title: Rounding to Decimal Digits
Authors@R: c(person("Martin","Maechler", role=c("aut","cre"), email="maechler@stat.math.ethz.ch", comment = c(ORCID = "0000-0002-8685-9910")) , person("R-core", email = "R-core@R-project.org", role = "ctb", comment = '"r1.C" only') )
Description: Decimal rounding is non-trivial in binary arithmetic. ISO standard round to even is more rare than typically assumed as most decimal fractions are not exactly representable in binary. Our roundX() versions explore differences between current and potential future versions of round() in R. Further, provides (some partly related) C99 math lib functions not in base R.
Imports: stats
Suggests: grDevices, graphics, Matrix, lattice, knitr
License: AGPL (>= 3)
Encoding: UTF-8
VignetteBuilder: knitr
URL: https://gitlab.com/mmaechler/round/
BugReports: https://gitlab.com/mmaechler/round/issues
NeedsCompilation: yes
Packaged: 2020-01-15 11:46:58 UTC; maechler
Author: Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>), R-core [ctb] ("r1.C" only)
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>
Repository: CRAN
Date/Publication: 2020-01-24 18:00:03 UTC

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New package gridtext with initial version 0.1.0
Package: gridtext
Type: Package
Title: Improved Text Rendering Support for 'Grid' Graphics
Version: 0.1.0
Authors@R: person( given = "Claus O.", family = "Wilke", role = c("aut", "cre"), email = "wilke@austin.utexas.edu", comment = c(ORCID = "0000-0002-7470-9261") )
Description: Provides support for rendering of formatted text using 'grid' graphics. Text can be formatted via a minimal subset of 'Markdown', 'HTML', and inline 'CSS' directives, and it can be rendered both with and without word wrap.
URL: https://wilkelab.org/gridtext
BugReports: https://github.com/wilkelab/gridtext/issues
License: MIT + file LICENSE
Depends: R (>= 3.5)
Imports: grid, grDevices, markdown, rlang, Rcpp, RCurl, png, jpeg, stringr, xml2
Suggests: covr, knitr, rmarkdown, testthat, vdiffr
LinkingTo: Rcpp, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2020-01-16 18:37:10 UTC; clauswilke
Author: Claus O. Wilke [aut, cre] (<https://orcid.org/0000-0002-7470-9261>)
Maintainer: Claus O. Wilke <wilke@austin.utexas.edu>
Repository: CRAN
Date/Publication: 2020-01-24 17:30:02 UTC

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New package GADGET with initial version 0.2.0
Package: GADGET
Title: Gaussian Process Approximations for Designing Experiments
Version: 0.2.0
Authors@R: c(person(given = "Isaac", family = "Michaud", role = c("aut", "cre"), email = "imichaud@lanl.gov"), person(given = "Brian", family = "Weaver", role = "aut"), person(given = "Brian", family = "Williams", role = "aut"))
Description: Computes near-optimal Bayesian experimental designs with Gaussian processes optimization following the algorithm presented by B. Weaver, et al. (2016) <doi:10.1214/15-BA945> for either physical or sequential computer experiments.
License: BSD_3_clause + file LICENSE
Copyright: see file COPYRIGHTS
LazyData: TRUE
Encoding: UTF-8
RoxygenNote: 7.0.2
Imports: DiceKriging, DiceOptim, lhs, pbapply, utils, graphics, stats
Suggests: testthat, parallel
NeedsCompilation: no
Maintainer: Isaac Michaud <imichaud@lanl.gov>
BugReports: https://github.com/isaacmichaud/GADGET/issues
Packaged: 2020-01-16 18:50:39 UTC; isaacmichaud
Author: Isaac Michaud [aut, cre], Brian Weaver [aut], Brian Williams [aut]
Repository: CRAN
Date/Publication: 2020-01-24 17:30:11 UTC

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New package fdaACF with initial version 0.1.0
Package: fdaACF
Type: Package
Title: Autocorrelation Function for Functional Time Series
Version: 0.1.0
Date: 2020-01-16
Author: Guillermo Mestre Marcos [aut, cre], José Portela González [aut], Antonio Muñoz San Roque [ctb], Estrella Alonso Pérez [ctb]
Maintainer: Guillermo Mestre Marcos <guillermo.mestre@comillas.edu>
Description: Quantify the serial correlation across lags of a given functional time series using an autocorrelation function for functional time series. The autocorrelation function is based on the L2 norm of the lagged covariance operators of the series. Functions are available for estimating the distribution of the autocorrelation function under the assumption of strong functional white noise.
Imports: CompQuadForm, pracma
NeedsCompilation: no
URL: https://github.com/GMestreM/fdaACF
BugReports: https://github.com/GMestreM/fdaACF/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Authors@R: c( person(given = "Guillermo", family = "Mestre Marcos", email = "guillermo.mestre@comillas.edu", role = c("aut", "cre")), person(given = "José", family = "Portela González", email = "Jose.Portela@iit.comillas.edu", role = "aut"), person(given = "Antonio", family = "Muñoz San Roque", email = "antonio.munoz@iit.comillas.edu", role = "ctb"), person(given = "Estrella", family = "Alonso Pérez", email = "ealonso@icai.comillas.edu", role = "ctb") )
RoxygenNote: 7.0.1
Suggests: testthat, fields
Packaged: 2020-01-16 11:43:27 UTC; gmestre
Repository: CRAN
Date/Publication: 2020-01-24 17:10:06 UTC

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New package datanugget with initial version 1.0.0
Package: datanugget
Type: Package
Title: Create, Refine, and Cluster Data Nuggets
Version: 1.0.0
Date: 2020-1-16
Authors@R: c( person("Traymon", "Beavers", email = "tray.beavers@gmail.com", role = c("aut", "cre")), person("Javier", "Cabrera", email = "xavier.cabrera@gmail.com", role = "aut"), person("Mariusz", "Lubomirski", email = "mlubomir@its.jnj.com", role = "aut"))
Author: Traymon Beavers [aut, cre], Javier Cabrera [aut], Mariusz Lubomirski [aut]
Maintainer: Traymon Beavers <tray.beavers@gmail.com>
Description: Creating, refining, and clustering data nuggets. Data nuggets reduce a large dataset into a small collection of nuggets of data, each containing a center (location), weight (importance), and scale (variability) parameter. Data nugget centers are created by choosing observations in the dataset which are as equally spaced apart as possible. Data nugget weights are created by counting the number observations closest to a given data nugget’s center. We then say the data nugget 'contains' these observations and the data nugget center is recalculated as the mean of these observations. Data nugget scales are created by calculating the trace of the covariance matrix of the observations contained within a data nugget divided by the dimension of the dataset. Data nuggets are refined by 'splitting' data nuggets which have scales or shapes (defined as the ratio of the two largest eigenvalues of the covariance matrix of the observations contained within the data nugget) deemed too large. Data nuggets are clustered by using a weighted form of k-means clustering which uses both the centers and weights of data nuggets to optimize the clustering assignments.
Depends: R (>= 3.5.0), doSNOW (>= 1.0.16), foreach (>= 1.4.4), parallel (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-16 20:25:52 UTC; tbeaver2
Repository: CRAN
Date/Publication: 2020-01-24 17:30:08 UTC

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New package Rdta with initial version 1.0.0
Package: Rdta
Version: 1.0.0
Date: 2020-1-7
Title: Data Transforming Augmentation for Linear Mixed Models
Author: Hyungsuk Tak, Kisung You, Sujit K. Ghosh, and Bingyue Su
Maintainer: Hyungsuk Tak <hyungsuk.tak@gmail.com>
Depends: R (>= 2.2.0)
Imports: MCMCpack(>= 1.4-4), mvtnorm(>= 1.0-11), Rdpack, stats
Description: We provide a toolbox to fit univariate and multivariate linear mixed models via data transforming augmentation. Users can also fit these models via typical data augmentation for a comparison. It returns either maximum likelihood estimates of unknown model parameters (hyper-parameters) via an EM algorithm or posterior samples of those parameters via a Markov chain Monte Carlo method. Also see Tak, You, Ghosh, Su, and Kelly (2019+) <doi:10.1080/10618600.2019.1704295> <arXiv:1911.02748>.
License: GPL-2
Encoding: UTF-8
RdMacros: Rdpack
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-15 20:48:04 UTC; hyungsuktak
Repository: CRAN
Date/Publication: 2020-01-24 16:50:03 UTC

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New package nlist with initial version 0.1.0
Package: nlist
Title: Lists of Numeric Atomic Objects
Version: 0.1.0
Authors@R: c( person("Joe", "Thorley", , "joe@poissonconsulting.ca", c("aut", "cre"), comment = c(ORCID = "0000-0002-7683-4592")), person("Poisson Consulting", role = c("cph", "fnd")) )
Description: Create and manipulate numeric list (nlist) objects. An nlist is an S3 list of uniquely named numeric atomic (natomic) objects. An natomic object is an integer or double vector, matrix or array. An nlists object is a S3 class list of nlist objects with the same names, dimensionalities and typeofs. Numeric list objects are of interest because they are the raw data inputs for analytic engines such as 'JAGS', 'STAN' and 'TMB'. Numeric lists objects, which are useful for storing multiple realizations of of simulated data sets, can be converted to coda::mcmc and coda::mcmc.list objects.
License: MIT + file LICENSE
Depends: R (>= 3.3)
Imports: stats, chk, term (>= 0.1.0), coda, abind, purrr
Suggests: covr, testthat
URL: https://github.com/poissonconsulting/nlist
BugReports: https://github.com/poissonconsulting/nlist/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Language: en-US
NeedsCompilation: no
Packaged: 2020-01-15 23:54:32 UTC; joe
Author: Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>), Poisson Consulting [cph, fnd]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>
Repository: CRAN
Date/Publication: 2020-01-24 17:00:02 UTC

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Thu, 23 Jan 2020

New package bamp with initial version 2.0.8
Package: bamp
Type: Package
Title: Bayesian Age-Period-Cohort Modeling and Prediction
Version: 2.0.8
Date: 2020-01-21
Author: Volker Schmid [aut, cre], Florian Geressen [ctb], Leonhard Held [ctb], Evi Rainer [ctb]
Authors@R: c(person("Volker","Schmid",email="volker.schmid@lmu.de", role=c("aut","cre")),person("Florian","Geressen",role="ctb"), person("Leonhard","Held",role="ctb"),person("Evi","Rainer",role="ctb"))
Maintainer: Volker Schmid <volker.schmid@lmu.de>
Description: Bayesian Age-Period-Cohort Modeling and Prediction using efficient Markov Chain Monte Carlo Methods. This is the R version of the previous BAMP software as described in Volker Schmid and Leonhard Held (2007) <DOI:10.18637/jss.v021.i08> Bayesian Age-Period-Cohort Modeling and Prediction - BAMP, Journal of Statistical Software 21:8. This package includes checks of convergence using Gelman's R.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: coda, graphics, parallel, stats, abind
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr, R.rsp
Suggests: knitr, rmarkdown, R.rsp
URL: https://volkerschmid.github.io/bamp/
BugReports: https://github.com/volkerschmid/bamp/issues
NeedsCompilation: yes
Packaged: 2020-01-21 21:49:52 UTC; schmid
Repository: CRAN
Date/Publication: 2020-01-23 22:50:12 UTC

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New package SNSequate with initial version 1.3.2
Package: SNSequate
Version: 1.3.2
Date: 2020-01-22
Title: Standard and Nonstandard Statistical Models and Methods for Test Equating
Authors@R: c( person("Jorge", "Gonzalez", email = "jorge.gonzalez@mat.uc.cl", role = c("cre","aut")), person("Daniel", "Leon Acuna", email = "dnacuna@uc.cl", role = "ctb"))
Maintainer: Jorge Gonzalez <jorge.gonzalez@mat.uc.cl>
Depends: R (>= 3.1.0), magic, stats
Imports: methods, emdbook, plyr, statmod, knitr, progress
Description: Contains functions to perform various models and methods for test equating. It currently implements the traditional mean, linear and equipercentile equating methods. Both IRT observed-score and true-score equating are also supported, as well as the mean-mean, mean-sigma, Haebara and Stocking-Lord IRT linking methods. It also supports newest methods such that local equating, kernel equating (using Gaussian, logistic, Epanechnikov, uniform and adaptive kernels) with presmoothing, and IRT parameter linking methods based on asymmetric item characteristic functions. Functions to obtain both standard error of equating (SEE) and standard error of equating differences between two equating functions (SEED) are also implemented for the kernel method of equating.
License: GPL (>= 2)
URL: http://www.mat.uc.cl/~jorge.gonzalez
Suggests: testthat
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2020-01-23 17:02:09 UTC; jgonzale
Author: Jorge Gonzalez [cre, aut], Daniel Leon Acuna [ctb]
Repository: CRAN
Date/Publication: 2020-01-23 17:30:14 UTC

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New package rarms with initial version 1.0.0
Package: rarms
Type: Package
Title: Access Data from the USDA ARMS Data API
Version: 1.0.0
Authors@R: c(person(given = "Bowen", family = "Chen", role = c("aut", "cre"), email = "bwchen0719@gmail.com", comment = c(ORCID = "0000-0003-0370-2756")), person(given = "Benjamin", family = "Gramig", role = "ctb"))
Description: Interface to easily access data via the United States Department of Agriculture (USDA)'s Agricultural Resource Management Survey (ARMS) Data API <https://www.ers.usda.gov/developer/data-apis/arms-data-api/>. The downloaded data can be saved for later off-line use. Also provide relevant information and metadata for each of the input variables needed for sending the data inquery.
Encoding: UTF-8
License: GPL (>= 2)
LazyData: true
RoxygenNote: 7.0.2
Depends: R (>= 3.6.0)
Imports: jsonlite (>= 1.6)
NeedsCompilation: no
Packaged: 2020-01-13 04:25:57 UTC; bwchen
Author: Bowen Chen [aut, cre] (<https://orcid.org/0000-0003-0370-2756>), Benjamin Gramig [ctb]
Maintainer: Bowen Chen <bwchen0719@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-23 17:30:02 UTC

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New package NLMR with initial version 1.0
Package: NLMR
Type: Package
Title: Simulating Neutral Landscape Models
Version: 1.0
Authors@R: c(person("Marco", "Sciaini", email = "sciaini.marco@gmail.com", role = c("aut", "cre"), comment = c(ORCID = '0000-0002-3042-5435')), person("Matthias", "Fritsch", email = "matthias.fritsch@forst.uni-goettingen.de", role = "aut"), person("Craig", "Simpkins", email = "simpkinscraig063@gmail.com", role = "aut", comment = c(ORCID = '0000-0003-3212-1379')), person("Cédric", "Scherer", email = "cedricphilippscherer@gmail.com", role = c("aut"), comment = c(ORCID = '0000-0003-0465-2543')), person("Sebastian", "Hanß", role = "aut", comment = c(ORCID = '0000-0002-3990-4897')), person("Laura", "Graham", role = "rev", comment = "Laura reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/188"), person("Jeffrey", "Hollister", role = "rev", comment = "Jeffrey reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/188"))
Maintainer: Marco Sciaini <sciaini.marco@gmail.com>
Description: Provides neutral landscape models (<doi:10.1007/BF02275262>, <http://sci-hub.tw/10.1007/bf02275262>). Neutral landscape models range from "hard" neutral models (completely random distributed), to "soft" neutral models (definable spatial characteristics) and generate landscape patterns that are independent of ecological processes. Thus, these patterns can be used as null models in landscape ecology. 'nlmr' combines a large number of algorithms from other published software for simulating neutral landscapes. The simulation results are obtained in a geospatial data format (raster* objects from the 'raster' package) and can, therefore, be used in any sort of raster data operation that is performed with standard observation data.
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 3.1.0)
SystemRequirements: C++11
RoxygenNote: 6.1.1
Imports: checkmate, dplyr, RandomFields, raster, spatstat, stats, tibble, fasterize, sf, Rcpp
URL: https://ropensci.github.io/NLMR/
BugReports: https://github.com/ropensci/NLMR/issues/
Suggests: testthat, covr, captioner, knitr, rmarkdown, lintr, landscapetools, igraph
LinkingTo: Rcpp
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-23 12:48:09 UTC; marco
Author: Marco Sciaini [aut, cre] (<https://orcid.org/0000-0002-3042-5435>), Matthias Fritsch [aut], Craig Simpkins [aut] (<https://orcid.org/0000-0003-3212-1379>), Cédric Scherer [aut] (<https://orcid.org/0000-0003-0465-2543>), Sebastian Hanß [aut] (<https://orcid.org/0000-0002-3990-4897>), Laura Graham [rev] (Laura reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/188), Jeffrey Hollister [rev] (Jeffrey reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/188)
Repository: CRAN
Date/Publication: 2020-01-23 17:50:02 UTC

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New package netstat with initial version 0.1.1
Package: netstat
Type: Package
Title: Retrieve Network Statistics Including Available TCP Ports
Version: 0.1.1
Authors@R: c( person("Steve", "Condylios", , "steve.condylios@gmail.com", c("aut", "cre"), comment = c(ORCID = "0000-0003-0599-844X")) )
Maintainer: Steve Condylios <steve.condylios@gmail.com>
BugReports: https://github.com/stevecondylios/netstat/issues
URL: https://github.com/stevecondylios/netstat
Description: R interface for the 'netstat' command line utility used to retrieve and parse commonly used network statistics, including available and in-use transmission control protocol (TCP) ports. Primers offering technical background information on the 'netstat' command line utility are available in the "Linux System Administrator's Manual" by Michael Kerrisk (2014) <http://man7.org/linux/man-pages/man8/netstat.8.html>, and on the Microsoft website (2017) <https://docs.microsoft.com/en-us/windows-server/administration/windows-commands/netstat>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: utils
Language: en-US
NeedsCompilation: no
Packaged: 2020-01-13 02:09:26 UTC; st
Author: Steve Condylios [aut, cre] (<https://orcid.org/0000-0003-0599-844X>)
Repository: CRAN
Date/Publication: 2020-01-23 17:30:05 UTC

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New package metropolis with initial version 0.1.5
Package: metropolis
Title: The Metropolis Algorithm
Version: 0.1.5
Date: 2020-01-12
Authors@R: person(given = "Alexander", family = "Keil", role = c("aut", "cre"), email = "akeil@unc.edu")
Author: Alexander Keil [aut, cre]
Maintainer: Alexander Keil <akeil@unc.edu>
Description: Learning and using the Metropolis algorithm for Bayesian fitting of a generalized linear model. The package vignette includes examples of hand-coding a logistic model using several variants of the Metropolis algorithm. The package also contains R functions for simulating posterior distributions of Bayesian generalized linear model parameters using guided, adaptive, guided-adaptive and random walk Metropolis algorithms. The random walk Metropolis algorithm was originally described in Metropolis et al (1953) <doi:10.1063/1.1699114>.
License: GPL (>= 2)
Depends: coda, R (>= 3.5.0)
Imports: stats
Suggests: knitr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-13 01:19:36 UTC; akeil
Repository: CRAN
Date/Publication: 2020-01-23 17:30:07 UTC

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New package spiR with initial version 0.1.1
Package: spiR
Type: Package
Title: Wrapper for the Social Progress Index Data
Version: 0.1.1
Authors@R: person("Thierry", "Warin", email = "thierry.warin@skema.edu", role =c("aut", "cre"), comment = c(ORCID = "0000-0002-5921-3428") )
Description: In 2015, The 17 United Nations' Sustainable Development Goals were adopted. 'spiR' is a wrapper of several open datasets published by the Social Progress Imperative (<https://www.socialprogress.org/>), including the Social Progress Index (a synthetic measure of human development across the world). 'spiR''s goal is to provide data to help policymakers and researchers prioritize actions that accelerate social progress across the world in the context of the Sustainable Development Goals. Please cite: Warin, Th. (2019) "spiR: An R Package for the Social Progress Index", <doi:10.6084/m9.figshare.11421573>.
Imports: gsheet, dplyr,reshape2
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-12 16:00:12 UTC; warint
Author: Thierry Warin [aut, cre] (<https://orcid.org/0000-0002-5921-3428>)
Maintainer: Thierry Warin <thierry.warin@skema.edu>
Repository: CRAN
Date/Publication: 2020-01-23 16:20:02 UTC

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New package heddlr with initial version 0.5.0
Package: heddlr
Title: Dynamic R Markdown Document Generation
Version: 0.5.0
Authors@R: person(given = "Michael", family = "Mahoney", role = c("aut", "cre"), email = "mike.mahoney.218@gmail.com", comment = c(ORCID = "0000-0003-2402-304X"))
Description: Helper functions designed to make dynamically generating R Markdown documents easier by providing a simple and tidy way to create report pieces, shape them to your data, and combine them for exporting into a single R Markdown document.
License: MIT + file LICENSE
URL: https://github.com/mikemahoney218/heddlr, https://mikemahoney218.github.io/heddlr/
BugReports: https://github.com/mikemahoney218/heddlr/issues
Depends: R (>= 3.4.0)
Imports: rlang (>= 0.1.2), utf8, yaml
Suggests: covr, here, rmarkdown, roxygen2, testthat (>= 2.1.0), dplyr, tidyr (>= 1.0.0), nycflights13, ggplot2, knitr, purrr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-12 16:41:56 UTC; mikemahoney218
Author: Michael Mahoney [aut, cre] (<https://orcid.org/0000-0003-2402-304X>)
Maintainer: Michael Mahoney <mike.mahoney.218@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-23 16:30:02 UTC

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New package gwsem with initial version 0.1.10
Package: gwsem
Type: Package
Title: Genome-Wide Structural Equation Modeling
Version: 0.1.10
Authors@R: c(person(c("Joshua", "N."), "Pritikin", email="jpritikin@pobox.com", role=c("aut", 'cre')), person("Bradley", "Verhulst", role="cph", email="brad.verhulst@gmail.com"), person("Gavin", "Band", role="cph"), person("Yann", "Collet", role="cph"), person("Facebook, Inc.", role="cph"), person("Yuta", "Mori", role="cph"), person("Shaun", "Purcell", role="cph"), person("Christopher", "Chang", role="cph"), person("Wojciech", "Mula", role="cph"), person("Kim", "Walisch", role="cph"))
Description: Melds genome-wide association tests with structural equation modeling (SEM) using 'OpenMx'. This package contains low-level C/C++ code to rapidly read genetic data encoded in U.K. Biobank or 'plink' formats. Prebuilt modeling options include one and two factor models. Alternately, analyses may utilize arbitrary, user-provided SEMs. See Verhulst, Maes, & Neale (2017) <doi:10.1007/s10519-017-9842-6> for details. An updated manuscript is in preparation.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Language: en-US
LinkingTo: BH (>= 1.69.0-1), Rcpp
Depends: R (>= 3.5), OpenMx (>= 2.15.5)
Imports: data.table, methods, qqman, Rcpp
Suggests: testthat (>= 2.1.0), MASS, covr, knitr, rmarkdown
RoxygenNote: 7.0.2
SystemRequirements: GNU make
URL: https://github.com/jpritikin/gwsem
BugReports: https://github.com/jpritikin/gwsem/issues
NeedsCompilation: yes
VignetteBuilder: knitr
Packaged: 2020-01-23 15:09:36 UTC; joshua
Author: Joshua N. Pritikin [aut, cre], Bradley Verhulst [cph], Gavin Band [cph], Yann Collet [cph], Facebook, Inc. [cph], Yuta Mori [cph], Shaun Purcell [cph], Christopher Chang [cph], Wojciech Mula [cph], Kim Walisch [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>
Repository: CRAN
Date/Publication: 2020-01-23 16:30:05 UTC

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New package depcoeff with initial version 0.0.1
Package: depcoeff
Title: Dependency Coefficients
Type: Package
Version: 0.0.1
Date: 2019-12-23
Author: Eckhard Liebscher
Maintainer: Eckhard Liebscher <eckhard.liebscher@hs-merseburg.de>
Description: Functions to compute coefficients measuring the dependence of two or more than two variables. The functions can be deployed to gain information about functional dependencies of the variables with emphasis on monotone functions. The statistics describe how well one response variable can be approximated by a monotone function of other variables. In regression analysis the variable selection is an important issue. In this framework the functions could be useful tools in modeling the regression function. Detailed explanations on the subject can be found in papers Liebscher (2014) <doi:10.2478/demo-2014-0004>; Liebscher (2017) <doi:10.1515/demo-2017-0012>; Liebscher (2019, submitted).
Depends: R (>= 3.5.0)
Suggests: MASS
License: GPL-2
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp, copula
RoxygenNote: 7.0.2
NeedsCompilation: yes
Packaged: 2019-12-23 15:27:38 UTC; spillner
Repository: CRAN
Date/Publication: 2020-01-23 16:20:05 UTC

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New package Bvalue with initial version 1.0
Package: Bvalue
Type: Package
Title: B-Value and Empirical Equivalence Bound
Version: 1.0
Date: 2020-01-08
Author: Yi Zhao <zhaoyi1026@gmail.com> Brian Caffo <bcaffo@gmail.com> Joshua Ewen <ewen@kennedykrieger.org>
Maintainer: Yi Zhao <zhaoyi1026@gmail.com>
Description: Calculates B-value and empirical equivalence bound. B-value is defined as the maximum magnitude of a confidence interval; and the empirical equivalence bound is the minimum B-value at a certain level. A new two-stage procedure for hypothesis testing is proposed, where the first stage is conventional hypothesis testing and the second is an equivalence testing procedure using the introduced empirical equivalence bound. See Zhao et al. (2019) "B-Value and Empirical Equivalence Bound: A New Procedure of Hypothesis Testing" <arXiv:1912.13084> for details.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2020-01-12 19:46:51 UTC; yizhao
Repository: CRAN
Date/Publication: 2020-01-23 16:50:02 UTC

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New package splitTools with initial version 0.1.0
Type: Package
Package: splitTools
Title: Tools for Data Splitting
Version: 0.1.0
Date: 2020-01-12
Authors@R: person(given = "Michael", family = "Mayer", role = c("aut", "cre", "cph"), email = "mayermichael79@gmail.com")
Maintainer: Michael Mayer <mayermichael79@gmail.com>
Description: Fast, lightweight toolkit for data splitting. Data sets can be partitioned into disjoint groups (e.g. into training, validation, and test) or into (repeated) k-folds for subsequent cross-validation. Besides basic splits, the package supports stratified as well as grouped splitting. See e.g. Hastie et al. (2001) <doi:10.1007/978-0-387-84858-7> for the basic background on data partitioning and cross-validation.
License: GPL (>= 2)
URL: https://github.com/mayer79/splitTools
BugReports: https://github.com/mayer79/splitTools/issues
Depends: R (>= 3.5.0)
Encoding: UTF-8
LazyData: true
Imports: stats
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-12 14:29:57 UTC; Michael
Author: Michael Mayer [aut, cre, cph]
Repository: CRAN
Date/Publication: 2020-01-23 16:00:02 UTC

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New package icrf with initial version 1.0.0
Package: icrf
Title: Interval Censored Recursive Forests
Version: 1.0.0
Date: 2019-12-25
Depends: R (>= 3.5.0), stats
Imports: Icens
Suggests: survival, ggplot2
Authors@R: c(person(given = c("Hunyong"), family = "Cho", email = "hunycho@live.unc.edu", role = c("aut", "cre")), person(given = c("Nicholas", "P"), family = "Jewell", role = c("aut")), person(given = c("Michael", "R"), family = "Kosorok", role = c("aut")), person("Leo", "Breiman", role = "ctb", comment = "Author of incldued randomForest C codes"), person("Adele", "Cutler", role = "ctb", comment = "Author of included randomForest Fortran codes"), person("Andy", "Liaw", role = "ctb", comment = "Author of included randomForest R codes"), person("Matthew", "Wiener", role = "ctb", comment = "Author of included randomForest R codes"), person("Merck & Co. Inc.", role = "cph", comment = "Copyright holder of included randomForest R codes"), person("The R Foundation", role = "cph", comment = "Copyright holder of included ksmooth C codes"))
Description: Implements interval censored recursive forests (ICRF) based on Cho, Jewell, and Kosorok (2020+). ICRF is a variant of random forests where the outcome variable is interval censored survival data. It can be used for usual right censored data and current status data as well. A recursion technique is used to improve accuracy and smoothed survival curves are provided.
Maintainer: Hunyong Cho <hunycho@live.unc.edu>
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2020-01-12 11:28:57 UTC; hycho
Repository: CRAN
Date/Publication: 2020-01-23 15:30:02 UTC
RoxygenNote: 6.1.1
Author: Hunyong Cho [aut, cre], Nicholas P Jewell [aut], Michael R Kosorok [aut], Leo Breiman [ctb] (Author of incldued randomForest C codes), Adele Cutler [ctb] (Author of included randomForest Fortran codes), Andy Liaw [ctb] (Author of included randomForest R codes), Matthew Wiener [ctb] (Author of included randomForest R codes), Merck & Co. Inc. [cph] (Copyright holder of included randomForest R codes), The R Foundation [cph] (Copyright holder of included ksmooth C codes)

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New package flying with initial version 0.1.1
Package: flying
Type: Package
Title: Simulation of Bird Flight Range
Version: 0.1.1
Authors@R: c(person(family = "Masinde", given = "Brian", role = c("aut", "cre"), email= "masindeb@live.com"), person(family = "Bartoszek", given = "Krzysztof", role = c("ctb", "ths"), email= "krzbar@protonmail.ch"))
Description: Functions for range estimation in birds based on Pennycuick (2008) and Pennycuick (1975), 'Flight' program which compliments Pennycuick (2008) requires manual entry of birds which can be tedious when there are thousands of birds to estimate. Implemented are two ODE methods discussed in Pennycuick (1975) and time-marching computation method "constant muscle mass" as in Pennycuick (1998). See Pennycuick (1975, ISBN:978-0-12-249405-5), Pennycuick (1998) <doi:10.1006/jtbi.1997.0572>, and Pennycuick (2008, ISBN:9780080557816).
License: Apache License
Encoding: UTF-8
LazyData: true
Imports: utils, Rcpp (>= 1.0.2), knitr, rmarkdown, kableExtra
Suggests: testthat, covr
RoxygenNote: 7.0.0
Depends: R (>= 2.10)
VignetteBuilder: knitr
Collate: 'RcppExports.R' 'birds_documentation.R' 'constant_muscle_mass.R' 'control.R' 'method_2.R' 'method_1.R' 'input_match.R' 'lookup_table2.R' 'misc_functions.R' 'flight_simulation.R' 'flying.R' 'migrate.R' 'zzz.R'
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-01-12 14:49:07 UTC; masinde
Author: Brian Masinde [aut, cre], Krzysztof Bartoszek [ctb, ths]
Maintainer: Brian Masinde <masindeb@live.com>
Repository: CRAN
Date/Publication: 2020-01-23 16:00:05 UTC

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New package progressr with initial version 0.4.0
Package: progressr
Version: 0.4.0
Title: A Unifying API for Progress Updates
Description: A minimal, unifying API for scripts and packages to report progress updates from anywhere including when using parallel processing. The package is designed such that the developer can to focus on what progress should be reported on without having to worry about how to present it. The end user has full control of how, where, and when to render these progress updates, e.g. in the terminal using 'utils::txtProgressBar()' or 'progress::progress_bar()', in a graphical user interface using 'utils::winProgressBar()', 'tcltk::tkProgressBar()' or 'shiny::withProgress()', via the speakers using 'beep::beepr()', or on a file system via the size of a file. Anyone can add additional, customized, progression handlers. The 'progressr' package uses R's condition framework for signaling progress updated. Because of this, progress can be reported from almost anywhere in R, e.g. from classical for and while loops, from map-reduce APIs like the 'lapply()' family of functions, 'purrr', 'plyr', and 'foreach'. It will also work with parallel processing via the 'future' framework, e.g. 'future.apply::future_lapply()', 'furrr::map()', and 'foreach' with 'doFuture'. The package is compatible with Shiny applications.
Authors@R: c( person("Henrik", "Bengtsson", role=c("aut", "cre", "cph"), email = "henrikb@braju.com"))
License: GPL (>= 3)
Imports: digest, utils
Suggests: graphics, tcltk, beepr, pbmcapply, progress, purrr, foreach, plyr, doFuture, future (>= 1.16.0), future.apply, furrr, shiny, commonmark, tools
VignetteBuilder: progressr
URL: https://github.com/HenrikBengtsson/progressr
BugReports: https://github.com/HenrikBengtsson/progressr/issues
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-23 08:14:26 UTC; hb
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>
Repository: CRAN
Date/Publication: 2020-01-23 14:10:02 UTC

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New package nat.nblast with initial version 1.6.5
Package: nat.nblast
Type: Package
Title: NeuroAnatomy Toolbox ('nat') Extension for Assessing Neuron Similarity and Clustering
Version: 1.6.5
Authors@R: c( person("Gregory", "Jefferis", email= "jefferis@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0002-0587-9355")), person("James", "Manton", email="ajd.manton@googlemail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9260-3156")) )
Description: Extends package 'nat' (NeuroAnatomy Toolbox) by providing a collection of NBLAST-related functions for neuronal morphology comparison (Costa et al. (2016) <doi: 10.1016/j.neuron.2016.06.012>).
URL: https://github.com/natverse/nat.nblast, https://natverse.github.io
BugReports: https://github.com/natverse/nat.nblast/issues
Depends: R (>= 2.15.1), rgl, methods, nat (>= 1.5.12)
Imports: nabor, dendroextras, plyr, spam
Suggests: spelling, bigmemory, ff, testthat, knitr, rmarkdown
License: GPL-3
LazyData: yes
VignetteBuilder: knitr
RoxygenNote: 7.0.2
Language: en-GB
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-01-23 13:47:22 UTC; James Manton
Author: Gregory Jefferis [aut] (<https://orcid.org/0000-0002-0587-9355>), James Manton [aut, cre] (<https://orcid.org/0000-0001-9260-3156>)
Maintainer: James Manton <ajd.manton@googlemail.com>
Repository: CRAN
Date/Publication: 2020-01-23 14:10:05 UTC

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New package gofCopula with initial version 0.3-1
Package: gofCopula
Type: Package
Title: Goodness-of-Fit Tests for Copulae
Version: 0.3-1
Date: 2020-01-20
Author: Ostap Okhrin <ostap.okhrin@tu-dresden.de>, Simon Trimborn <simon.trimborn@nus.edu.sg>, Martin Waltz <martin.waltz@tu-dresden.de>
Maintainer: Simon Trimborn <simon.trimborn@nus.edu.sg>
LazyLoad: yes
LazyData: true
Depends: R (>= 1.9.0), copula (>= 0.999-15), foreach, parallel, doSNOW, R.utils
Imports: SparseGrid, numDeriv, VineCopula (>= 2.0.5), methods, stats, MASS, utils, yarrr, progress
Description: Several Goodness-of-Fit (GoF) tests for Copulae are provided. A new hybrid test, Zhang et al. (2016) <doi:10.1016/j.jeconom.2016.02.017> is implemented which supports all of the individual tests in the package, e.g. Genest et al. (2009) <doi:10.1016/j.insmatheco.2007.10.005>. Estimation methods for the margins are provided and all the tests support parameter estimation and predefined values. The parameters are estimated by pseudo maximum likelihood but if it fails the estimation switches automatically to inversion of Kendall's tau. For reproducibility of results, the functions support the definition of seeds. Also all the tests support automatized parallelization of the bootstrapping tasks. The package provides an interface to perform new GoF tests by submitting the test statistic.
License: GPL (>= 3)
NeedsCompilation: yes
Packaged: 2020-01-23 06:15:49 UTC; matsim
Repository: CRAN
Date/Publication: 2020-01-23 13:50:02 UTC

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Wed, 22 Jan 2020

New package soundcorrs with initial version 0.1.0
Package: soundcorrs
Title: Semi-Automatic Analysis of Sound Correspondences
Version: 0.1.0
Authors@R: person("Kamil", "Stachowski", email = "kamil.stachowski@gmail.com", role = c("aut","cre"))
Description: A set of tools that can be used in computer-aided analysis of sound correspondences between languages, plus several helper functions. Analytic functions range from purely qualitative analysis, through statistic methods yielding qualitative results, to an entirely quantitative approach.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-15 13:40:42 UTC; kamil
Author: Kamil Stachowski [aut, cre]
Maintainer: Kamil Stachowski <kamil.stachowski@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-22 15:20:02 UTC

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New package PoissonBinomial with initial version 1.0.0
Package: PoissonBinomial
Type: Package
Title: Exact and Approximate Implementations of the Poisson Binomial Distribution
Version: 1.0.0
Date: 2020-01-15
Authors@R: person("Florian", "Junge", role = c("aut", "cre"), email = "florian.junge@h-da.de")
Maintainer: Florian Junge <florian.junge@h-da.de>
Description: Implementations of multiple exact and approximate methods as described in Hong (2013) <doi:10.1016/j.csda.2012.10.006> and Biscarri et al. (2018) <doi:10.1016/j.csda.2018.01.007> for computing the probability mass, cumulative distribution and quantile functions, as well as generating random numbers for the Poisson binomial distribution.
License: GPL (>= 2)
Encoding: UTF-8
Imports: Rcpp (>= 1.0.3)
LinkingTo: Rcpp, BH
SystemRequirements: fftw3 (>= 3.3)
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown, microbenchmark
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-15 14:43:32 UTC; fjunge
Author: Florian Junge [aut, cre]
Repository: CRAN
Date/Publication: 2020-01-22 14:50:07 UTC

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New package crevents with initial version 0.1.0
Package: crevents
Title: Client for the 'Crossref' Events API
Description: Client for the 'Crossref' Events API <https://www.eventdata.crossref.org/guide/>. The 'Crossref' Events service captures discussion of scholarly works (e.g., peer-reviewed publications) in non-traditional places such as blogs and social media.
Version: 0.1.0
License: MIT + file LICENSE
Authors@R: c( person("Scott", "Chamberlain", role = c("aut", "cre"), email = "myrmecocystus@gmail.com", comment = c(ORCID = "0000-0003-1444-9135")) )
URL: https://docs.ropensci.org/crevents, https://github.com/ropensci/crevents
BugReports: https://github.com/ropensci/crevents/issues
LazyData: true
Encoding: UTF-8
Language: en-US
Imports: crul, jsonlite, tibble
Suggests: testthat, vcr
RoxygenNote: 7.0.2
X-schema.org-applicationCategory: Literature
X-schema.org-keywords: text-ming, literature, scholarly, publications, citations, events, Crossref, tweets
X-schema.org-isPartOf: https://ropensci.org
NeedsCompilation: no
Packaged: 2020-01-15 03:19:02 UTC; sckott
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-22 14:50:03 UTC

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New package climdex.pcic with initial version 1.1-11
Package: climdex.pcic
Version: 1.1-11
Date: 2020-01-21
Title: PCIC Implementation of Climdex Routines
Author: David Bronaugh <bronaugh@uvic.ca> for the Pacific Climate Impacts Consortium
Maintainer: James Hiebert <hiebert@uvic.ca>
Depends: R (>= 2.12.0), PCICt (>= 0.5-4)
Imports: methods, Rcpp (>= 0.11.4)
Suggests: compiler, RUnit
LinkingTo: Rcpp
Description: PCIC's implementation of Climdex routines for computation of extreme climate indices. Further details on the extreme climate indices can be found at <http://etccdi.pacificclimate.org/list_27_indices.shtml> and in the package manual.
License: GPL-3
URL: https://www.r-project.org
LazyData: yes
BugReports: https://github.com/pacificclimate/climdex.pcic/issues/
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2020-01-21 18:53:11 UTC; james
Repository: CRAN
Date/Publication: 2020-01-22 12:30:05 UTC

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New package mosmafs with initial version 0.1.0
Package: mosmafs
Title: Multi-Objective Simultaneous Model and Feature Selection
Description: Performs simultaneous hyperparameter tuning and feature selection through both single-objective and multi-objective optimization as described in Binder, Moosbauer et al. (2019) <arXiv:1912.12912>. Uses the 'ecr'-package as basis but adds mixed integer evolutionary strategies and multi-fidelity functionality as well as operators specific for the problem of feature selection.
Authors@R: c( person("Martin", "Binder", email = "developer.mb706@mb706.com", role = c("aut", "cre")), person("Susanne", "Dandl", email = "dandl.susanne@googlemail.com", role = "aut"), person("Julia", "Moosbauer", email = "ju.moosbauer@googlemail.com", role = "aut"))
URL: https://github.com/compstat-lmu/mosmafs
BugReports: https://github.com/compstat-lmu/mosmafs/issues
License: MIT + file LICENSE
Encoding: UTF-8
ByteCompile: yes
Version: 0.1.0
VignetteBuilder: knitr
Depends: ecr (>= 2.1.0)
Imports: BBmisc, checkmate (>= 1.9.0), ParamHelpers, MASS, smoof, mlrCPO (>= 0.3.4), mlr, parallelMap
Suggests: knitr, ggplot2, magrittr, testthat, rpart, parallel, praznik, mlrMBO, emoa, DiceKriging, rgenoud, randomForest, digest
RoxygenNote: 7.0.2
Collate: 'customnsga2.R' 'datagen.R' 'ecrshims.R' 'evalmosmafs.R' 'filtermat.R' 'objective.R' 'utils.R' 'operators.R' 'plotting.R' 'selectorcpo.R' 'terminators.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2020-01-21 23:54:55 UTC; user
Author: Martin Binder [aut, cre], Susanne Dandl [aut], Julia Moosbauer [aut]
Maintainer: Martin Binder <developer.mb706@mb706.com>
Repository: CRAN
Date/Publication: 2020-01-22 11:20:06 UTC

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New package BrailleR with initial version 0.30.2
Package: BrailleR
Type: Package
Title: Improved Access for Blind Users
Version: 0.30.2
Author: A. Jonathan R. Godfrey [aut, cre], Debra Warren [aut], Donal Fitzpatrick [ctb], Duncan Murdoch [ctb], Greg Snow [ctb], Henrik Bengtsson [ctb], James Curtis [ctb], JooYoung Seo [ctb], Marshall Flax [ctb], Paul Murrell [aut], Timothy Bilton [aut], Tony Hirst [ctb], Tsan-Kuang Lee [ctb], Volker Sorge [aut], Yihui Xie [ctb]
Maintainer: A. Jonathan R. Godfrey <a.j.godfrey@massey.ac.nz>
Authors@R: c(person("A. Jonathan R.", "Godfrey", role=c("aut", "cre"), email="a.j.godfrey@massey.ac.nz"), person("Debra", "Warren", email = "dwar068@aucklanduni.ac.nz", role = "aut"), person("Donal", "Fitzpatrick", email = "donal.fitzpatrick@dcu.ie", role = "ctb"), person("Duncan", "Murdoch", email = "murdoch.duncan@gmail.com", role = "ctb"), person("Greg", "Snow", email = "greg.snow@imail.org", role = "ctb"), person("Henrik", "Bengtsson", email = "henrikb@braju.com", role = "ctb"), person("James", "Curtis", email = "james@curtis.net.nz", role = "ctb"), person("JooYoung", "Seo", email = "jooyoung@psu.edu", role = "ctb"), person("Marshall", "Flax", email = "marshall.flax@gmail.com", role = "ctb"), person("Paul", "Murrell", email = "paul@stat.auckland.ac.nz", role = "aut"), person("Timothy", "Bilton", email = "tbilton@gmail.com", role = "aut"), person("Tony", "Hirst", email = "tony.hirst@open.ac.uk", role = "ctb"), person("Tsan-Kuang", "Lee", email = "developer@tklee.com", role = "ctb"), person("Volker", "Sorge", email = "v.sorge@mathjax.org", role = "aut"), person("Yihui", "Xie", email = "xie@yihui.name", role = "ctb"))
Description: Blind users do not have access to the graphical output from R without printing the content of graphics windows to an embosser of some kind. This is not as immediate as is required for efficient access to statistical output. The functions here are created so that blind people can make even better use of R. This includes the text descriptions of graphs, convenience functions to replace the functionality offered in many GUI front ends, and experimental functionality for optimising graphical content to prepare it for embossing as tactile images.
Repository: CRAN
License: GPL-2
Depends: R (>= 3.4.0)
Imports: devtools, dplyr, extrafont, ggplot2, grid, gridGraphics, gridSVG, hunspell, knitr, magrittr, moments, nortest, reticulate, rmarkdown, roloc, rolocISCCNBS, utils, whisker, XML, xtable
Suggests: installr
SystemRequirements: Python 3 and wxPython 4.0
VignetteBuilder: knitr
URL: https://github.com/ajrgodfrey/BrailleR
BugReports: https://github.com/ajrgodfrey/BrailleR/issues
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2020-01-21 22:14:53 UTC; ajgodfre
Date/Publication: 2020-01-22 11:20:19 UTC

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Tue, 21 Jan 2020

New package ClimProjDiags with initial version 0.1.0
Package: ClimProjDiags
Title: Set of Tools to Compute Various Climate Indices
Version: 0.1.0
Authors@R: c( person("BSC-CNS", role = c("aut", "cph")), person("Nuria", "Perez-Zanon", , "nuria.perez@bsc.es", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8568-3071")), person("Nicolau", "Manubens", , "nicolau.manubens@bsc.es", role = "ctb"), person("Alasdair", "Hunter", , "alasdair.hunter@bsc.es", role = "aut"), person("Louis-Philippe", "Caron", , "louis-philippe.caron@bsc.es", role = "ctb"))
Description: Set of tools to compute metrics and indices for climate analysis. The package provides functions to compute extreme indices, evaluate the agreement between models and combine theses models into an ensemble. Multi-model time series of climate indices can be computed either after averaging the 2-D fields from different models provided they share a common grid or by combining time series computed on the model native grid. Indices can be assigned weights and/or combined to construct new indices.
Depends: R (>= 3.2.0)
Imports: multiApply (>= 2.0.0), PCICt, plyr, stats
License: LGPL-3
URL: https://earth.bsc.es/gitlab/es/ClimProjDiags
BugReports: https://earth.bsc.es/gitlab/es/ClimProjDiags/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 5.0.0
Suggests: knitr, testthat, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-21 12:16:56 UTC; nperez
Author: BSC-CNS [aut, cph], Nuria Perez-Zanon [aut, cre] (<https://orcid.org/0000-0001-8568-3071>), Nicolau Manubens [ctb], Alasdair Hunter [aut], Louis-Philippe Caron [ctb]
Maintainer: Nuria Perez-Zanon <nuria.perez@bsc.es>
Repository: CRAN
Date/Publication: 2020-01-21 14:30:09 UTC

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New package SmartEDA with initial version 0.3.3
Package: SmartEDA
Type: Package
Title: Summarize and Explore the Data
Version: 0.3.3
Authors@R: c(person("Dayanand Ubrangala", role = c("aut", "cre"), email = "daya6489@gmail.com"), person("Kiran", "R", role = c("aut","ctb")), person("Ravi", "Prasad Kondapalli", role = c("aut","ctb")), person("Sayan", "Putatunda", role = c("aut","ctb")))
Maintainer: Dayanand Ubrangala <daya6489@gmail.com>
Depends: R (>= 3.3.0)
Imports: ggplot2(>= 2.2.1),sampling(>= 2.8),scales(>= 0.5.0),rmarkdown(>= 1.9),ISLR(>= 1.2),data.table(>= 1.10.4-3),gridExtra(>= 2.3),GGally(>= 1.4.0)
Description: Exploratory analysis on any input data describing the structure and the relationships present in the data. The package automatically select the variable and does related descriptive statistics. Analyzing information value, weight of evidence, custom tables, summary statistics, graphical techniques will be performed for both numeric and categorical predictors.
License: MIT + file LICENSE
Suggests: psych, Hmisc, smbinning,testthat,knitr,covr
Encoding: UTF-8
LazyData: true
URL: https://daya6489.github.io/SmartEDA/
BugReports: https://github.com/daya6489/SmartEDA/issues
Repository: CRAN
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-20 12:34:35 UTC; dubrangala
Author: Dayanand Ubrangala [aut, cre], Kiran R [aut, ctb], Ravi Prasad Kondapalli [aut, ctb], Sayan Putatunda [aut, ctb]
Date/Publication: 2020-01-21 11:00:02 UTC

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New package EpiILMCT with initial version 1.1.6
Package: EpiILMCT
Title: Continuous Time Distance-Based and Network-Based Individual Level Models for Epidemics
Version: 1.1.6
Date: 2020-01-20
Authors@R: c( person("Waleed", "Almutiry", email = "wkmtierie@qu.edu.sa", role = c("aut", "cre")), person("Rob", "Deardon", role = c("aut", "ths")), person("Vineetha", "Warriyar K. V.", role = "ctb") )
Author: Waleed Almutiry [aut, cre], Rob Deardon [aut, ths], Vineetha Warriyar K. V. [ctb]
Maintainer: Waleed Almutiry <wkmtierie@qu.edu.sa>
Description: Provides tools for simulating from continuous-time individual level models of disease transmission, and carrying out infectious disease data analyses with the same models. The epidemic models considered are distance-based and/or contact network-based models within Susceptible-Infectious-Removed (SIR) or Susceptible-Infectious-Notified-Removed (SINR) compartmental frameworks. An overview of the implemented continuous-time individual level models for epidemics is given by Almutiry and Deardon (2019) <doi:10.1515/ijb-2017-0092>.
Depends: graphics, stats, utils, coda, parallel, R (>= 3.5.0)
Imports: methods, igraph
License: GPL (>= 2)
URL: https://github.com/waleedalmutiry/EpiILMCT/
NeedsCompilation: yes
Packaged: 2020-01-20 20:47:41 UTC; ABO-HATIM
Repository: CRAN
Date/Publication: 2020-01-21 10:30:06 UTC

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New package fitzRoy with initial version 0.3.1
Package: fitzRoy
Title: Easily Scrape and Process AFL Data
Version: 0.3.1
Authors@R: c(person(given = "James", family = "Day", role = c("cre", "aut"), email = "jamesthomasday@gmail.com"), person(given = "Robert", family = "Nguyen", role = "aut", email = "nguyen.n.robert@gmail.com"), person(given = "Matthew", family = "Erbs", role = "ctb", email = "matthew.erbs@merbla.com"), person(given = "Oscar", family = "Lane", role = "aut", email = "lane.oscar@gmail.com"), person(given = "Jason", family = "Zivkovic", role = "ctb", email = "jaseziv83@gmail.com"))
Description: An easy package for scraping and processing Australia Rules Football (AFL) data. 'fitzRoy' provides a range of functions for accessing publicly available data from 'AFL Tables' <https://afltables.com>, 'Footy Wire' <https://www.footywire.com> and 'The Squiggle' <https://squiggle.com.au>. Further functions allow for easy processing, cleaning and transformation of this data into formats that can be used for analysis.
License: GPL-3
URL: https://github.com/jimmyday12/fitzRoy
BugReports: https://github.com/jimmyday12/fitzRoy/issues
Depends: R (>= 3.1)
Imports: dplyr, httr, jsonlite, lubridate, magrittr, purrr, readr, rlang (>= 0.1.2), rvest, stringr (>= 1.3.0), tidyr (>= 1.0.0), tidyselect, xml2, tibble, glue
Suggests: covr, ggplot2, knitr, rmarkdown, testthat, roxygen2, elo, spelling, curl
VignetteBuilder: knitr
ByteCompile: true
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Language: en-US
NeedsCompilation: no
Packaged: 2020-01-21 04:51:56 UTC; jamesday
Author: James Day [cre, aut], Robert Nguyen [aut], Matthew Erbs [ctb], Oscar Lane [aut], Jason Zivkovic [ctb]
Maintainer: James Day <jamesthomasday@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-21 09:20:13 UTC

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Mon, 20 Jan 2020

New package iMRMC with initial version 1.2.1
Package: iMRMC
Type: Package
Title: Multi-Reader, Multi-Case Analysis Methods (ROC, Agreement, and Other Metrics)
Version: 1.2.1
Author: Brandon Gallas
Maintainer: Brandon Gallas <Brandon.Gallas@fda.hhs.gov>
Description: Do Multi-Reader, Multi-Case (MRMC) analyses of data from imaging studies where clinicians (readers) evaluate patient images (cases). What does this mean? ... Many imaging studies are designed so that every reader reads every case in all modalities, a fully-crossed study. In this case, the data is cross-correlated, and we consider the readers and cases to be cross-correlated random effects. An MRMC analysis accounts for the variability and correlations from the readers and cases when estimating variances, confidence intervals, and p-values. The functions in this package can treat arbitrary study designs and studies with missing data, not just fully-crossed study designs. The initial package analyzes the reader-average area under the receiver operating characteristic (ROC) curve with U-statistics according to Gallas, Bandos, Samuelson, and Wagner 2009 <doi:10.1080/03610920802610084>. Additional functions analyze other endpoints with U-statistics (binary performance and score differences) following the work by Gallas, Pennello, and Myers 2007 <doi:10.1364/JOSAA.24.000B70>. Package development and documentation is at <https://github.com/DIDSR/iMRMC/tree/master>.
License: CC0
Encoding: UTF-8
SystemRequirements: Java JDK 1.7 or higher
LazyData: true
Depends: R (>= 2.10)
RoxygenNote: 7.0.2
Imports: stats
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-01-20 15:20:20 UTC; BDG
Repository: CRAN
Date/Publication: 2020-01-20 19:30:07 UTC

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New package deGradInfer with initial version 1.0.1
Package: deGradInfer
Title: Parameter Inference for Systems of Differential Equation
Version: 1.0.1
Authors@R: c(person("Benn", "Macdonald", email = "Benn.Macdonald@glasgow.ac.uk", role = c("aut")), person("Frank", "Dondelinger", email = "fdondelinger.work@gmail.com", role = c("aut", "cre")))
Description: Efficient Bayesian parameter inference for systems of ordinary differential equations. The inference is based on adaptive gradient matching (AGM, Dondelinger et al. 2013 <http://proceedings.mlr.press/v31/dondelinger13a.pdf>, Macdonald 2017 <http://theses.gla.ac.uk/7987/1/2017macdonaldphd.pdf>), which offers orders-of-magnitude improvements in computational efficiency over standard methods that require solving the differential equation system. Features of the package include flexible specification of custom ODE systems as R functions, support for missing variables, Bayesian inference via population MCMC.
Depends: R (>= 3.3.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: deSolve, gdata, gptk, graphics, stats
RoxygenNote: 7.0.2
Suggests: testthat, knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-20 14:00:44 UTC; dondelin
Author: Benn Macdonald [aut], Frank Dondelinger [aut, cre]
Maintainer: Frank Dondelinger <fdondelinger.work@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-20 19:30:25 UTC

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New package bomrang with initial version 0.7.0
Package: bomrang
Type: Package
Title: Australian Government Bureau of Meteorology ('BOM') Data Client
Version: 0.7.0
Authors@R: c(person("Adam H.", "Sparks", role = c("aut", "cre"), email = "adamhsparks@gmail.com", comment = c(ORCID = "0000-0002-0061-8359")), person("Jonathan", "Carroll", , role = "aut", email = "rpkg@jcarroll.com.au", comment = c(ORCID = "0000-0002-1404-5264")), person("James", "Goldie", role = "aut", email = "me@rensa.co", comment = c(ORCID = "0000-0002-5024-6207")), person("Dean", "Marchiori", , role = "aut", email = "deanmarchiori@gmail.com"), person("Paul", "Melloy", role = "aut", email = "paul@melloy.com.au", comment = c(ORCID = "0000-0003-4253-7167")), person("Mark", "Padgham", role = c("aut", "rev"), email = "mark.padgham@email.com", comment = c(ORCID = "0000-0003-2172-5265")), person("Hugh", "Parsonage", role = "aut", email = "hugh.parsonage@gmail.com", comment = c(ORCID = "0000-0003-4055-0835")), person("Keith", "Pembleton", role = "aut", email = "keith.pembleton@usq.edu.au", comment = c(ORCID = "0000-0002-1896-4516")), person("James", "Balamuta", role = "ctb", email = "balamut2@illinois.edu", comment = c(ORCID = "0000-0003-2826-8458")), person("Brooke", "Anderson", role = "rev", email = "brooke.anderson@colostate.edu", comment = c(ORCID = "0000-0002-5012-9035")))
Description: Provides functions to interface with Australian Government Bureau of Meteorology ('BOM') data, fetching data and returning a tidy data frame of precis forecasts, historical and current weather data from stations, agriculture bulletin data, 'BOM' 0900 or 1500 weather bulletins and downloading and importing radar and satellite imagery files. Data (c) Australian Government Bureau of Meteorology Creative Commons (CC) Attribution 3.0 licence or Public Access Licence (PAL) as appropriate. See <http://www.bom.gov.au/other/copyright.shtml> for further details.
URL: https://github.com/ropensci/bomrang, https://docs.ropensci.org/bomrang/
BugReports: https://github.com/ropensci/bomrang/issues
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: curl (>= 2.8.1), crayon, data.table (>= 1.10.4), dplyr (>= 0.7.0), foreign, httr (>= 1.2.1), hoardr, janitor (>= 1.0.0), jsonlite (>= 1.5), lubridate, magrittr (>= 1.5), raster, rgdal, readr (>= 1.1.1), rvest, tidyr (>= 0.6.3), tools, utils, xml2 (>= 1.1.1)
Encoding: UTF-8
LazyData: true
Suggests: ASGS.foyer, covr, testthat, knitr, rmarkdown, ggplot2, ggthemes, grid, gridExtra, maps, mapproj, rappdirs, roxygen2 (>= 6.1.0)
Language: en-AU
RoxygenNote: 7.0.2
NeedsCompilation: no
ByteCompile: TRUE
VignetteBuilder: knitr
X-schema.org-applicationCategory: Tools
X-schema.org-keywords: bom, meteorological-data, weather-forecast, australia, weather, weather-data, meteorology, australia-bureau-of-meteorology
X-schema.org-isPartOf: https://ropensci.org
Packaged: 2020-01-20 04:03:47 UTC; adamsparks
Author: Adam H. Sparks [aut, cre] (<https://orcid.org/0000-0002-0061-8359>), Jonathan Carroll [aut] (<https://orcid.org/0000-0002-1404-5264>), James Goldie [aut] (<https://orcid.org/0000-0002-5024-6207>), Dean Marchiori [aut], Paul Melloy [aut] (<https://orcid.org/0000-0003-4253-7167>), Mark Padgham [aut, rev] (<https://orcid.org/0000-0003-2172-5265>), Hugh Parsonage [aut] (<https://orcid.org/0000-0003-4055-0835>), Keith Pembleton [aut] (<https://orcid.org/0000-0002-1896-4516>), James Balamuta [ctb] (<https://orcid.org/0000-0003-2826-8458>), Brooke Anderson [rev] (<https://orcid.org/0000-0002-5012-9035>)
Maintainer: Adam H. Sparks <adamhsparks@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-20 19:30:29 UTC

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New package vampyr with initial version 1.0.5
Package: vampyr
Type: Package
Title: Factor Analysis Controlling the Effects of Response Bias
Version: 1.0.5
Date: 2020-01-15
Author: David Navarro-Gonzalez, Andreu Vigil-Colet, Pere J. Ferrando, Urbano Lorenzo-Seva, Jorge N. Tendeiro
Maintainer: David Navarro-Gonzalez <david.navarro@urv.cat>
Description: Vampirize the response biases from a dataset! Performs factor analysis controlling the effects of social desirability and acquiescence using the method described in Ferrando, Lorenzo-Seva & Chico (2009) <doi:10.1080/10705510902751374>.
Depends: R (>= 2.10)
Imports: stats, optimbase, psych, EFA.MRFA, GPArotation, PCovR, moments, corpcor, lavaan, fungible
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2020-01-15 08:10:02 UTC; 39928973-F
Repository: CRAN
Date/Publication: 2020-01-20 10:30:02 UTC

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New package abdiv with initial version 0.2.0
Package: abdiv
Title: Alpha and Beta Diversity Measures
Version: 0.2.0
Authors@R: person("Kyle", "Bittinger", email = "kylebittinger@gmail.com", role = c("aut", "cre"))
Description: A collection of measures for measuring ecological diversity. Ecological diversity comes in two flavors: alpha diversity measures the diversity within a single site or sample, and beta diversity measures the diversity across two sites or samples. This package overlaps considerably with other R packages such as 'vegan', 'gUniFrac', 'betapart', and 'fossil'. We also include a wide range of functions that are implemented in software outside the R ecosystem, such as 'scipy', 'Mothur', and 'scikit-bio'. The implementations here are designed to be basic and clear to the reader.
URL: https://github.com/kylebittinger/abdiv
BugReports: https://github.com/kylebittinger/abdiv/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0), vegan
Imports: ape
NeedsCompilation: no
Packaged: 2020-01-15 02:25:11 UTC; bittingerk
Author: Kyle Bittinger [aut, cre]
Maintainer: Kyle Bittinger <kylebittinger@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-20 10:50:02 UTC

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New package vamc with initial version 0.1.1
Package: vamc
Type: Package
Title: A Monte Carlo Valuation Framework for Variable Annuities
Version: 0.1.1
Authors@R: c( person("Hengxin", "Li", email = "h343li@uwaterloo.ca", role = c("aut", "cph")), person("Ben", "Feng", email = "ben.feng@uwaterloo.ca", role = c("aut", "cph")), person("Mingyi", "Jiang", email = "m64jiang@uwaterloo.ca", role = c("aut" , "cph", "cre")), person("GuoJun", "Gan", email = "Guojun.Gan@uconn.edu", role = c("ctb")))
Description: Implementation of a Monte Carlo simulation engine for valuing synthetic portfolios of variable annuities, which reflect realistic features of common annuity contracts in practice. It aims to facilitate the development and dissemination of research related to the efficient valuation of a portfolio of large variable annuities. The main valuation methodology was proposed by Gan (2017) <doi:10.1515/demo-2017-0021>.
Depends: R (>= 3.3.0)
License: GPL-2
LazyData: true
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 7.0.2
Imports: stats (>= 3.3.0), utils (>= 3.3.0), Rdpack (>= 0.4)
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2020-01-19 18:19:53 UTC; Iris
Encoding: UTF-8
Repository: CRAN
Author: Hengxin Li [aut, cph], Ben Feng [aut, cph], Mingyi Jiang [aut, cph, cre], GuoJun Gan [ctb]
Maintainer: Mingyi Jiang <m64jiang@uwaterloo.ca>
Date/Publication: 2020-01-20 09:30:02 UTC

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New package shinySIR with initial version 0.1.0
Package: shinySIR
Type: Package
Title: Interactive Plotting for Mathematical Models of Infectious Disease Spread
Version: 0.1.0
Date: 2020-01-04
Authors@R: c(person("Sinead E.", "Morris", role = c("aut", "cre"), email = "sinead.morris@columbia.edu", comment = c(ORCID = "0000-0001-8626-1698")), person("Ottar N.", "Bjornstad", role = "ctb"))
Maintainer: Sinead E. Morris <sinead.morris@columbia.edu>
Description: Provides interactive plotting for mathematical models of infectious disease spread. Users can choose from a variety of common built-in ordinary differential equation (ODE) models (such as the SIR, SIRS, and SIS models), or create their own. This latter flexibility allows 'shinySIR' to be applied to simple ODEs from any discipline. The package is a useful teaching tool as students can visualize how changing different parameters can impact model dynamics, with minimal knowledge of coding in R. The built-in models are inspired by those featured in Keeling and Rohani (2008) <doi:10.2307/j.ctvcm4gk0> and Bjornstad (2018) <doi:10.1007/978-3-319-97487-3>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: dplyr (>= 0.8.0.1), tidyr (>= 0.8.3), ggplot2 (>= 3.1.1), shiny (>= 1.3.2), deSolve (>= 1.2.1)
Suggests: knitr (>= 1.22), rmarkdown (>= 1.12), testthat (>= 2.2.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-14 20:45:02 UTC; sineadmorris
Author: Sinead E. Morris [aut, cre] (<https://orcid.org/0000-0001-8626-1698>), Ottar N. Bjornstad [ctb]
Repository: CRAN
Date/Publication: 2020-01-20 09:30:05 UTC

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New package provGraphR with initial version 1.0
Package: provGraphR
Title: Creates Adjacency Matrices for Lineage Searches
Version: 1.0
Authors@R: c( person("Orenna", "Brand", email = "o.brand@columbia.edu", role = "aut"), person("Joseph", "Wonsil", email = "jwonsil@carthage.edu", role = "aut"), person("Emery", "Boose", email = "boose@fas.harvard.edu", role = "aut"), person("Barbara", "Lerner", email = "blerner@mtholyoke.edu", role = "cre") )
Copyright: President and Fellows of Harvard College, Trustees of Mount Holyoke College
Description: Creates and manages a provenance graph corresponding to the provenance created by the 'rdtLite' package, which collects provenance from R scripts. 'rdtLite' is available on CRAN. The provenance format is an extension of the W3C PROV JSON format (<https://www.w3.org/Submission/2013/SUBM-prov-json-20130424/>). The extended JSON provenance format is described in <https://github.com/End-to-end-provenance/ExtendedProvJson>.
Depends: R (>= 3.5.0)
Imports: igraph, Matrix, methods, provParseR (>= 0.2)
Suggests: testthat
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-14 19:05:16 UTC; blerner
Author: Orenna Brand [aut], Joseph Wonsil [aut], Emery Boose [aut], Barbara Lerner [cre]
Maintainer: Barbara Lerner <blerner@mtholyoke.edu>
Repository: CRAN
Date/Publication: 2020-01-20 09:30:09 UTC

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New package Disequilibrium with initial version 1.0
Package: Disequilibrium
Type: Package
Title: Disequilibrium Models
Version: 1.0
Author: Nate Latshaw [aut, cre], Michael Guggisberg [aut]
Maintainer: Nate Latshaw <dcms2015@gmail.com>
Description: Estimate, summarize, and perform predictions with the market in disequilibrium model, as found in Gourieroux, C. (2000) <doi:10.1017/CBO9780511805608> and Maddala, G. (1983) <doi:10.1017/CBO9780511810176>. The parameters are estimated with maximum likelihood.
License: GPL-3
Encoding: UTF-8
Imports: optimr, Formula, numDeriv
Suggests: MASS
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-14 18:01:40 UTC; nlatshaw
Repository: CRAN
Date/Publication: 2020-01-20 09:10:02 UTC

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New package clustermole with initial version 1.0.0
Type: Package
Package: clustermole
Title: Unbiased Cell Type Identification of Single-Cell Transcriptomic Data
Version: 1.0.0
Authors@R: person(given = "Igor", family = "Dolgalev", role = c("aut", "cre"), email = "igor.dolgalev@nyumc.org")
Description: A typical computational pipeline to process single-cell RNA sequencing (scRNA-seq) data involves clustering of cells. Assignment of cell type labels to those clusters is often a time-consuming process that involves manual inspection of the cluster marker genes complemented with a detailed literature search. This is especially challenging if you are not familiar with all the captured subpopulations or have unexpected contaminants. 'clustermole' provides a comprehensive meta collection of cell identity markers for thousands of human and mouse cell types sourced from a variety of databases as well as methods to query them.
License: MIT + file LICENSE
URL: https://github.com/igordot/clustermole
BugReports: https://github.com/igordot/clustermole/issues
Depends: R (>= 3.4)
Imports: dplyr, GSVA (>= 1.26.0), magrittr, methods, rlang (>= 0.1.2), tibble, tidyr, utils
Suggests: covr, roxygen2, testthat (>= 2.1.0), knitr, rmarkdown
biocViews:
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-15 00:50:36 UTC; id460
Author: Igor Dolgalev [aut, cre]
Maintainer: Igor Dolgalev <igor.dolgalev@nyumc.org>
Repository: CRAN
Date/Publication: 2020-01-20 10:00:02 UTC

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Sun, 19 Jan 2020

New package gratia with initial version 0.3.0
Package: gratia
Version: 0.3.0
Date: 2020-01-16
Title: Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'
Authors@R: c(person(given = "Gavin L.", family = "Simpson", email = "ucfagls@gmail.com", role = c("aut","cre"), comment = c(ORCID = "0000-0002-9084-8413")), person(given = "Henrik", family = "Singmann", role = "ctb", comment = c(ORCID = "0000-0002-4842-3657")))
Maintainer: Gavin L. Simpson <ucfagls@gmail.com>
Depends: R (>= 3.6.0)
Imports: mgcv, ggplot2, tibble, dplyr, tidyr, rlang, cowplot, grid, mvnfast, purrr, stats, tools, grDevices
Suggests: testthat, vdiffr, MASS, scam, datasets
Description: Graceful 'ggplot'-based graphics and utility functions for working with generalized additive models (GAMs) fitted using the 'mgcv' package. Provides a reimplementation of the plot() method for GAMs that 'mgcv' provides, as well as 'tidyverse' compatible representations of estimated smooths.
License: MIT + file LICENSE
LazyData: true
URL: https://gavinsimpson.github.io/gratia
BugReports: https://github.com/gavinsimpson/gratia/issues
RoxygenNote: 7.0.2
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-01-17 16:09:17.810 UTC; gavin
Author: Gavin L. Simpson [aut, cre] (<https://orcid.org/0000-0002-9084-8413>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>)
Repository: CRAN
Date/Publication: 2020-01-19 20:20:03 UTC

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New package rchallenge with initial version 1.3.2
Package: rchallenge
Title: A Simple Data Science Challenge System
Version: 1.3.2
Authors@R: c(person("Adrien", "Todeschini", email = "adrien.todeschini@gmail.com", role=c("aut", "cre")), person("Robin", "Genuer", email = "robin.genuer@isped.u-bordeaux2.fr", role=c("ctb")))
Description: A simple data science challenge system using R Markdown and 'Dropbox' <https://www.dropbox.com/>. It requires no network configuration, does not depend on external platforms like e.g. 'Kaggle' <https://www.kaggle.com/> and can be easily installed on a personal computer.
URL: https://adrtod.github.io/rchallenge
BugReports: https://github.com/adrtod/rchallenge/issues
Depends: R (>= 3.2.0)
Imports: rmarkdown (>= 0.5.1), knitr (>= 1.6)
SystemRequirements: pandoc (>= 1.12.3) - http://johnmacfarlane.net/pandoc
License: GPL-2
LazyData: true
RoxygenNote: 7.0.2
Encoding: UTF-8
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2020-01-14 11:25:32 UTC; adrien
Author: Adrien Todeschini [aut, cre], Robin Genuer [ctb]
Maintainer: Adrien Todeschini <adrien.todeschini@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-19 18:30:03 UTC

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New package MethComp with initial version 1.30.0
Package: MethComp
Version: 1.30.0
Date: 2020-01-14
Title: Analysis of Agreement in Method Comparison Studies
Authors@R: c(person(given="Bendix", family="Carstensen", email="b@bxc.dk", role=c("aut")), person(given="Lyle", family="Gurrin", email="lgurrin@unimelb.edu.au", role=c("aut")), person(given="Claus Thorn", family="Ekstrøm", email="ekstrom@sund.ku.dk", role=c("aut", "cre")), person(given="Michal", family="Figurski", email="figurski@mail.med.upenn.edu", role=c("aut")))
Depends: R (>= 3.5)
Imports: coda, nlme, rjags
Suggests: lattice, lme4
Description: Methods (standard and advanced) for analysis of agreement between measurement methods. These cover Bland-Altman plots, Deming regression, Lin's Total deviation index, and difference-on-average regression. See Carstensen B. (2010) "Comparing Clinical Measurement Methods: A Practical Guide (Statistics in Practice)" <doi:10.1002/9780470683019> for more information.
License: GPL (>= 2)
Encoding: UTF-8
URL: http://BendixCarstensen.com/MethComp/
BugReports: https://github.com/ekstroem/MethComp/issues
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
NeedsCompilation: no
Repository: CRAN
ByteCompile: true
RoxygenNote: 7.0.2
Packaged: 2020-01-17 20:09:14 UTC; cld189
Author: Bendix Carstensen [aut], Lyle Gurrin [aut], Claus Thorn Ekstrøm [aut, cre], Michal Figurski [aut]
Maintainer: Claus Thorn Ekstrøm <ekstrom@sund.ku.dk>
Date/Publication: 2020-01-19 18:30:10 UTC

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New package disk.frame with initial version 0.3.2
Type: Package
Package: disk.frame
Title: Larger-than-RAM Disk-Based Data Manipulation Framework
Version: 0.3.2
Date: 2020-01-18
Authors@R: c( person("Dai", "ZJ", email = "zhuojia.dai@gmail.com", role = c("aut", "cre")), person("Jacky", "Poon", role = c("ctb")) )
Maintainer: Dai ZJ <zhuojia.dai@gmail.com>
Description: A disk-based data manipulation tool for working with large-than-RAM datasets. Aims to lower the barrier-to-entry for manipulating large datasets by adhering closely to popular and familiar data manipulation paradigms like dplyr verbs and data.table syntax.
License: MIT + file LICENSE
Imports: Rcpp (>= 0.12.13), glue (>= 1.3.1), rlang (>= 0.4.0), furrr (>= 0.1.0), future.apply (>= 1.3.0), fs (>= 1.3.1), jsonlite (>= 1.6), pryr (>= 0.1.4), stringr (>= 1.4.0), fst (>= 0.8.0), globals (>= 0.12.4), future (>= 1.14.0), data.table (>= 1.12.2), crayon (>= 1.3.4), bigreadr (>= 0.2.0), bit64
Depends: R (>= 3.4), dplyr (>= 0.8.3), purrr (>= 0.3.2)
Suggests: benchmarkme, testthat (>= 2.1.0), knitr, rmarkdown, nycflights13, magrittr, shiny, LaF, readr, rstudioapi, biglm, biglmm, speedglm, broom, learnr, ggplot2
LinkingTo: Rcpp
RoxygenNote: 7.0.2
VignetteBuilder: knitr
Encoding: UTF-8
URL: https://diskframe.com
BugReports: https://github.com/xiaodaigh/disk.frame/issues
NeedsCompilation: yes
Packaged: 2020-01-18 11:28:08 UTC; RTX2080
Author: Dai ZJ [aut, cre], Jacky Poon [ctb]
Repository: CRAN
Date/Publication: 2020-01-19 18:20:07 UTC

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New package optpart with initial version 3.0-3
Package: optpart
Version: 3.0-3
Title: Optimal Partitioning of Similarity Relations
Author: David W. Roberts <droberts@montana.edu>
Maintainer: David W. Roberts <droberts@montana.edu>
Depends: cluster, labdsv, MASS, plotrix
Suggests: tree
Description: Contains a set of algorithms for creating partitions and coverings of objects largely based on operations on (dis)similarity relations (or matrices). There are several iterative re-assignment algorithms optimizing different goodness-of-clustering criteria. In addition, there are covering algorithms 'clique' which derives maximal cliques, and 'maxpact' which creates a covering of maximally compact sets. Graphical analyses and conversion routines are also included.
License: GPL (>= 2)
URL: http://ecology.msu.montana.edu/labdsv/R
NeedsCompilation: yes
Packaged: 2020-01-17 13:31:54 UTC; dvrbts
Repository: CRAN
Date/Publication: 2020-01-19 17:10:02 UTC

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New package seagull with initial version 1.0.3
Package: seagull
Type: Package
Title: Lasso, Group Lasso, and Sparse-Group Lasso for Mixed Models
Version: 1.0.3
Date: 2020-01-14
Authors@R: c(person("Jan", "Klosa", role = c("aut", "cre"), email = "klosa@fbn-dummerstorf.de"), person("Noah", "Simon", role = "ths"), person("Dörte", "Wittenburg", role = "ths"))
Maintainer: Jan Klosa <klosa@fbn-dummerstorf.de>
Description: Proximal gradient descent solver for the operators lasso, group lasso, and sparse-group lasso. The implementation involves backtracking line search and warm starts. Input data needs to be clustered/grouped for the (sparse-)group lasso before calling these algorithms.
License: GPL (>= 2)
URL: https://github.com/jklosa/seagull
BugReports: https://github.com/jklosa/seagull/issues
Depends: R (>= 3.5.0)
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.3)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.0.2
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-14 15:34:19 UTC; klosa
Author: Jan Klosa [aut, cre], Noah Simon [ths], Dörte Wittenburg [ths]
Repository: CRAN
Date/Publication: 2020-01-19 16:20:02 UTC

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New package miceRanger with initial version 1.1.0
Package: miceRanger
Title: Multiple Imputation by Chained Equations with Random Forests
Version: 1.1.0
Authors@R: person(given = "Sam", family = "Wilson", role = c("aut","cre"), email = "samwilson303@gmail.com")
Maintainer: Sam Wilson <samwilson303@gmail.com>
Description: Multiple Imputation has been shown to be a flexible method to impute missing values by Van Buuren (2007) <doi:10.1177/0962280206074463>. Expanding on this, random forests have been shown to be an accurate model by Stekhoven and Buhlmann <arXiv:1105.0828> to impute missing values in datasets. They have the added benefits of returning out of bag error and variable importance estimates, as well as being simple to run in parallel.
Encoding: UTF-8
LazyData: true
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: ranger, data.table, stats, FNN, ggplot2, gridExtra, crayon, corrplot, ggpubr, DescTools, foreach
Suggests: knitr, rmarkdown, doParallel
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-14 14:43:41 UTC; SamWilson
Author: Sam Wilson [aut, cre]
Repository: CRAN
Date/Publication: 2020-01-19 16:20:06 UTC

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New package isoboost with initial version 1.0.0
Package: isoboost
Title: Isotonic Boosting Classification Rules
Version: 1.0.0
Date: 2020-01-14
Authors@R: c( person("David", "Conde", email = "dconde@eio.uva.es", role = c("aut", "cre")), person("Miguel A.", "Fernandez", email = "miguelaf@eio.uva.es", role = "aut"), person("Cristina", "Rueda", email = "cristina.rueda@uva.es", role = "aut"), person("Bonifacio", "Salvador", email = "bosal@eio.uva.es", role = "aut"))
Description: In classification problems a monotone relation between some predictors and the classes may be assumed. In this package 'isoboost' we propose new boosting algorithms, based on LogitBoost, that incorporate this isotonicity information, yielding more accurate and easily interpretable rules.
Imports: Iso, isotone, rpart
License: GPL-2 | GPL-3
NeedsCompilation: no
Packaged: 2020-01-14 15:24:09 UTC; davidconde
Author: David Conde [aut, cre], Miguel A. Fernandez [aut], Cristina Rueda [aut], Bonifacio Salvador [aut]
Maintainer: David Conde <dconde@eio.uva.es>
Repository: CRAN
Date/Publication: 2020-01-19 16:30:03 UTC

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New package BAS with initial version 1.5.4
Package: BAS
Version: 1.5.4
Date: 2020-1-8
Title: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling
Authors@R: c(person("Merlise", "Clyde", email="clyde@duke.edu", role=c("aut","cre", "cph"), comment=c("ORCID=0000-0002-3595-1872") ), person("Michael", "Littman", role="ctb"), person("Quanli", "Wang", role="ctb"), person("Joyee", "Ghosh", role="ctb"), person("Yingbo", "Li", role="ctb"), person("Don", "van de Bergh", role="ctb"))
Depends: R (>= 3.0)
Imports: stats, graphics, utils, grDevices
Suggests: MASS, knitr, ggplot2, GGally, rmarkdown, roxygen2, dplyr, glmbb, pkgdown, testthat, covr
Description: Package for Bayesian Variable Selection and Model Averaging in linear models and generalized linear models using stochastic or deterministic sampling without replacement from posterior distributions. Prior distributions on coefficients are from Zellner's g-prior or mixtures of g-priors corresponding to the Zellner-Siow Cauchy Priors or the mixture of g-priors from Liang et al (2008) <DOI:10.1198/016214507000001337> for linear models or mixtures of g-priors from Li and Clyde (2019) <DOI:10.1080/01621459.2018.1469992> in generalized linear models. Other model selection criteria include AIC, BIC and Empirical Bayes estimates of g. Sampling probabilities may be updated based on the sampled models using Sampling w/out Replacement or an efficient MCMC algorithm which samples models using the BAS tree structure as an efficient hash table. Uniform priors over all models or beta-binomial prior distributions on model size are allowed, and for large p truncated priors on the model space may be used to enforce sampling models that are full rank. The user may force variables to always be included in addition to imposing constraints that higher order interactions are included only if their parents are included in the model. Details behind the sampling algorithm are provided in Clyde, Ghosh and Littman (2010) <DOI:10.1198/jcgs.2010.09049>. This material is based upon work supported by the National Science Foundation under Grant DMS-1106891. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
License: GPL (>= 3)
URL: https://www.r-project.org, https://github.com/merliseclyde/BAS
BugReports: https://github.com/merliseclyde/BAS/issues
Repository: CRAN
NeedsCompilation: yes
ByteCompile: yes
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.0.2
Packaged: 2020-01-15 14:03:07 UTC; mclyde
Author: Merlise Clyde [aut, cre, cph] (ORCID=0000-0002-3595-1872), Michael Littman [ctb], Quanli Wang [ctb], Joyee Ghosh [ctb], Yingbo Li [ctb], Don van de Bergh [ctb]
Maintainer: Merlise Clyde <clyde@duke.edu>
Date/Publication: 2020-01-19 17:00:05 UTC

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New package statgenGWAS with initial version 1.0.1
Package: statgenGWAS
Type: Package
Title: Genome Wide Association Studies
Version: 1.0.1
Date: 2020-01-14
Authors@R: c(person(given = "Bart-Jan", family = "van Rossum", email = "bart-jan.vanrossum@wur.nl", role = c("aut", "cre")), person(given = "Willem", family = "Kruijer", role = "aut", comment = c(ORCID = "0000-0001-7179-1733")), person(given = "Fred", family = "van Eeuwijk", role = "ctb", comment = c(ORCID = "0000-0003-3672-2921")), person(given = "Martin", family = "Boer", role = "ctb"), person(given = "Marcos", family = "Malosetti", role = "ctb", comment = c(ORCID = "0000-0002-8150-1397")), person(given = "Daniela", family = "Bustos-Korts", role = "ctb", comment = c(ORCID = "0000-0003-3827-6726")), person(given = "Emilie", family = "Millet", role = "ctb", comment = c(ORCID = "0000-0002-2913-4892")), person(given = "Joao", family = "Paulo", role = "ctb", comment = c(ORCID = "0000-0002-4180-0763")), person(given = "Maikel", family = "Verouden", role = "ctb", comment = c(ORCID = "0000-0002-4893-3323")), person(given = "Ron", family = "Wehrens", role = "ctb", comment = c(ORCID = "0000-0002-8798-5599")), person(given = "Choazhi", family = "Zheng", role = "ctb", comment = c(ORCID = "0000-0001-6030-3933")) )
Description: Fast single trait Genome Wide Association Studies (GWAS). One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Depends: R (>= 3.5)
Imports: data.table, ggplot2 (>= 3.0.0), sommer (>= 3.7.3), Rcpp
Suggests: knitr, rmarkdown, officer, rvg, tinytest
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2020-01-14 10:53:44 UTC; rossu027
Author: Bart-Jan van Rossum [aut, cre], Willem Kruijer [aut] (<https://orcid.org/0000-0001-7179-1733>), Fred van Eeuwijk [ctb] (<https://orcid.org/0000-0003-3672-2921>), Martin Boer [ctb], Marcos Malosetti [ctb] (<https://orcid.org/0000-0002-8150-1397>), Daniela Bustos-Korts [ctb] (<https://orcid.org/0000-0003-3827-6726>), Emilie Millet [ctb] (<https://orcid.org/0000-0002-2913-4892>), Joao Paulo [ctb] (<https://orcid.org/0000-0002-4180-0763>), Maikel Verouden [ctb] (<https://orcid.org/0000-0002-4893-3323>), Ron Wehrens [ctb] (<https://orcid.org/0000-0002-8798-5599>), Choazhi Zheng [ctb] (<https://orcid.org/0000-0001-6030-3933>)
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>
Repository: CRAN
Date/Publication: 2020-01-19 15:30:02 UTC

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New package opentripplanner with initial version 0.2.0.3
Package: opentripplanner
Title: Setup and connect to 'OpenTripPlanner'
Version: 0.2.0.3
Authors@R: c( person("Malcolm", "Morgan", email = "m.morgan1@leeds.ac.uk", role = c("aut","cre"), comment = c(ORCID = "0000-0002-9488-9183")), person("Marcus", "Young", email = "M.A.Young@soton.ac.uk", role = "aut", comment = c(ORCID = "0000-0003-4627-1116")), person("Robin", "Lovelace", email = "rob00x@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-5679-6536")), person("Layik", "Hama", email = "layik.hama@gmail.com", role = "ctb", comment = c(ORCID = "0000-0003-1912-4890")) )
Maintainer: Malcolm Morgan <m.morgan1@leeds.ac.uk>
Description: Setup and connect to 'OpenTripPlanner' (OTP) <http://www.opentripplanner.org/>. OTP is an open source platform for multi-modal and multi-agency journey planning written in 'Java'. The package allows you to manage a local version or connect to remote OTP server e.g. <https://api.digitransit.fi:443/routing/v1/routers/hsl>. This package has been peer-reviewed by rOpenSci (v. 0.2.0.0).
Language: EN-GB
License: GPL-3
URL: https://github.com/ropensci/opentripplanner, https://docs.ropensci.org/opentripplanner/
BugReports: https://github.com/ropensci/opentripplanner/issues
Encoding: UTF-8
LazyData: true
Imports: checkmate, dplyr, geodist, googlePolylines, httr, jsonlite, pbapply, sf
RoxygenNote: 7.0.2
Suggests: covr, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-06 22:49:38 UTC; malcolm
Author: Malcolm Morgan [aut, cre] (<https://orcid.org/0000-0002-9488-9183>), Marcus Young [aut] (<https://orcid.org/0000-0003-4627-1116>), Robin Lovelace [aut] (<https://orcid.org/0000-0001-5679-6536>), Layik Hama [ctb] (<https://orcid.org/0000-0003-1912-4890>)
Repository: CRAN
Date/Publication: 2020-01-19 15:20:02 UTC

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New package NGSSEML with initial version 1.0
Package: NGSSEML
Type: Package
Title: Non-Gaussian State-Space with Exact Marginal Likelihood
Version: 1.0
Date: 2020-01-14
Author: Thiago Rezende dos Santos <thiagords@est.ufmg.br>, Dani Gamerman <dani@im.ufrj.br>, Glaura da Conceicao Franco <glaura@est.ufmg.br>
Maintainer: T. R. dos Santos <thiagords@est.ufmg.br>
Description: Due to a large quantity of non-Gaussian time series and reliability data, the R-package non-Gaussian state-space with exact marginal likelihood is useful for modeling and forecasting non-Gaussian time series and reliability data via non-Gaussian state-space models with the exact marginal likelihood easily, see Gamerman, Santos and Franco (2013) <doi:10.1111/jtsa.12039> and Santos, Gamerman and Franco (2017) <doi:10.1109/TR.2017.2670142>. The package gives codes for formulating and specifying the non-Gaussian state-space models in the R language. Inferences for the parameters of the model can be made under the classical and Bayesian. Furthermore, prediction, filtering, and smoothing procedures can be used to perform inferences for the latent parameters. Applications include, e.g., count, volatility, piecewise exponential, and software reliability data.
License: GPL (>= 2)
URL: https://github.com/hadht/NGSSEML-R-Package
Imports: mvtnorm, fields, compiler, dlm, car, interp
Depends: R (>= 1.9.0), R (>= 3.5.0), R (>= 3.5.0), R (>= 3.5.0), R (>= 3.5.0), R (>= 3.5.0), R (>= 3.5.0)
Collate: 'FilteringF.r' 'gridfunction.r' 'GridP.r' 'LikeF.r' 'LikeF2.r' 'ngssm.bayes.r' 'ngssm.mle.r' 'NumFail.r' 'PlotF.r' 'Prediction.r' 'PriorF.r' 'ProdXtChi.r' 'SmoothingF.r' 'TTime.r'
NeedsCompilation: no
Packaged: 2020-01-14 12:46:43 UTC; Windows 8
Repository: CRAN
Date/Publication: 2020-01-19 15:40:03 UTC

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New package LassoNet with initial version 0.8.3
Package: LassoNet
Type: Package
Title: 3CoSE Algorithm
Version: 0.8.3
Date: 2019-12-17
Author: Jonas Striaukas [aut, trl, cre] and Matthias Weber [aut]
Maintainer: Jonas Striaukas <jonas.striaukas@gmail.com>
Description: Contains functions to estimate a penalized regression model using 3CoSE algorithm, see Weber, Striaukas, Schumacher Binder (2018) <doi:10.2139/ssrn.3211163>.
License: GPL (>= 2)
Imports: Rcpp (>= 0.11.5)
Suggests: snowfall
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-01-14 12:37:39 UTC; striaukas
Repository: CRAN
Date/Publication: 2020-01-19 15:30:08 UTC

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New package centrifugeR with initial version 0.1.3
Package: centrifugeR
Type: Package
Title: Balancing Centrifuge Rotors
Version: 0.1.3
Authors@R: person("Duy Nghia", "Pham", email = "nghiapham@yandex.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1349-1710"))
Description: Find the numbers of tubes that can be loaded in centrifuge rotors and give the instructions on how to balance these tubes in cases of equal or unequal masses. The methods of the package are constructed based on Sivek (2010) <doi:10.1515/integ.2010.031> and Peil and Hauryliuk (2010) <arXiv:1004.3671>.
Depends: R (>= 3.6.0)
Imports: pracma (>= 2.2.9), grDevices, graphics, utils
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-14 12:44:02 UTC; Nghia Pham
Author: Duy Nghia Pham [aut, cre] (<https://orcid.org/0000-0003-1349-1710>)
Maintainer: Duy Nghia Pham <nghiapham@yandex.com>
Repository: CRAN
Date/Publication: 2020-01-19 15:30:05 UTC

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Sat, 18 Jan 2020

New package Taba with initial version 0.1.0
Package: Taba
Type: Package
Title: Taba Linear and Taba Rank Correlations
Version: 0.1.0
Imports: robustbase, stats
Authors@R: c( person("Mohammad", "Tabatabai", email = "mtabatabai@mmc.edu", role = c("aut")), person("Derek", "Wilus", email = "dwilus@mmc.edu", role = c("aut", "cre")) )
Description: Calculates the robust Taba linear and Taba rank (monotonic) correlations. Test statistics as well as one sided or two sided p-values are provided for Taba and Taba rank correlations. Multiple correlations and p-values can be calculated simultaneously across multiple variables. In addition, users will have the option to use the partial, semipartial, and generalized partial correlations; where the partial and semipartial correlations use linear, logistic, or Poisson regression to modify the specified variable.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-01-13 21:40:58 UTC; dwilus
Author: Mohammad Tabatabai [aut], Derek Wilus [aut, cre]
Maintainer: Derek Wilus <dwilus@mmc.edu>
Repository: CRAN
Date/Publication: 2020-01-18 11:30:05 UTC

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New package hildareadR with initial version 0.1.0
Package: hildareadR
Type: Package
Title: Extract Variables from HILDA
Version: 0.1.0
Authors@R: c( person("Sebastian", "Kalucza", email = "sebastian.kalucza@gmail.com", role = c("aut", "cre")), person("Sara", "Kalucza", email = "sara.kalucza@gmail.com", role = c("aut")))
Imports: haven(>= 2.1.1), dplyr(>= 0.8.3)
Description: Makes it easy to extract and combine variables from the HILDA (Household, Income and Labour Dynamics in Australia) survey maintained by the Melbourne Institute <https://melbourneinstitute.unimelb.edu.au/hilda>.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-13 21:51:53 UTC; Conny
Author: Sebastian Kalucza [aut, cre], Sara Kalucza [aut]
Maintainer: Sebastian Kalucza <sebastian.kalucza@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-18 11:30:02 UTC

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New package dscore with initial version 1.0.0
Package: dscore
Type: Package
Title: D-Score for Child Development
Version: 1.0.0
Authors@R: c(person("Stef", "van Buuren", email = "stef.vanbuuren@tno.nl", role = c("cre", "aut")), person("Iris", "Eekhout", email = "iris.eekhout@tno.nl", role = "aut"), person("Arjan", "Huizing", email = "arjan.huizing@tno.nl", role = "aut"))
Description: The D-score is a quantitative measure of child development. The D-score follows the Rasch model. See Jacobusse, van Buuren and Verkerk (2006) <doi:10.1002/sim.2351>. The user can convert milestone scores from 19 assessment instruments into the D-score and the DAZ (D-score adjusted for age). Several tools assist in mapping milestone names into the 9-position Global Scale of Early Development (GSED) convention. Supports calculation of the D-score using 'dutch' <doi:10.1177/0962280212473300>, 'gcdg' <doi:10.1136/bmjgh-2019-001724> and 'gsed' conversion keys. The user can calculate DAZ using 'dutch' and 'gcdg' age-conditional references.
Depends: R (>= 3.5)
Imports: dplyr (>= 0.8.2), Rcpp, stats, stringr, tidyr (>= 1.0.0)
LinkingTo: Rcpp, RcppArmadillo
Suggests: ggplot2, kableExtra, knitr, lme4, rmarkdown, sirt, testthat
Encoding: UTF-8
License: GPL-3
LazyData: TRUE
VignetteBuilder: knitr
RoxygenNote: 7.0.2
NeedsCompilation: yes
URL: https://github.com/stefvanbuuren/dscore, https://stefvanbuuren.name/dscore/, https://stefvanbuuren.name/dbook1/
BugReports: https://github.com/stefvanbuuren/dscore/issues
Copyright: Stef van Buuren, Iris Eekhout, Arjan Huizing
Packaged: 2020-01-13 22:07:08 UTC; buurensv
Author: Stef van Buuren [cre, aut], Iris Eekhout [aut], Arjan Huizing [aut]
Maintainer: Stef van Buuren <stef.vanbuuren@tno.nl>
Repository: CRAN
Date/Publication: 2020-01-18 12:00:02 UTC

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New package CovCombR with initial version 1.0
Package: CovCombR
Type: Package
Title: Combine Partial Covariance / Relationship Matrices
Version: 1.0
Date: 2020-01-08
Author: Deniz Akdemir, Mohamed Somo, Julio Isidro Sanchez
Maintainer: Deniz Akdemir <deniz.akdemir.work@gmail.com>
Description: Combine partial covariance matrices using a Wishart-EM algorithm. Methods are described in the November 2019 article by Akdemir et al. <https://www.biorxiv.org/content/10.1101/857425v1>. It can be used to combine partially overlapping covariance matrices from independent trials, partially overlapping multi-view relationship data from genomic experiments, partially overlapping Gaussian graphs described by their covariance structures. High dimensional covariance estimation, multi-view data integration. high dimensional covariance graph estimation.
License: GPL
Imports: Matrix, nlme, CholWishart
Suggests: knitr, plyr, spcov, qgraph, igraph
VignetteBuilder: knitr
NeedsCompilation: yes
Depends: R (>= 3.5.0)
Packaged: 2020-01-13 21:57:38 UTC; denizakdemir
Repository: CRAN
Date/Publication: 2020-01-18 11:30:08 UTC

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Thu, 16 Jan 2020

New package SplitReg with initial version 1.0.1
Package: SplitReg
Type: Package
Title: Split Regularized Regression
Version: 1.0.1
Date: 2020-01-12
Author: Anthony Christidis <anthony.christidis@stat.ubc.ca>, Ezequiel Smucler <ezequiels.90@gmail.com>, Ruben Zamar <ruben@stat.ubc.ca>
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>
Description: Functions for computing split regularized estimators defined in Christidis, Lakshmanan, Smucler and Zamar (2019) <arXiv:1712.03561>. The approach fits linear regression models that split the set of covariates into groups. The optimal split of the variables into groups and the regularized estimation of the regression coefficients are performed by minimizing an objective function that encourages sparsity within each group and diversity among them. The estimated coefficients are then pooled together to form the final fit.
License: GPL (>= 2)
Biarch: true
Imports: Rcpp (>= 0.12.12)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, glmnet, MASS
NeedsCompilation: yes
RoxygenNote: 7.0.2
Packaged: 2020-01-14 11:25:27 UTC; antho
Repository: CRAN
Date/Publication: 2020-01-16 23:50:07 UTC

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New package cobs with initial version 1.3-3
Package: cobs
Version: 1.3-3
Date: 2017-03-29
Title: Constrained B-Splines (Sparse Matrix Based)
Description: Qualitatively Constrained (Regression) Smoothing Splines via Linear Programming and Sparse Matrices.
Author: Pin T. Ng <Pin.Ng@nau.edu> and Martin Maechler
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>
Depends: R (>= 2.15.1)
Imports: SparseM (>= 1.6), quantreg (>= 4.65), grDevices, graphics, splines, stats, methods
LazyData: yes
BuildResaveData: no
URL: http://curves-etc.r-forge.r-project.org/ http://r-forge.r-project.org/R/?group_id=846
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2017-03-30 14:12:28 UTC; maechler
Repository: CRAN
Date/Publication: 2017-03-31 17:23:46 UTC
X-CRAN-Comment: Archived on 2020-01-16 as check issues were not corrected in time. 'Additional issues'

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New package ChillModels with initial version 1.0.2
Package: ChillModels
Title: Processing Chill and Heat Models for Temperate Fruit Trees
Version: 1.0.2
Authors@R: c(person("Rafael Henrique", "Pertille", email = "henriquepertille@gmail.com", role = c("aut","cre"), comment = c(ORCID = "0000-0002-4888-2001")), person("Marcos Robson", "Sachet", email = "marcos.sachet@gmail.com", role = c("aut","ctb"), comment = c(ORCID = "0000-0002-0395-2475")), person("Idemir", "Citadin", email = "idemir@utfpr.edu.br", role = c("aut","ctb"), comment = c(ORCID = "0000-0001-9416-2761")), person("Marieli Teresinha", "Guerrezi", email = "marieliguerrezi@hotmail.com", role = c("aut","ctb"), comment = c(ORCID = "0000-0003-3314-4046")))
Description: Calculates the chilling and heat accumulation for studies of the temperate fruit trees. The models in this package are: Utah (Richardson et al., 1974, ISSN:0018-5345), Positive Chill Units - PCU (Linsley-Noaks et al., 1995, ISSN:1017-0316), GDH-A - Growing Degree Hours by Anderson et al.(1986, ISSN:0567-7572), GDH-R - Growing Degree Hours by Richardson et al.(1975, ISSN:0018-5345), North Carolina (Shaltout e Unrath, 1983, ISSN:0003-1062), Landsberg Model (Landsberg, 1974, ISSN:0305-7364), Q10 Model (Bidabe, 1967, ISSN:0031-9368), Jones Model (Jones et al., 2013 <DOI:10.1111/j.1438-8677.2012.00590.x>), Low-Chill Model (Gilreath and Buchanan, 1981, ISSN:0003-1062), Model for Cherry "Sweetheart" (Guak and Nielsen, 2013 <DOI:10.1007/s13580-013-0140-9>), Model for apple "Gala" (Guak and Nielsen, 2013 <DOI:10.1007/s13580-013-0140-9>), Taiwan Model (Lu et al., 2012 <DOI:10.17660/ActaHortic.2012.962.35>), Dynamic Model (Fishman et al., 1987, ISSN:0022-5193) adapted from the function Dynamic_Model() of the 'chillR' package (Luedeling, 2018), Unified Model (Chuine et al., 2016 <DOI:10.1111/gcb.13383>) and Heat Restriction model.
Depends: R (>= 3.6.0)
License: GPL-3
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 6.1.1
Suggests: chillR, dplyr, lubridate, ggplot2
NeedsCompilation: no
Packaged: 2020-01-16 13:57:18 UTC; Rafael
Author: Rafael Henrique Pertille [aut, cre] (<https://orcid.org/0000-0002-4888-2001>), Marcos Robson Sachet [aut, ctb] (<https://orcid.org/0000-0002-0395-2475>), Idemir Citadin [aut, ctb] (<https://orcid.org/0000-0001-9416-2761>), Marieli Teresinha Guerrezi [aut, ctb] (<https://orcid.org/0000-0003-3314-4046>)
Maintainer: Rafael Henrique Pertille <henriquepertille@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-16 16:50:06 UTC

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New package fracdiff with initial version 1.5-0
Package: fracdiff
Version: 1.5-0
VersionNote: Released 1.4-2 on 2012-12-01 on CRAN
Date: 2019-12-09
Title: Fractionally Differenced ARIMA aka ARFIMA(P,d,q) Models
Authors@R: c(person("Martin","Maechler", role=c("aut","cre"), email="maechler@stat.math.ethz.ch", comment = c(ORCID = "0000-0002-8685-9910")) , person("Chris", "Fraley", role=c("ctb","cph"), comment = "S original; Fortran code") , person("Friedrich", "Leisch", role = "ctb", comment = c("R port", ORCID = "0000-0001-7278-1983")) , person("Valderio", "Reisen", role="ctb", comment = "fdGPH() & fdSperio()") , person("Artur", "Lemonte", role="ctb", comment = "fdGPH() & fdSperio()") , person("Rob", "Hyndman", email="Rob.Hyndman@monash.edu", role="ctb", comment = c("residuals() & fitted()", ORCID = "0000-0002-2140-5352")) )
Description: Maximum likelihood estimation of the parameters of a fractionally differenced ARIMA(p,d,q) model (Haslett and Raftery, Appl.Statistics, 1989); including inference and basic methods. Some alternative algorithms to estimate "H".
Imports: stats
Suggests: longmemo, forecast, urca
License: GPL (>= 2)
URL: https://github.com/mmaechler/fracdiff
BugReports: https://github.com/mmaechler/fracdiff/issues
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-12-09 10:23:55 UTC; maechler
Author: Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>), Chris Fraley [ctb, cph] (S original; Fortran code), Friedrich Leisch [ctb] (R port, <https://orcid.org/0000-0001-7278-1983>), Valderio Reisen [ctb] (fdGPH() & fdSperio()), Artur Lemonte [ctb] (fdGPH() & fdSperio()), Rob Hyndman [ctb] (residuals() & fitted(), <https://orcid.org/0000-0002-2140-5352>)
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>
Repository: CRAN
Date/Publication: 2019-12-09 15:00:02 UTC
X-CRAN-Comment: Archived on 2020-01-16 as check issues were not corrected in time. 'Additional issues'

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New package portalr with initial version 0.3.1
Package: portalr
Title: Create Useful Summaries of the Portal Data
Version: 0.3.1
Authors@R: c(person(c("Glenda", "M."), "Yenni", role = c("aut", "cre"), email = "glenda@weecology.org", comment = c(ORCID = "0000-0001-6969-1848")), person("Hao", "Ye", role = c("aut"), comment = c(ORCID = "0000-0002-8630-1458")), person(c("Erica", "M."), "Christensen", role = c("aut"), comment = c(ORCID = "0000-0002-5635-2502")), person(c("Juniper", "L."), "Simonis", role = c("aut"), comment = c(ORCID = "0000-0001-9798-0460")), person(c("Ellen", "K."), "Bledsoe", role = c("aut"), comment = c(ORCID = "0000-0002-3629-7235")), person(c("Renata", "M."), "Diaz", role = c("aut"), comment = c(ORCID = "0000-0003-0803-4734")), person(c("Shawn", "D."), "Taylor", role = c("aut"), comment = c(ORCID = "0000-0002-6178-6903")), person(c("Ethan", "P,"), "White", role = c("aut"), comment = c(ORCID = "0000-0001-6728-7745")), person(c("S.K.", "Morgan"), "Ernest", role = c("aut"), comment = c(ORCID = "0000-0002-6026-8530")))
Description: Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Project. Portal is a long-term (and ongoing) experimental monitoring site in the Chihuahua desert. The raw data files can be found at <https://github.com/weecology/portaldata>.
License: MIT + file LICENSE
URL: https://weecology.github.io/portalr/, https://github.com/weecology/portalr
BugReports: https://github.com/weecology/portalr/issues
LazyData: true
Depends: R (>= 3.2.3)
Imports: dplyr, tidyr, lubridate, magrittr, httr, rlang, forecast, lunar, tibble, usethis (>= 1.5.0), crayon, clisymbols, gh
Suggests: httptest, cowplot, knitr, rmarkdown, pkgdown, covr, ggplot2, testthat
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-15 22:46:04 UTC; GlendaYenni
Author: Glenda M. Yenni [aut, cre] (<https://orcid.org/0000-0001-6969-1848>), Hao Ye [aut] (<https://orcid.org/0000-0002-8630-1458>), Erica M. Christensen [aut] (<https://orcid.org/0000-0002-5635-2502>), Juniper L. Simonis [aut] (<https://orcid.org/0000-0001-9798-0460>), Ellen K. Bledsoe [aut] (<https://orcid.org/0000-0002-3629-7235>), Renata M. Diaz [aut] (<https://orcid.org/0000-0003-0803-4734>), Shawn D. Taylor [aut] (<https://orcid.org/0000-0002-6178-6903>), Ethan P, White [aut] (<https://orcid.org/0000-0001-6728-7745>), S.K. Morgan Ernest [aut] (<https://orcid.org/0000-0002-6026-8530>)
Maintainer: Glenda M. Yenni <glenda@weecology.org>
Repository: CRAN
Date/Publication: 2020-01-16 15:00:02 UTC

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New package muHVT with initial version 1.0.0
Package: muHVT
Type: Package
Date: 2020-01-09
Title: Constructing Hierarchical Voronoi Tessellations and Overlay Heatmap for Data Analysis
Version: 1.0.0
Authors@R: c( person("Sangeet", "Das", email = "dassangeet768@gmail.com", role = "aut"), person("Zubin", "Dowlaty", email = "zubin.dowlaty@mu-sigma.com", role = "aut"), person("Avinash", "Joshi", email = "avinash.joshi@mu-sigma.com", role = "aut"), person("Meet", "Dave", email = "meetdave06@gmail.com", role = "aut"), person("Shubhra", "Prakash", email = "Shubhra.Prakash@mu-sigma.com", role = c("ctb")), person("Mu Sigma, Inc.", email = "ird.experiencelab@mu-sigma.com", role = c("cre")))
Description: Constructing hierarchical Voronoi tessellations for a given data set and overlay heatmap for variables at various levels of the tessellations for in-depth data analysis. See <https://en.wikipedia.org/wiki/Voronoi_diagram> for more information. Credits to Mu Sigma for their continuous support throughout the development of the package.
License: Apache License 2.0
Encoding: UTF-8
Imports: MASS, deldir, grDevices, splancs, sp, conf.design, Hmisc, dplyr, purrr, gtools, magrittr, plyr, polyclip, rgeos, ggplot2
Depends: R (>= 3.5.0)
BugReports: https://github.com/Mu-Sigma/muHVT/issues
URL: https://github.com/Mu-Sigma/muHVT
LazyData: true
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown, testthat,geozoo,plotly,kableExtra
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-15 20:46:57 UTC; test
Author: Sangeet Das [aut], Zubin Dowlaty [aut], Avinash Joshi [aut], Meet Dave [aut], Shubhra Prakash [ctb], Mu Sigma, Inc. [cre]
Maintainer: "Mu Sigma, Inc." <ird.experiencelab@mu-sigma.com>
Repository: CRAN
Date/Publication: 2020-01-16 13:30:03 UTC

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New package policytree with initial version 0.9.0
Package: policytree
Title: Policy Learning via Doubly Robust Empirical Welfare Maximization over Trees
Version: 0.9.0
Authors@R: c( person("Zhengyuan", "Zhou", role = "aut"), person("Susan", "Athey", role = "aut"), person("Stefan", "Wager", role = "aut"), person("Ayush", "Kanodia", role = "aut"), person("Erik", "Sverdrup", role = "cre", email = "erikcs@stanford.edu") )
Description: Multi-action treatment effect estimation and policy learning as in Zhou, Athey and Wager (2018) <arXiv:1810.04778>.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 2.1.0), DiagrammeR
RoxygenNote: 7.0.1
LinkingTo: Rcpp, BH
Imports: Rcpp, grf (>= 1.0.0)
URL: https://github.com/grf-labs/policytree
NeedsCompilation: yes
Packaged: 2020-01-13 17:26:43 UTC; erik
Author: Zhengyuan Zhou [aut], Susan Athey [aut], Stefan Wager [aut], Ayush Kanodia [aut], Erik Sverdrup [cre]
Maintainer: Erik Sverdrup <erikcs@stanford.edu>
Repository: CRAN
Date/Publication: 2020-01-16 11:40:02 UTC

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New package packageDiff with initial version 0.1
Package: packageDiff
Title: Compare R Package Differences
Version: 0.1
Date: 2019-12-31
Authors@R: person("Cole", "Beck", role = c("aut","cre"), email = "cole.beck@vumc.org", comment = c(ORCID = "0000-0002-6849-6255"))
Description: It provides utility functions for investigating changes within R packages. The pkgInfo() function extracts package information such as exported and non-exported functions as well as their arguments. The pkgDiff() function compares this information for two versions of a package and creates a diff file viewable in a browser.
Imports: diffr, htmlwidgets
License: GPL (>= 2)
Depends: R (>= 2.10)
URL: https://github.com/couthcommander/packageDiff
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-13 16:19:45 UTC; beckca
Author: Cole Beck [aut, cre] (<https://orcid.org/0000-0002-6849-6255>)
Maintainer: Cole Beck <cole.beck@vumc.org>
Repository: CRAN
Date/Publication: 2020-01-16 11:30:02 UTC

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New package matchmaker with initial version 0.1.0
Package: matchmaker
Title: Flexible Dictionary-Based Cleaning
Version: 0.1.0
Authors@R: c( person(given = "Zhian N.", family = "Kamvar", role = c("aut", "cre"), email = "zkamvar@gmail.com", comment = c(ORCID = "0000-0003-1458-7108")), person(given = "Thibaut", family = "Jombart", email = "thibautjombart@gmail.com", role = c("ctb")), person(given = "Patrick", family = "Barks", email = "patrick.barks@epicentre.msf.org", role = c("ctb")))
Description: Provides flexible dictionary-based cleaning that allows users to specify implicit and explicit missing data, regular expressions for both data and columns, and global matches, while respecting ordering of factors. This package is part of the 'RECON' (<https://www.repidemicsconsortium.org/>) toolkit for outbreak analysis.
URL: https://www.repidemicsconsortium.org/matchmaker, https://github.com/reconhub/matchmaker
License: GPL-3
Suggests: testthat (>= 2.1.0), covr, knitr, rmarkdown
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Imports: rlang, forcats, cli
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-13 14:53:01 UTC; zkamvar
Author: Zhian N. Kamvar [aut, cre] (<https://orcid.org/0000-0003-1458-7108>), Thibaut Jombart [ctb], Patrick Barks [ctb]
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-16 11:10:02 UTC

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New package bacondecomp with initial version 0.1.0
Package: bacondecomp
Type: Package
Title: Goodman-Bacon Decomposition
Version: 0.1.0
Authors@R: c( person("Evan", "Flack", email = "evanjflack@gmail.com", role = c("aut", "cre")), person("Edward", "Jee", role = c("aut")) )
Maintainer: Evan Flack <evanjflack@gmail.com>
Description: Decomposition for differences-in-differences with variation in treatment timing from Goodman-Bacon (2018) <doi:10.3386/w25018>.
License: MIT + file LICENSE
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown, testthat, ggplot2, covr
VignetteBuilder: knitr
RoxygenNote: 7.0.2
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2020-01-13 17:52:58 UTC; rstudio
Author: Evan Flack [aut, cre], Edward Jee [aut]
Repository: CRAN
Date/Publication: 2020-01-16 11:40:06 UTC

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New package polyMatrix with initial version 0.2.4
Package: polyMatrix
Version: 0.2.4
Title: Infrastructure for Manipulation Polynomial Matrices
Description: Implementation of class "polyMatrix" for storing a matrix of polynomials and implements basic matrix operations; including a determinant and characteristic polynomial. It is based on the package 'polynom' and uses a lot of its methods to implement matrix operations. This package includes 2 methods of triangularization of polynomial matrices: Extended Euclidean algorithm which is most classical but numerically unstable; Sylvester algorithm based on LQ decomposition. Both methods are described in D. Henrion & M. Sebek, Reliable numerical methods for polynomial matrix triangularization, IEEE Transactions on Automatic Control (Volume 44, Issue 3, Mar 1999, Pages 497-508) <doi:10.1109/9.751344> and in Salah Labhalla, Henri Lombardi & Roger Marlin, Algorithmes de calcule de la reduction de Hermite d'une matrice a coefficients polynomeaux, Theoretical Computer Science (Volume 161, Issue 1-2, July 1996, Pages 69-92) <doi:10.1016/0304-3975(95)00090-9>.
Type: Package
Authors@R: c( person("Tamas", "Prohle", email="prohlet@ludens.elte.hu", role="aut"), person("Peter", "Prohle", email="prohlep@math.elte.hu", role="aut"), person("Nikolai", "Ryzhkov", email="namezys@gmail.com", role=c("aut", "cre")), person("Ildiko", "Laszlo", role="ctb", comment = c(ORCID = "0000-0003-2324-8183")), person("Ulas Onat", "Alakent", role="ctb") )
Imports: polynom
License: MIT + file LICENSE
Depends: R (>= 3.0), stats, MTS
Suggests: testthat
Repository: CRAN
URL: https://github.com/namezys/polymatrix
BugReports: https://github.com/namezys/polymatrix/issues
NeedsCompilation: no
Packaged: 2020-01-13 12:11:01 UTC; namezys
Author: Tamas Prohle [aut], Peter Prohle [aut], Nikolai Ryzhkov [aut, cre], Ildiko Laszlo [ctb] (<https://orcid.org/0000-0003-2324-8183>), Ulas Onat Alakent [ctb]
Maintainer: Nikolai Ryzhkov <namezys@gmail.com>
Date/Publication: 2020-01-16 10:30:02 UTC

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New package DSpoty with initial version 0.1.0
Package: DSpoty
Type: Package
Date: 2020-01-07
Title: Get 'Spotify' API Multiple Information
Version: 0.1.0
Author: Alberto Almuiña <albertogonzalezalmuinha@gmail.com>
Maintainer: Alberto Almuiña <albertogonzalezalmuinha@gmail.com>
Description: You can retrieve 'Spotify' API Information such as artists, albums, tracks, features tracks, recommendations or related artists. This package allows you to search all the information by name and also includes a distance based algorithm to find similar songs. More information: <https://developer.spotify.com/documentation/web-api/> .
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/AlbertoAlmuinha/DSpoty
Imports: dplyr, purrr, httr, stringr
NeedsCompilation: no
Packaged: 2020-01-13 13:29:18 UTC; albgonzal
Repository: CRAN
Date/Publication: 2020-01-16 10:50:02 UTC

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New package demoShiny with initial version 0.1
Package: demoShiny
Title: Runs a 'Shiny' App as Demo or Lists All Demo 'Shiny' Apps
Version: 0.1
Authors@R: person("Sigbert", "Klinke", email="sigbert@hu-berlin.de", role=c("aut", "cre"))
Description: Mimics the demo functionality for 'Shiny' apps in a package. Apps stored to the package subdirectory inst/shiny can be called by demoShiny(topic).
Depends: shiny
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-13 11:58:23 UTC; sigbert
Author: Sigbert Klinke [aut, cre]
Maintainer: Sigbert Klinke <sigbert@hu-berlin.de>
Repository: CRAN
Date/Publication: 2020-01-16 10:30:07 UTC

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Wed, 15 Jan 2020

New package StatCharrms with initial version 0.90.94
Package: StatCharrms
Version: 0.90.94
Date: 2020-1-14
Title: Statistical Analysis of Chemistry, Histopathology, and Reproduction Endpoints Including Repeated Measures and Multi-Generation Studies
Authors@R: c(person("Joe", "Swintek", role = c("aut", "cre"), email = "swintek.joe@epa.gov"), person("Kevin", "Flynn", role = "ctb", email = "Flynn.Kevin@epa.gov"), person("Jon", "Haselman", role = "ctb", email = "Haselman.Jon@epa.gov"), person("Maki", "Sakurai", role = "ctb", email = "skr21441@ideacon.co.jp") )
Depends: R (>= 3.1.0)
Imports: RGtk2, R2HTML, gWidgets, gWidgetsRGtk2, multcomp, nlme, lattice, cairoDevice, car, clinfun, survival, coxme, methods, RSCABS
SystemRequirements: GTK+ (>= 2.8.0)
ByteCompile: no
LazyLoad: yes
LazyData: yes
Description: A front end for the statistical analyses involved in the tier II endocrine disruptor screening program. The analyses available to this package are: Rao-Scott adjusted Cochran-Armitage test for trend By Slices (RSCABS), a Standard Cochran-Armitage test for trend By Slices (SCABS), mixed effects Cox proportional model, Jonckheere-Terpstra step down trend test Dunn test, one way ANOVA, weighted ANOVA, mixed effects ANOVA, repeated measures ANOVA, and Dunnett test.
License: CC0
URL: https://CRAN.R-project.org/package=StatCharrms
Author: Joe Swintek [aut, cre], Kevin Flynn [ctb], Jon Haselman [ctb], Maki Sakurai [ctb]
Maintainer: Joe Swintek <swintek.joe@epa.gov>
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-14 17:00:55 UTC; jswintek
Repository: CRAN
Date/Publication: 2020-01-15 23:00:02 UTC

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New package covglasso with initial version 1.0
Package: covglasso
Version: 1.0
Date: 2020-01-13
Title: Sparse Covariance Matrix Estimation
Description: Direct sparse covariance matrix estimation via the covariance graphical lasso by Bien, Tibshirani (2011) <doi:10.1093/biomet/asr054> using the fast coordinate descent algorithm of Wang (2014) <doi:10.1007/s11222-013-9385-5>.
Authors@R: c(person("Michael", "Fop", role = c("aut", "cre"), email = "michael.fop@ucd.ie", comment = c(ORCID = "0000-0003-3936-2757")), person("Hao", "Wang", role = "ctb"))
Maintainer: Michael Fop <michael.fop@ucd.ie>
Depends: R (>= 3.4)
Imports: Rcpp (>= 1.0)
Suggests: MASS, mixggm
LinkingTo: Rcpp, RcppArmadillo
License: GPL (>= 2)
Repository: CRAN
ByteCompile: true
NeedsCompilation: yes
LazyData: yes
Encoding: UTF-8
Packaged: 2020-01-13 11:49:52 UTC; michael
Author: Michael Fop [aut, cre] (<https://orcid.org/0000-0003-3936-2757>), Hao Wang [ctb]
Date/Publication: 2020-01-15 10:30:02 UTC

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New package carat with initial version 0.1.0
Package: carat
Type: Package
Title: Covariate-Adaptive Randomization for Clinical Trials
Version: 0.1.0
Date: 2019-12-17
Authors@R: c( person(given="Fuyi", family="Tu", email="fuyi.tu@ruc.edu.cn", role="aut"), person(given="Xiaoqing", family="Ye", email="ye_xiaoq@163.com", role=c("aut","cre")), person(given="Wei", family="Ma", email="mawei@ruc.edu.cn", role=c("aut", "ths")), person(given="Feifang", family="Hu", email="ffhu68@163.com", role=c("aut","ths")) )
Maintainer: Xiaoqing Ye <ye_xiaoq@163.com>
Description: Provides functions and command-line user interface to generate allocation sequence by covariate-adaptive randomization for clinical trials. It currently supports six covariate-adaptive randomization procedures. Three hypothesis testing methods that are valid and robust under covariate-adaptive randomization are also available in the package to facilitate the inference for treatment effect under the included randomization procedures. Additionally, the package provides comprehensive and efficient tools to allow one to evaluate and compare the performance of randomization procedures and tests based on various criteria.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.1), ggplot2 (>= 3.1.1), gridExtra (>= 2.3), stringr (>= 1.4.0)
Suggests: dplyr (>= 0.8.1)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Author: Fuyi Tu [aut], Xiaoqing Ye [aut, cre], Wei Ma [aut, ths], Feifang Hu [aut, ths]
Packaged: 2020-01-13 08:17:38 UTC; YeXiaoqing
Repository: CRAN
Date/Publication: 2020-01-15 10:20:02 UTC

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New package yap with initial version 0.1.0
Package: yap
Title: Yet Another Probabilistic Neural Network
Version: 0.1.0
Author: WenSui Liu
Maintainer: WenSui Liu <liuwensui@gmail.com>
Description: Another implementation of probabilistic neural network in R based on Specht (1990) <DOI:10.1016/0893-6080(90)90049-Q>. It is applicable to the pattern recognition with a N-level response, where N > 2.
URL: https://github.com/statcompute/yap
Depends: R (>= 3.6.0)
Imports: stats, randtoolbox, lhs, parallel, datasets
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-08 03:09:02 UTC; liuwensui
Repository: CRAN
Date/Publication: 2020-01-15 09:50:02 UTC

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Tue, 14 Jan 2020

New package retrosheet with initial version 1.1.0
Package: retrosheet
Type: Package
Title: Import Professional Baseball Data from 'Retrosheet'
Version: 1.1.0
Authors@R: c(person(given = "Colin", family = "Douglas", role = c("aut", "cre", "cph"), email = "colindouglas@gmail.com"), person(given = "Richard", family = "Scriven", role = c("aut", "cph"), email = "rmscriven@gmail.com"))
Date: 2019-12-19
Maintainer: Colin Douglas <colindouglas@gmail.com>
Description: A collection of tools to import and structure the (currently) single-season event, game-log, roster, and schedule data available from <http://www.retrosheet.org>. In particular, the event (a.k.a. play-by-play) files can be especially difficult to parse. This package does the parsing on those files, returning the requested data in the most practical R structure to use for sabermetric or other analyses.
URL: http://github.com/colindouglas/retrosheet
Depends: R (>= 2.10)
License: GPL (>= 2)
Imports: xml2 (>= 1.2.2), data.table (>= 1.9.4), stringi (>= 0.4-1), httr (>= 1.4.1), stringr (>= 1.4.0), rvest (>= 0.3.5)
Note: NOTICE regarding the transfer of data from Retrosheet: The information used here was obtained free of charge from and is copyrighted by Retrosheet. Interested parties may contact Retrosheet at "www.retrosheet.org".
RoxygenNote: 7.0.2
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2020-01-14 19:42:51 UTC; cdouglas
Author: Colin Douglas [aut, cre, cph], Richard Scriven [aut, cph]
Repository: CRAN
Date/Publication: 2020-01-15 00:20:03 UTC

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New package warp with initial version 0.1.0
Package: warp
Title: Group Dates
Version: 0.1.0
Authors@R: c(person(given = "Davis", family = "Vaughan", role = c("aut", "cre"), email = "davis@rstudio.com"), person(given = "RStudio", role = "cph"))
Description: Tooling to group dates by a variety of periods including: yearly, monthly, by second, by week of the month, and more. The groups are defined in such a way that they also represent the distance between dates in terms of the period. This extracts valuable information that can be used in further calculations that rely on a specific temporal spacing between observations.
License: MIT + file LICENSE
URL: https://github.com/DavisVaughan/warp
BugReports: https://github.com/DavisVaughan/warp/issues
Depends: R (>= 3.2)
Suggests: covr, testthat (>= 2.1.0), knitr, rmarkdown
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-10 22:08:24 UTC; davis
Author: Davis Vaughan [aut, cre], RStudio [cph]
Maintainer: Davis Vaughan <davis@rstudio.com>
Repository: CRAN
Date/Publication: 2020-01-14 11:40:03 UTC

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New package statgenSTA with initial version 1.0.2
Package: statgenSTA
Type: Package
Title: Single Trial Analysis (STA) of Field Trials
Version: 1.0.2
Date: 2020-01-09
Authors@R: c(person(given = "Bart-Jan", family = "van Rossum", email = "bart-jan.vanrossum@wur.nl", role = c("aut", "cre")), person(given = "Fred", family = "van Eeuwijk", role = "ctb", comment = c(ORCID = "0000-0003-3672-2921")), person(given = "Martin", family = "Boer", role = "ctb"), person(given = "Marcos", family = "Malosetti", role = "ctb", comment = c(ORCID = "0000-0002-8150-1397")), person(given = "Daniela", family = "Bustos-Korts", role = "ctb", comment = c(ORCID = "0000-0003-3827-6726")), person(given = "Emilie", family = "Millet", role = "ctb", comment = c(ORCID = "0000-0002-2913-4892")), person(given = "Joao", family = "Paulo", role = "ctb", comment = c(ORCID = "0000-0002-4180-0763")), person(given = "Maikel", family = "Verouden", role = "ctb", comment = c(ORCID = "0000-0002-4893-3323")), person(given = "Willem", family = "Kruijer", role = "ctb", comment = c(ORCID = "0000-0001-7179-1733")), person(given = "Ron", family = "Wehrens", role = "ctb", comment = c(ORCID = "0000-0002-8798-5599")), person(given = "Choazhi", family = "Zheng", role = "ctb", comment = c(ORCID = "0000-0001-6030-3933")) )
Description: Phenotypic analysis of field trials using mixed models with and without spatial components. One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris. Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<http://www.vsni.co.uk/software/asreml-r>).
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Depends: R (>= 3.3)
Imports: emmeans, ggplot2 (>= 3.0), ggrepel, gridExtra, knitr, lme4, mapproj, maps, methods, qtl, reshape2, scales, SpATS (>= 1.0-10), xtable
Suggests: asreml(>= 3.0), rmarkdown, testthat, tibble
SystemRequirements: pdflatex
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-09 09:05:07 UTC; rossu027
Author: Bart-Jan van Rossum [aut, cre], Fred van Eeuwijk [ctb] (<https://orcid.org/0000-0003-3672-2921>), Martin Boer [ctb], Marcos Malosetti [ctb] (<https://orcid.org/0000-0002-8150-1397>), Daniela Bustos-Korts [ctb] (<https://orcid.org/0000-0003-3827-6726>), Emilie Millet [ctb] (<https://orcid.org/0000-0002-2913-4892>), Joao Paulo [ctb] (<https://orcid.org/0000-0002-4180-0763>), Maikel Verouden [ctb] (<https://orcid.org/0000-0002-4893-3323>), Willem Kruijer [ctb] (<https://orcid.org/0000-0001-7179-1733>), Ron Wehrens [ctb] (<https://orcid.org/0000-0002-8798-5599>), Choazhi Zheng [ctb] (<https://orcid.org/0000-0001-6030-3933>)
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>
Repository: CRAN
Date/Publication: 2020-01-14 11:30:02 UTC

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New package ROMDB with initial version 0.1.0
Package: ROMDB
Type: Package
Date: 2020-01-06
Title: Get 'OMDB' API Multiple Information
Version: 0.1.0
Author: Alberto Almuiña <albertogonzalezalmuinha@gmail.com>
Maintainer: Alberto Almuiña <albertogonzalezalmuinha@gmail.com>
Description: Load multiple movies, series, actors, directors etc from 'OMDB' API. More information in: <http://www.omdbapi.com/> .
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/AlbertoAlmuinha/ROMDB
Imports: dplyr, purrr, httr, stringr, RODBC, magick
NeedsCompilation: no
Packaged: 2020-01-09 12:50:47 UTC; albgonzal
Repository: CRAN
Date/Publication: 2020-01-14 11:40:06 UTC

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New package forestError with initial version 0.1.0
Package: forestError
Type: Package
Title: A Unified Framework for Random Forest Prediction Error Estimation
Version: 0.1.0
Author: Benjamin Lu and Johanna Hardin
Maintainer: Benjamin Lu <b.lu@berkeley.edu>
Description: Estimates the conditional error distributions of random forest predictions and common parameters of those distributions, including conditional mean squared prediction errors, conditional biases, and conditional quantiles, by out-of-bag weighting of out-of-bag prediction errors as proposed by Lu and Hardin (2019+) <arXiv:1912.07435>. This package is compatible with several existing packages that implement random forests in R.
Imports: Rcpp, foreach, doParallel
Suggests: randomForest
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-01-10 20:52:25 UTC; benji
Repository: CRAN
Date/Publication: 2020-01-14 11:30:06 UTC

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New package factset.protobuf.stach with initial version 1.0.2
Package: factset.protobuf.stach
Type: Package
Title: 'FactSet' 'STACH' Library
Version: 1.0.2
Author: analytics-reporting
Maintainer: Charlie Mathis<chmathis@factset.com>
Description: Generates 'RProtobuf' classes for 'FactSet' 'STACH' tabular format which represents complex multi-dimensional array of data. These classes help in the 'serialization' and 'deserialization' of 'STACH' formatted data. See 'GitHub' repository documentation for more information.
URL: https://github.com/factset/stachschema
BugReports: https://github.com/factset/stachschema/issues
License: Apache License 2.0
Encoding: UTF-8
LazyData: true
Imports: R6
Depends: RProtoBuf
Suggests: testthat
RoxygenNote: 7.0.0
NeedsCompilation: no
Packaged: 2020-01-10 20:19:49 UTC; chmathis
Repository: CRAN
Date/Publication: 2020-01-14 11:20:34 UTC

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New package yager with initial version 0.1.0
Package: yager
Title: Yet Another General Regression Neural Network
Version: 0.1.0
Author: WenSui Liu
Maintainer: WenSui Liu <liuwensui@gmail.com>
Description: Another implementation of general regression neural network in R based on Specht (1991) <DOI:10.1109/72.97934>. It is applicable to the functional approximation or the classification.
URL: https://github.com/statcompute/yager
Depends: R (>= 3.6.0)
Imports: datasets, stats, randtoolbox, lhs, MLmetrics, graphics, parallel
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-10 18:07:17 UTC; liuwensui
Repository: CRAN
Date/Publication: 2020-01-14 10:30:02 UTC

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New package nosoi with initial version 1.0.0
Package: nosoi
Type: Package
Title: A Forward Agent-Based Transmission Chain Simulator
Version: 1.0.0
Authors@R: c(person("Sebastian", "Lequime", email = "sebastian.lequime@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3140-0651")), person("Paul", "Bastide", email = "paul.bastide@kuleuven.be", role = "aut", comment = c(ORCID = "0000-0002-8084-9893")), person("Simon", "Dellicour", email = "simon.dellicour@kuleuven.be", role = "aut", comment = c(ORCID = "0000-0001-9558-1052")), person("Philippe", "Lemey", email = "philippe.lemey@kuleuven.be", role = "aut", comment = c(ORCID = "0000-0003-2826-5353")), person("Guy", "Baele", email = "guy.baele@kuleuven.be", role = "aut", comment = c(ORCID = "0000-0002-1915-7732")))
Description: The aim of 'nosoi' (pronounced no.si) is to provide a flexible agent-based stochastic transmission chain/epidemic simulator (Lequime et al. in prep). It is named after the daimones of plague, sickness and disease that escaped Pandora's jar in the Greek mythology. 'nosoi' is able to take into account the influence of multiple variable on the transmission process (e.g. dual-host systems (such as arboviruses), within-host viral dynamics, transportation, population structure), alone or taken together, to create complex but relatively intuitive epidemiological simulations.
URL: https://github.com/slequime/nosoi
Language: en-US
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
biocViews:
Depends: data.table (>= 1.12.0), R (>= 3.5.0)
Imports: utils (>= 3.5.2), stats (>= 3.5.2), methods (>= 3.5.2), dplyr (>= 0.8.0), magrittr (>= 1.5), stringr (>= 1.4.0), reshape2 (>= 1.4.0), raster (>= 2.8-19)
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, igraph, tidyverse, ggplot2, ggnetwork, intergraph, viridis, gganimate, gifski, png, ape (>= 5.3), tidytree (>= 0.2.4), treeio (>= 1.6.2), ggtree (>= 1.16.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-12-18 22:06:53 UTC; slequime
Author: Sebastian Lequime [aut, cre] (<https://orcid.org/0000-0002-3140-0651>), Paul Bastide [aut] (<https://orcid.org/0000-0002-8084-9893>), Simon Dellicour [aut] (<https://orcid.org/0000-0001-9558-1052>), Philippe Lemey [aut] (<https://orcid.org/0000-0003-2826-5353>), Guy Baele [aut] (<https://orcid.org/0000-0002-1915-7732>)
Maintainer: Sebastian Lequime <sebastian.lequime@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-14 10:30:05 UTC

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New package metan with initial version 1.2.1
Type: Package
Package: metan
Title: Multi Environment Trials Analysis
Version: 1.2.1
Authors@R: person(given = "Tiago", family = "Olivoto", role = c("aut", "cre", "cph"), email = "tiagoolivoto@gmail.com", comment = c(ORCID = "0000-0002-0241-9636"))
Maintainer: Tiago Olivoto <tiagoolivoto@gmail.com>
Description: Performs stability analysis of multi-environment trial data using parametric and non-parametric methods. Parametric methods includes Additive Main Effects and Multiplicative Interaction (AMMI) analysis by Gauch (2013) <doi:10.2135/cropsci2013.04.0241>, Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) <doi:10.1201/9781420040371>, joint Regression Analysis by Eberhart & Russel (1966) (<doi:10.2135/cropsci1966.0011183X000600010011x>), ecovalence by Wricke (1965), genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method <doi:10.12702/1984-7033.v04n01a02>, stability variance by Shukla (1972) <doi:10.1038/hdy.1972.87>, weighted average of absolute scores by Olivoto et al. (2019a) <doi:10.2134/agronj2019.03.0220>, and multi-trait stability index by Olivoto et al. (2019b) <doi:10.2134/agronj2019.03.0221>. Non-parametric methods includes superiority index by Lin & Binns (1988) <doi:10.4141/cjps88-018>, nonparametric measures of phenotypic stability by Huehn (1990) <https://link.springer.com/article/10.1007/BF00024241>, TOP third statistic by Fox et al. (1990) <doi:10.1007/BF00040364>, geometric adaptability index described by Shahbazi (2019) <doi:10.1016/j.scienta.2019.04.047>. Functions for computing biometrical analysis such as path analysis, canonical correlation, partial correlation, clustering analysis, and tools for inspecting, manipulating, summarizing and plotting typical multi-environment trial data are also provided.
License: GPL-3
URL: https://github.com/TiagoOlivoto/metan
BugReports: https://github.com/TiagoOlivoto/metan/issues
Depends: R (>= 3.5.0)
Imports: ade4, dendextend, cowplot, dplyr, FWDselect, GGally, ggforce, ggplot2, ggrepel, gplots, grid, lattice, lme4, lmerTest, magrittr, methods, progress, rlang, tibble, tidyr, tidyselect
Suggests: DT, knitr, readxl, rmarkdown, roxygen2
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-10 17:23:25 UTC; tiago
Author: Tiago Olivoto [aut, cre, cph] (<https://orcid.org/0000-0002-0241-9636>)
Repository: CRAN
Date/Publication: 2020-01-14 10:20:02 UTC

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New package impactflu with initial version 0.1.0
Package: impactflu
Title: Quantification of Population-Level Impact of Vaccination
Version: 0.1.0
Authors@R: person(given = "Arseniy", family = "Khvorov", role = c("aut", "cre"), email = "khvorov45@gmail.com")
Description: Implements the compartment model from Tokars (2018) <doi:10.1016/j.vaccine.2018.10.026>. This enables quantification of population-wide impact of vaccination against vaccine-preventable diseases such as influenza.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
RoxygenNote: 7.0.2
LinkingTo: Rcpp
Imports: Rcpp, tibble, dplyr, rlang, glue, lubridate, magrittr
Suggests: testthat (>= 2.1.0)
NeedsCompilation: yes
Packaged: 2020-01-10 20:14:47 UTC; khvorov45
Author: Arseniy Khvorov [aut, cre]
Maintainer: Arseniy Khvorov <khvorov45@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-14 11:00:02 UTC

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New package OptimClassifier with initial version 0.1.5
Package: OptimClassifier
Title: Create the Best Train for Classification Models
Version: 0.1.5
Authors@R: c( person("Agustin", "Perez-Martin", email = "agustin.perez@umh.es", role = "aut", comment = c(ORCID = "0000-0003-4994-3176")), person("Agustin", "Perez-Torregrosa", email = "agustin.perez01@goumh.umh.es", role = c("cre","aut"), comment = c(ORCID = "0000-0001-5658-4795")), person("Marta","Vaca-Lamata", email="mvaca@umh.es",role="aut", comment = c(ORCID = "0000-0001-8496-5579")), person("Antonio Jose","Verdu-Jover", email="ajverdu@umh.es",role="aut", comment = c(ORCID = "0000-0002-6201-7196")) )
Description: Patterns searching and binary classification in economic and financial data is a large field of research. There are a large part of the data that the target variable is binary. Nowadays, many methodologies are used, this package collects most popular and compare different configuration options for Linear Models (LM), Generalized Linear Models (GLM), Linear Mixed Models (LMM), Discriminant Analysis (DA), Classification And Regression Trees (CART), Neural Networks (NN) and Support Vector Machines (SVM).
Depends: R (>= 3.2.3)
License: GPL (>= 2)
BugReports: https://github.com/economistgame/OptimClassifier/issues
URL: https://economistgame.github.io/OptimClassifier
Imports: crayon, dplyr, MASS, lme4, rpart, nnet, e1071, lmtest, nortest, clisymbols, ggplot2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-14 05:03:00 UTC; agustin
Author: Agustin Perez-Martin [aut] (<https://orcid.org/0000-0003-4994-3176>), Agustin Perez-Torregrosa [cre, aut] (<https://orcid.org/0000-0001-5658-4795>), Marta Vaca-Lamata [aut] (<https://orcid.org/0000-0001-8496-5579>), Antonio Jose Verdu-Jover [aut] (<https://orcid.org/0000-0002-6201-7196>)
Maintainer: Agustin Perez-Torregrosa <agustin.perez01@goumh.umh.es>
Repository: CRAN
Date/Publication: 2020-01-14 09:20:10 UTC

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New package dppmix with initial version 0.1.1
Package: dppmix
Type: Package
Title: Determinantal Point Process Mixture Models
Version: 0.1.1
Date: 2019-12-20
Author: Yanxun Xu [aut], Peter Mueller [aut], Donatello Telesca [aut], David J. H. Shih [aut, cre]
Maintainer: David J. H. Shih <djh.shih@gmail.com>
Description: Multivariate Gaussian mixture model with a determinant point process prior to promote the discovery of parsimonious components from observed data. See Xu, Mueller, Telesca (2016) <doi:10.1111/biom.12482>.
URL: https://bitbucket.org/djhshih/dppmix
BugReports: https://bitbucket.org/djhshih/dppmix/issues
Imports: stats, mvtnorm
License: GPL (>= 3)
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-10 16:51:51 UTC; davids
Repository: CRAN
Date/Publication: 2020-01-14 10:00:07 UTC

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New package crplyr with initial version 0.3.3
Package: crplyr
Type: Package
Title: A 'dplyr' Interface for Crunch
Description: In order to facilitate analysis of datasets hosted on the Crunch data platform <http://crunch.io/>, the 'crplyr' package implements 'dplyr' methods on top of the Crunch backend. The usual methods 'select', 'filter', 'group_by', 'summarize', and 'collect' are implemented in such a way as to perform as much computation on the server and pull as little data locally as possible.
Version: 0.3.3
Authors@R: c( person("Greg", "Freedman Ellis", role="aut", email="greg@crunch.io"), person("Jonathan", "Keane", role="aut", email="jkeane@gmail.com"), person("Neal", "Richardson", role="aut", email="neal.p.richardson@gmail.com"), person("Mike", "Malecki", role=c("aut", "cre"), email="mike@crunch.io"), person("Gordon", "Shotwell", role="aut", email="gordon.shotwell@gmail.com"))
URL: https://crunch.io/r/crplyr/, https://github.com/Crunch-io/crplyr
BugReports: https://github.com/Crunch-io/crplyr/issues
License: LGPL (>= 3)
Depends: R (>= 3.0.0), crunch (>= 1.15.3), dplyr
Imports: methods, ggplot2, lazyeval, purrr, tibble, rlang, scales, stringr, viridisLite
Suggests: covr, httptest (>= 3.0.0), magrittr, spelling, vdiffr, knitr, testthat, rmarkdown
RoxygenNote: 7.0.2
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-13 22:45:04 UTC; malecki
Author: Greg Freedman Ellis [aut], Jonathan Keane [aut], Neal Richardson [aut], Mike Malecki [aut, cre], Gordon Shotwell [aut]
Maintainer: Mike Malecki <mike@crunch.io>
Repository: CRAN
Date/Publication: 2020-01-14 09:20:02 UTC

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Mon, 13 Jan 2020

New package tidyREDCap with initial version 0.1.0
Package: tidyREDCap
Title: Helper Functions for Working with REDCap Data
Version: 0.1.0
Authors@R: c(person(given = "Raymond", family = "Balise", role = c("aut", "cre"), email = "balise@miami.edu", comment = c(ORCID = "0000-0002-9856-5901")), person(given = "Gabriel", family = "Odom", role = "aut", email = "gabriel.odom@fiu.edu", comment = c(ORCID = "0000-0003-1341-4555")) )
Description: Helper functions for processing REDCap data in R. 'REDCap' (Research Electronic Data CAPture; <https://projectredcap.org>) is a web-enabled application for building and managing surveys and databases developed at Vanderbilt University.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Depends: R (>= 3.5.0)
Imports: purrr, stringr, tibble, magrittr
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, dplyr, redcapAPI, janitor
VignetteBuilder: knitr
URL: https://raymondbalise.github.io/tidyREDCap/index.html
BugReports: https://github.com/RaymondBalise/tidyREDCap/issues
NeedsCompilation: no
Packaged: 2020-01-10 15:53:57 UTC; rrb28
Author: Raymond Balise [aut, cre] (<https://orcid.org/0000-0002-9856-5901>), Gabriel Odom [aut] (<https://orcid.org/0000-0003-1341-4555>)
Maintainer: Raymond Balise <balise@miami.edu>
Repository: CRAN
Date/Publication: 2020-01-13 23:40:03 UTC

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New package lncDIFF with initial version 1.0.0
Package: lncDIFF
Title: Long Non-Coding RNA Differential Expression Analysis
Version: 1.0.0
Authors@R: person("Qian", "Li", email = "qian.li10000@gmail.com", role = c("aut", "cre"))
Description: We developed an approach to detect differential expression features in long non-coding RNA low counts, using generalized linear model with zero-inflated exponential quasi likelihood ratio test. Methods implemented in this package are described in Li (2019) <doi:10.1186/s12864-019-5926-4>.
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.0
NeedsCompilation: no
Packaged: 2020-01-10 03:36:50 UTC; liq
Author: Qian Li [aut, cre]
Maintainer: Qian Li <qian.li10000@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-13 22:20:08 UTC

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New package ced with initial version 1.0.0
Package: ced
Type: Package
Title: The Compact Encoding Detector
Description: R bindings of the Google Compact Encoding Detection library (<https://github.com/google/compact_enc_det>). The library takes as input a source buffer of raw text bytes and probabilistically determines the most likely encoding for that text. It was designed with accuracy, robustness, small size, and speed in mind.
Version: 1.0.0
Authors@R: c( person(given = "Artem", family = "Klevtsov", role = c("aut", "cre"), email = "a.a.klevtsov@gmail.com", comment = c(ORCID = "0000-0003-0492-6647")), person(given = "Philipp", family = "Upravitelev", role = "ctb", email = "upravitelev@gmail.com"), person("Google Inc.", role = "cph") )
License: GPL-2
Copyright: file COPYRIGHTS
URL: https://artemklevtsov.gitlab.io/ced, https://gitlab.com/artemklevtsov/ced
BugReports: https://gitlab.com/artemklevtsov/ced/issues
Depends: R (>= 3.5.0)
Imports: Rcpp
Suggests: tinytest, curl
LinkingTo: Rcpp
Encoding: UTF-8
NeedsCompilation: yes
ByteCompile: yes
RoxygenNote: 7.0.2
SystemRequirements: C++11
Packaged: 2020-01-10 06:31:12.922 UTC; unikum
Author: Artem Klevtsov [aut, cre] (<https://orcid.org/0000-0003-0492-6647>), Philipp Upravitelev [ctb], Google Inc. [cph]
Maintainer: Artem Klevtsov <a.a.klevtsov@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-13 23:00:02 UTC

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New package vegtable with initial version 0.1.5
Package: vegtable
Version: 0.1.5
Encoding: UTF-8
Title: Handling Vegetation Data Sets
Authors@R: person("Miguel", "Alvarez", email="kamapu78@gmail.com", role=c("aut","cre"), comment=c(ORCID="0000-0003-1500-1834"))
Depends: R(>= 3.0.0), taxlist
Imports: foreign, methods, plotKML, qdapRegex, sp, stringi, vegdata
Suggests: devtools, vegan
LazyData: true
Description: Import and handling data from vegetation-plot databases, especially data stored in 'Turboveg' (<https://www.synbiosys.alterra.nl/turboveg>). Also import/export routines for exchange of data with 'Juice' (<http://www.sci.muni.cz/botany/juice>) are implemented.
License: GPL (>= 2)
URL: https://github.com/kamapu/vegtable
BugReports: https://github.com/kamapu/vegtable/issues
Collate: 'NULLing.R' 'coverconvert-class.R''vegtable-class.R''shaker-class.R' 'cross2db.R''clean.R''as.list.R''merge_taxa.R''add_releves.R' 'header.R''Extract.R''veg_relation.R''relation2header.R' 'vegtable_stat.R''df2vegtable.R''used_synonyms.R' 'subset.R' 'coverconvert-methods.R''names.R' 'tv2coverconvert.R''tv2vegtable.R' 'crosstable.R''aggregate.R''write_juice.R''read_juice.R''vegtable2kml.R' 'layers2samples.R' 'shaker-methods.R''make_cocktail.R' 'summary.R''match_names.R' 'taxa2samples.R''count_taxa.R' 'trait_proportion.R''trait_stats.R' 'StartMessage.R'
NeedsCompilation: no
Packaged: 2020-01-12 06:21:27 UTC; m_alvarez
Author: Miguel Alvarez [aut, cre] (<https://orcid.org/0000-0003-1500-1834>)
Maintainer: Miguel Alvarez <kamapu78@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-13 19:30:02 UTC

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New package RSCABS with initial version 0.9.4
Package: RSCABS
Version: 0.9.4
Date: 2020-1-13
Title: Rao-Scott Cochran-Armitage by Slices Trend Test
Authors@R: c(person("Joe", "Swintek", role = c("aut", "cre"), email = "swintek.joe@epa.gov"), person("Kevin", "Flynn", role = "ctb", email = "Flynn.Kevin@epa.gov") )
Depends: R (>= 3.1.0)
SystemRequirements: Cairo (>= 1.0.0), ATK (>= 1.10.0), Pango (>= 1.10.0), GTK+ (>= 2.8.0), GLib (>= 2.8.0)
Imports: gWidgets, RGtk2, R2HTML, gWidgetsRGtk2, methods
LazyLoad: yes
LazyData: yes
Description: Performs the Rao-Scott Cochran-Armitage by Slices trend test (RSCABS) used in analysis of histopathological endpoints, built to be used with either a GUI or by a command line. The RSCABS method is detailed in "Statistical analysis of histopathological endpoints" by John Green et. al. (2014) <doi:10.1002/etc.2530>.
License: CC0
URL: https://CRAN.R-project.org/package=RSCABS
Author: Joe Swintek [aut, cre], Kevin Flynn [ctb]
Maintainer: Joe Swintek <swintek.joe@epa.gov>
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-13 19:24:13 UTC; jswintek
Repository: CRAN
Date/Publication: 2020-01-13 20:00:02 UTC

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New package s2net with initial version 1.0
Package: s2net
Type: Package
Title: The Generalized Semi-Supervised Elastic-Net
Version: 1.0
Date: 2020-01-08
Authors@R: c(person("Juan C.", "Laria",, role = c("aut", "cre"), email = "juank.laria@gmail.com", comment = c(ORCID = "0000-0001-7734-9647")), person("Line H.", "Clemmensen",, role = c("aut"), email = "lkhc@dtu.dk"))
Description: Implements the generalized semi-supervised elastic-net. This method extends the supervised elastic-net problem, and thus it is a practical solution to the problem of feature selection in semi-supervised contexts. Its mathematical formulation is presented from a general perspective, covering a wide range of models. We focus on linear and logistic responses, but the implementation could be easily extended to other losses in generalized linear models. We develop a flexible and fast implementation, written in 'C++' using 'RcppArmadillo' and integrated into R via 'Rcpp' modules. See Culp, M. 2013 <doi:10.1080/10618600.2012.657139> for references on the Joint Trained Elastic-Net.
License: GPL (>= 2)
Imports: Rcpp, methods, MASS
Depends: stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, glmnet, Metrics, testthat
VignetteBuilder: knitr
URL: https://github.com/jlaria/s2net
BugReports: https://github.com/jlaria/s2net/issues
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-01-11 13:17:07 UTC; juank
Author: Juan C. Laria [aut, cre] (<https://orcid.org/0000-0001-7734-9647>), Line H. Clemmensen [aut]
Maintainer: Juan C. Laria <juank.laria@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-13 17:10:06 UTC

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New package hrcomprisk with initial version 0.1.0
Package: hrcomprisk
Type: Package
Title: Nonparametric Assessment Between Competing Risks Hazard Ratios
Version: 0.1.0
Author: Daniel Antiporta <dantiporta@jhu.edu>; Matthew Matheson <mmathes4@jhu.edu>; Derek Ng <dng@jhu.edu>; Alvaro Munoz <amunoz@jhu.edu>
Maintainer: Daniel Antiporta <dantiporta@jhu.edu>
Description: Nonparametric cumulative-incidence based estimation of the ratios of sub-hazard ratios to cause-specific hazard ratios using the approach from Ng et al. (2020).
Depends: R (>= 3.0.0)
Imports: survival
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
URL: https://github.com/AntiportaD/hrcomprisk
BugReports: https://github.com/AntiportaD/hrcomprisk/issues
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-11 17:48:09 UTC; antiporta
Repository: CRAN
Date/Publication: 2020-01-13 17:30:02 UTC

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New package cuRe with initial version 1.0.0
Package: cuRe
Type: Package
Title: Parametric Cure Model Estimation
Version: 1.0.0
Date: 2020-01-07
Authors@R: person(given = "Lasse Hjort Jakobsen", role = c("aut", "cre"), email = "lahja@dcm.aau.dk")
Maintainer: Lasse Hjort Jakobsen <lahja@dcm.aau.dk>
Description: Contains functions for estimating generalized parametric mixture and non-mixture cure models, loss of lifetime, mean residual lifetime, and crude event probabilities.
URL: http://github.com/LasseHjort/cuRe
BugReports: http://github.com/LasseHjort/cuRe/issues
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.5.0), survival, rstpm2, date
Imports: numDeriv, rootSolve, statmod, relsurv
LazyData: Yes
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-13 08:36:07 UTC; sw1y
Author: Lasse Hjort Jakobsen [aut, cre]
Repository: CRAN
Date/Publication: 2020-01-13 17:30:06 UTC

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New package cSEM with initial version 0.1.0
Package: cSEM
Title: Composite-Based Structural Equation Modeling
Version: 0.1.0
Date: 2020-01-07
Authors@R: c(person(given = "Manuel", family = "Rademaker", role = c("aut", "cre"), email = "manuel.rademaker@uni-wuerzburg.de", comment = c(ORCID = "0000-0002-8902-3561")), person(given = "Florian", family = "Schuberth", role = c("aut"), email = "f.schuberth@utwente.nl", comment = c(ORCID = "0000-0002-2110-9086")), person(given = "Tamara", family = "Schamberger", role = c("ctb"), email = "tamara.schamberger@uni-wuerzburg.de"), person(given = "Michael", family = "Klesel", role = c("ctb"), email = ""), person(given = "Theo K.", family = "Dijkstra", role = c("ctb"), email = ""))
Maintainer: Manuel Rademaker <manuel.rademaker@uni-wuerzburg.de>
Depends: R (>= 3.5.0)
Description: Estimate, assess, test, and study linear, nonlinear, hierarchical and multigroup structural equation models using composite-based approaches and procedures, including estimation techniques such as partial least squares path modeling (PLS-PM) and its derivatives (PLSc, ordPLSc, robustPLSc), generalized structured component analysis (GSCA), generalized structured component analysis with uniqueness terms (GSCAm), generalized canonical correlation analysis (GCCA), principal component analysis (PCA), factor score regression (FSR) using sum score, regression or bartlett scores (including bias correction using Croon’s approach), as well as several tests and typical postestimation procedures (e.g., verify admissibility of the estimates, assess the model fit, test the model fit etc.).
BugReports: https://github.com/M-E-Rademaker/cSEM/issues
URL: https://github.com/M-E-Rademaker/cSEM, https://m-e-rademaker.github.io/cSEM/
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: abind, alabama, cli, crayon, expm, future.apply, future, lavaan, magrittr, MASS, Matrix, matrixcalc, matrixStats, polycor, psych, purrr, Rdpack, stats, symmoments, utils
RdMacros: Rdpack
RoxygenNote: 7.0.2
Suggests: dplyr, tidyr, knitr, nnls, prettydoc, rmarkdown, listviewer, testthat, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-11 15:23:39 UTC; mas55yq
Author: Manuel Rademaker [aut, cre] (<https://orcid.org/0000-0002-8902-3561>), Florian Schuberth [aut] (<https://orcid.org/0000-0002-2110-9086>), Tamara Schamberger [ctb], Michael Klesel [ctb], Theo K. Dijkstra [ctb]
Repository: CRAN
Date/Publication: 2020-01-13 17:20:02 UTC

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New package Boptbd with initial version 1.0.5
Package: Boptbd
Version: 1.0.5
Date: 2020-01-11
Title: Bayesian Optimal Block Designs
Authors@R: c(person("Dibaba Bayisa", "Gemechu", role = c("aut", "cre"), email = "dgemechu@nust.na"), person("Legesse Kassa", "Debusho", role = "aut", email = "debuslk@unisa.ac.za"), person("Linda", "Haines", role = "aut", email = "linda.haines@uct.ac.za"))
Author: Dibaba Bayisa Gemechu [aut, cre], Legesse Kassa Debusho [aut], Linda Haines [aut]
Maintainer: Dibaba Bayisa Gemechu <dgemechu@nust.na>
Depends: R (>= 3.4.0), MASS, Matrix, igraph, tcltk
Description: Computes Bayesian A- and D-optimal block designs under the linear mixed effects model settings using block/array exchange algorithm of Debusho, Gemechu and Haines (2018) <doi:10.1080/03610918.2018.1429617> where the interest is in a comparison of all possible elementary treatment contrasts. The package also provides an optional method of using the graphical user interface (GUI) R package 'tcltk' to ensure that it is user friendly.
License: GPL-2
NeedsCompilation: no
Packaged: 2020-01-11 15:27:36 UTC; Dibaba B Gemechu
Repository: CRAN
Date/Publication: 2020-01-13 17:20:07 UTC

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New package survParamSim with initial version 0.1.0
Package: survParamSim
Type: Package
Title: Parametric Survival Simulation with Parameter Uncertainty
Version: 0.1.0
Authors@R: c( person("Kenta", "Yoshida", , "6.kurabupasu@gmail.com", c("aut", "cre"), comment = c(ORCID = "0000-0003-4967-3831")), person("Laurent", "Claret", , , c("aut")))
Description: Perform survival simulation with parametric survival model generated from 'survreg' function in 'survival' package. In each simulation coefficients are resampled from variance-covariance matrix of parameter estimates to capture uncertainty in model parameters. Prediction intervals of Kaplan-Meier estimates and hazard ratio of treatment effect can be further calculated using simulated survival data.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0),
Imports: magrittr (>= 1.5), mvtnorm, rlang, purrr, forcats, dplyr, tidyr, tibble, ggplot2, survival (>= 2.43), methods
Suggests: testthat (>= 2.1.0), vdiffr, knitr, rmarkdown, survminer
RoxygenNote: 7.0.2
Language: en-US
URL: https://github.com/yoshidk6/survParamSim
BugReports: https://github.com/yoshidk6/survParamSim/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-11 05:29:55 UTC; rokuk
Author: Kenta Yoshida [aut, cre] (<https://orcid.org/0000-0003-4967-3831>), Laurent Claret [aut]
Maintainer: Kenta Yoshida <6.kurabupasu@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-13 17:00:02 UTC

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New package relgam with initial version 1.0
Package: relgam
Type: Package
Title: Reluctant Generalized Additive Models
Version: 1.0
Author: Kenneth Tay, Robert Tibshirani
Maintainer: Kenneth Tay <kjytay@stanford.edu>
Description: A method for fitting the entire regularization path of the reluctant generalized additive model (RGAM) for linear regression, logistic, Poisson and Cox regression models. See Tay, J. K., and Tibshirani, R., (2019) <arXiv:1912.01808> for details.
URL: https://arxiv.org/abs/1912.01808
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: glmnet, foreach
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-08 23:53:21 UTC; kjytay
Repository: CRAN
Date/Publication: 2020-01-13 16:10:02 UTC

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New package PAMA with initial version 0.1.0
Package: PAMA
Title: Rank Aggregation with Partition Mallows Model
Version: 0.1.0
Authors@R: person(given = "Wanchuang", family = "Zhu", role = c("cre","aut"), email = "andy.chou.sub@gmail.com")
Description: Rank aggregation aims to achieve a better ranking list given multiple observations. 'PAMA' implements Partition-Mallows model for rank aggregation. Both Bayesian inference and Maximum likelihood estimation (MLE) are provided. It can handle partial list as well. When covariates information is available, this package can make inference by incorporating the covariate information. More information can be found in the paper "Integrated Partition-Mallows Model and Its Inference for Rank Aggregation". The paper is not yet published.
Depends: R (>= 3.1.0), PerMallows, mc2d, stats
Imports:
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.1
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-01-09 22:11:11 UTC; wanchuangzhu
Author: Wanchuang Zhu [cre, aut]
Maintainer: Wanchuang Zhu <andy.chou.sub@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-13 16:20:05 UTC

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New package optimalThreshold with initial version 1.0
Package: optimalThreshold
Type: Package
Title: Bayesian Methods for Optimal Threshold Estimation
Version: 1.0
SystemRequirements: JAGS 4.x.y
Depends: R (>= 3.1.2)
Date: 2020-01-09
Authors@R: person("Yoann", "Blangero", email = "yblangero@gmail.com", role = c("aut", "cre"))
Description: Functions to estimate the optimal threshold of diagnostic markers or treatment selection markers. The optimal threshold is the marker value that maximizes the utility of the marker based-strategy (for diagnostic or treatment selection) in a given population. The utility function depends on the type of marker (diagnostic or treatment selection), but always takes into account the preferences of the patients or the physician in the decision process. For estimating the optimal threshold, ones must specify the distributions of the marker in different groups (defined according to the type of marker, diagnostic or treatment selection) and provides data to estimate the parameters of these distributions. Ones must also provide some features of the target populations (disease prevalence or treatment efficacies) as well as the preferences of patients or physicians. The functions rely on Bayesian inference which helps producing several indicators derived from the optimal threshold. See Blangero, Y, Rabilloud, M, Ecochard, R, and Subtil, F (2019) <doi:10.1177/0962280218821394> for the original article that describes the estimation method for treatment selection markers and Subtil, F, and Rabilloud, M (2019) <doi:10.1002/bimj.200900242> for diagnostic markers.
License: GPL (>= 2.0)
Collate: Package.R import_package.R scaledT.R ClassUnions.R ClassFitNormalDist.R ClassFitLogNormalDist.R ClassFitGammaDist.R ClassFitStudentDist.R ClassFitLogisticDist.R ClassFitUserDefinedDist.R ClassUndefined.R ClassNormalDist.R ClassLogNormalDist.R ClassGammaDist.R ClassStudentDist.R ClassLogisticDist.R ClassUnionsDist.R ClassCompoundDist.R ClassTrtSelOptThresh.R ClassTrtSelRelUtility.R ClassDiagOptThresh.R ClassDiagRelUtility.R cdf.R gradient.R hessian.R ARS.R samplePosteriorDist.R global.R
RoxygenNote: 6.1.1
Imports: ars, rjags, HDInterval, mgcv, utils, coda, grDevices, methods, stats, graphics
NeedsCompilation: no
Packaged: 2020-01-09 21:51:17 UTC; yblan
Author: Yoann Blangero [aut, cre]
Maintainer: Yoann Blangero <yblangero@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-13 16:10:05 UTC

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New package nlraa with initial version 0.53
Package: nlraa
Version: 0.53
Authors@R: c(person("Fernando", "Miguez", email = "femiguez@iastate.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4627-8329")), person("José", "Pinheiro", role = c("ctb","cph"), comment = "author of nlme::nlsList"), person("Douglas", "Bates", role = c("ctb","cph"), comment = "author of nlme::nlsList"), person("R-core", email = "R-core@R-project.org", role = c("ctb", "cph")))
Title: Nonlinear Regression for Agricultural Applications
Description: Additional nonlinear regression functions using self-start (SS) algorithms. One of the functions is the Beta growth function proposed by Yin et al. (2003) <doi:10.1093/aob/mcg029>. There are several other functions with breakpoints (e.g. linear-plateau, plateau-linear, exponential-plateau, plateau-exponential, quadratic-plateau, plateau-quadratic and bilinear), a non-rectangular hyperbola and a bell-shaped curve. Eighteen new self-start (SS) functions in total. This package also supports the publication 'Nonlinear regression Models and applications in agricultural research' by Archontoulis and Miguez (2015) <doi:10.2134/agronj2012.0506>, a book chapter with similar material <doi:10.2134/appliedstatistics.2016.0003> and a publication by Oddi et. al. (2019) in Ecology and Evolution <doi:10.1002/ece3.5543>. The function 'nlsLMList' uses nlsLM for fitting, but it is otherwise almost identical to 'nlme::nlsList'. One of the main benefits is that these functions can be integrated in the modeling framework of the 'nlme' package. It also provides three vignettes with extended examples.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
VignetteBuilder: knitr
BugReports: https://github.com/femiguez/nlraa/issues
Imports: knitr, nlme, stats
Suggests: bbmle, emmeans, ggplot2, HydroMe, lattice, minpack.lm, nlstools, nls2, segmented
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-09 21:39:02 UTC; fernandomiguez
Author: Fernando Miguez [aut, cre] (<https://orcid.org/0000-0002-4627-8329>), José Pinheiro [ctb, cph] (author of nlme::nlsList), Douglas Bates [ctb, cph] (author of nlme::nlsList), R-core [ctb, cph]
Maintainer: Fernando Miguez <femiguez@iastate.edu>
Repository: CRAN
Date/Publication: 2020-01-13 16:20:02 UTC

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New package BRL with initial version 0.1.0
Package: BRL
Title: Beta Record Linkage
Version: 0.1.0
Authors@R: person("Mauricio", "Sadinle", email = "msadinle@uw.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7092-3877"))
Description: Implementation of the record linkage methodology proposed by Sadinle (2017) <doi:10.1080/01621459.2016.1148612>. It handles the bipartite record linkage problem, where two duplicate-free datafiles are to be merged.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: utils
RoxygenNote: 7.0.2
URL: https://github.com/msadinle/BRL
BugReports: https://github.com/msadinle/BRL/issues
NeedsCompilation: yes
Packaged: 2020-01-11 01:12:16 UTC; Mauricio Sadinle
Author: Mauricio Sadinle [aut, cre] (<https://orcid.org/0000-0002-7092-3877>)
Maintainer: Mauricio Sadinle <msadinle@uw.edu>
Repository: CRAN
Date/Publication: 2020-01-13 16:50:06 UTC

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New package BinaryDosage with initial version 1.0.0
Package: BinaryDosage
Title: Creates, Merges, and Reads Binary Dosage Files
Version: 1.0.0
Authors@R: c(person(given = "John", family = "Morrison", role = c("aut", "cre"), email = "jmorr@usc.edu"), person(given = "NIEHS", role = "fnd", comment = "P01 CA196559"), person(given = "NIEHS", role = "fnd", comment = "R01 CA201407"), person(given = "NIEHS", role = "fnd", comment = "P30 ES007048"), person(given = "NIEHS", role = "fnd", comment = "P01 HL115606"))
Description: Tools to create binary dosage from either VCF or GEN files, merge binary dosage files, and read binary dosage files.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, testthat (>= 2.1.0), covr
VignetteBuilder: knitr
RoxygenNote: 7.0.2
LinkingTo: Rcpp
Imports: Rcpp, digest, prodlim
NeedsCompilation: yes
Packaged: 2020-01-09 23:00:33 UTC; jmorr
Author: John Morrison [aut, cre], NIEHS [fnd] (P01 CA196559), NIEHS [fnd] (R01 CA201407), NIEHS [fnd] (P30 ES007048), NIEHS [fnd] (P01 HL115606)
Maintainer: John Morrison <jmorr@usc.edu>
Repository: CRAN
Date/Publication: 2020-01-13 16:20:08 UTC

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New package atakrig with initial version 0.9.5
Package: atakrig
Type: Package
Title: Area-to-Area Kriging
Version: 0.9.5
Authors@R: c( person("Maogui", "Hu", role = c("aut", "cre"), email = "humg@lreis.ac.cn"), person("Yanwei", "Huang", role = "ctb"), person("Roger", "Bivand", role = "ctb"))
Description: Point-scale variogram deconvolution from irregular/regular spatial support according to Goovaerts, P., (2008) <doi: 10.1007/s11004-007-9129-1>; ordinary area-to-area (co)Kriging and area-to-point (co)Kriging.
Imports: gstat, sp, rgeos, foreach, doSNOW, snow, FNN, methods, MASS, Rcpp
Suggests: raster, rgdal, rtop
License: GPL (>= 2.0)
NeedsCompilation: yes
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Packaged: 2020-01-11 04:57:34 UTC; humg
Author: Maogui Hu [aut, cre], Yanwei Huang [ctb], Roger Bivand [ctb]
Maintainer: Maogui Hu <humg@lreis.ac.cn>
Repository: CRAN
Date/Publication: 2020-01-13 16:50:02 UTC

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New package themis with initial version 0.1.0
Package: themis
Title: Extra Recipes Steps for Dealing with Unbalanced Data
Version: 0.1.0
Authors@R: person(given = "Emil", family = "Hvitfeldt", role = c("aut", "cre"), email = "emilhhvitfeldt@gmail.com", comment = c(ORCID = "0000-0002-0679-1945"))
Description: A dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets. A dataset can be balanced by increasing the number of minority cases using SMOTE 2011 <arXiv:1106.1813>, BorderlineSMOTE 2005 <doi:10.1007/11538059_91> and ADASYN 2008 <https://ieeexplore.ieee.org/document/4633969>. Or by decreasing the number of majority cases using NearMiss 2003 <https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf> or Tomek link removal 1976 <https://ieeexplore.ieee.org/document/4309452>.
License: MIT + file LICENSE
Suggests: testthat (>= 2.1.0), covr, ggplot2, modeldata
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Depends: R (>= 2.10), recipes (>= 0.1.4)
Imports: tibble, purrr, withr, generics, dplyr, rlang, tidyselect (>= 0.2.5), ROSE, unbalanced, RANN, dials
URL: https://github.com/tidymodels/themis
BugReports: https://github.com/tidymodels/themis/issues
NeedsCompilation: no
Packaged: 2020-01-09 16:41:29 UTC; emilhvitfeldthansen
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-13 15:30:02 UTC

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New package outForest with initial version 0.1.0
Type: Package
Package: outForest
Title: Multivariate Outlier Detection and Replacement
Version: 0.1.0
Date: 2020-01-09
Authors@R: person(given = "Michael", family = "Mayer", role = c("aut", "cre"), email = "mayermichael79@gmail.com")
Maintainer: Michael Mayer <mayermichael79@gmail.com>
Description: Provides a random forest based implementation of the method described in Chapter 7.1.2 (Regression model based anomaly detection) of Chandola et al. (2009) <doi.acm.org/10.1145/1541880.1541882>. It works as follows: Each numeric variable is regressed onto all other variables by a random forest. If the scaled absolute difference between observed value and out-of-bag prediction of the corresponding random forest is suspiciously large, then a value is considered an outlier. The package offers different options to replace such outliers, e.g. by realistic values found via predictive mean matching. Once the method is trained on a reference data, it can be applied to new data.
License: GPL (>= 2)
URL: https://github.com/mayer79/outForest
BugReports: https://github.com/mayer79/outForest/issues
Depends: R (>= 3.5.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
Imports: stats, graphics, FNN, ranger, missRanger (>= 2.1.0)
Suggests: dplyr, knitr
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-09 18:20:39 UTC; Michael
Author: Michael Mayer [aut, cre]
Repository: CRAN
Date/Publication: 2020-01-13 15:50:03 UTC

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New package extRC with initial version 1.0
Package: extRC
Type: Package
Title: Extended RC Models for Contingency Tables
Version: 1.0
Date: 2019-12-24
Author: Francesco Bartolucci, Antonio Forcina
Maintainer: Francesco Bartolucci <francesco.bartolucci@unipg.it>
Description: Maximum likelihood estimation of an extended class of row-column (RC) association models for two-dimensional contingency tables, which are formulated by a condition of reduced rank on a matrix of extended association parameters; see Forcina (2019) <arXiv:1910.13848>. These parameters are defined by choosing the logit type for the row and column variables among four different options and a transformation derived from suitable divergence measures.
License: GPL (>= 2)
Imports: MASS
NeedsCompilation: no
Packaged: 2020-01-09 15:10:07 UTC; francescobartolucci
Repository: CRAN
Date/Publication: 2020-01-13 15:40:02 UTC

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New package apyramid with initial version 0.1.0
Package: apyramid
Title: Visualize Population Pyramids Aggregated by Age
Version: 0.1.0
Authors@R: c( person(given = "Zhian N.", family = "Kamvar", role = c("aut", "cre"), email = "zkamvar@gmail.com", comment = c(ORCID = "0000-0003-1458-7108")), person(given = "Alex", family = "Spina", role = c("ctb")))
Description: Provides a quick method for visualizing non-aggregated line-list or aggregated census data stratified by age and one or two categorical variables (e.g. gender and health status) with any number of values. It returns a 'ggplot' object, allowing the user to further customize the output. This package is part of the 'R4Epis' project <https://r4epis.netlify.com>.
License: GPL-3
Depends: R (>= 3.2.0)
URL: https://github.com/R4EPI/apyramid, https://r4epis.netlify.com
BugReports: https://github.com/R4EPI/apyramid/issues
Imports: ggplot2 (>= 3.0.0), tidyselect, rlang, forcats, dplyr, scales, glue
Suggests: testthat (>= 2.1.0), survey, srvyr, vdiffr, covr, outbreaks, knitr, rmarkdown
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-09 14:58:36 UTC; zkamvar
Author: Zhian N. Kamvar [aut, cre] (<https://orcid.org/0000-0003-1458-7108>), Alex Spina [ctb]
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-13 15:50:06 UTC

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New package packager with initial version 1.0.0
Package: packager
Title: Create, Build and Maintain Packages
Version: 1.0.0
Authors@R: person(given = "Andreas Dominik", family = "Cullmann", role = c("aut", "cre"), email = "fvafrcu@mailbox.org")
Description: Helper functions for package creation, building and maintenance. Designed to work with a build system such as 'GNU make' or package 'fakemake' to help you to conditionally work through the stages of package development (such as spell checking, linting, testing, before building and checking a package).
License: BSD_2_clause + file LICENSE
URL: https://gitlab.com/fvafrCU/packager
Depends: R (>= 3.3.0)
Imports: callr, checkmate, codetools, crayon, cyclocomp, desc, devtools, fakemake, git2r, httr, methods, pkgbuild, pkgload, rcmdcheck, remotes, rprojroot, tools, usethis, utils, whisker, whoami, withr
Suggests: cleanr, covr, digest, knitr, lintr, rmarkdown, roxygen2, RUnit, spelling, testthat
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-09 07:42:19 UTC; qwer
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>
Repository: CRAN
Date/Publication: 2020-01-13 11:10:06 UTC

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New package serpstatr with initial version 0.0.1
Package: serpstatr
Type: Package
Title: 'Serpstat' API Wrapper
Version: 0.0.1
Authors@R: person('Alex', 'Danilin', email = 'alexnikdanilin@gmail.com', role = c('aut', 'cre'))
URL: https://serpstat.com/api/
Description: The primary goal of 'Serpstat' API <https://serpstat.com/api/> is to reduce manual SEO (search engine optimization) and PPC (pay-per-click) tasks. You can automate your keywords research or competitors analysis with this API wrapper.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: httr (>= 1.4.1)
RoxygenNote: 7.0.2
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-01-09 07:39:13 UTC; mrbubu
Author: Alex Danilin [aut, cre]
Maintainer: Alex Danilin <alexnikdanilin@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-13 10:30:02 UTC

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Sun, 12 Jan 2020

New package xpose with initial version 0.4.6
Package: xpose
Type: Package
Title: Diagnostics for Pharmacometric Models
Version: 0.4.6
Authors@R: c( person('Benjamin', 'Guiastrennec', role = c('aut', 'cre', 'cph'), email = 'guiastrennec@gmail.com'), person('Andrew C.', 'Hooker', role = c('aut', 'cph'), email = 'andrew.hooker@farmbio.uu.se'), person('Sebastian', 'Ueckert', role = c('aut', 'cph'), email = 'sebastian.ueckert@farmbio.uu.se'), person('Mike K.', 'Smith', role = 'ctb', email = 'mike.k.smith@pfizer.com'), person('Mats O.', 'Karlsson', role = c('aut', 'cph'), email = 'mats.karlsson@farmbio.uu.se'))
Description: Diagnostics for non-linear mixed-effects (population) models from 'NONMEM' <http://www.iconplc.com/innovation/nonmem/>. 'xpose' facilitates data import, creation of numerical run summary and provide 'ggplot2'-based graphics for data exploration and model diagnostics.
Depends: R (>= 3.3.0), ggplot2 (>= 3.1.0)
Imports: dplyr (>= 0.8.0), ggforce (>= 0.2.0), grDevices, purrr (>= 0.3.0), readr (>= 1.3.0), rlang (>= 0.3.0), stringr (>= 1.4.0), tibble (>= 2.1.0), tidyr (>= 0.8.0), utils, stats, vpc (>= 1.1.0)
Suggests: here, gridExtra, rmarkdown, knitr, testthat, plotly, webshot, mvtnorm
License: LGPL-3
URL: https://github.com/UUPharmacometrics/xpose
BugReports: https://github.com/UUPharmacometrics/xpose/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-12 21:02:05 UTC; bguiastr
Author: Benjamin Guiastrennec [aut, cre, cph], Andrew C. Hooker [aut, cph], Sebastian Ueckert [aut, cph], Mike K. Smith [ctb], Mats O. Karlsson [aut, cph]
Maintainer: Benjamin Guiastrennec <guiastrennec@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-12 21:50:02 UTC

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New package PRIMAL with initial version 1.0.1
Package: PRIMAL
Type: Package
Title: Parametric Simplex Method for Sparse Learning
Version: 1.0.1
Date: 2020-01-10
Author: Zichong Li, Qianli Shen
Maintainer: Zichong Li <zichongli5@gmail.com>
LinkingTo: Rcpp, RcppEigen
Description: Implements a unified framework of parametric simplex method for a variety of sparse learning problems (e.g., Dantzig selector (for linear regression), sparse quantile regression, sparse support vector machines, and compressive sensing) combined with efficient hyper-parameter selection strategies. The core algorithm is implemented in C++ with Eigen3 support for portable high performance linear algebra. For more details about parametric simplex method, see Haotian Pang (2017) <https://papers.nips.cc/paper/6623-parametric-simplex-method-for-sparse-learning.pdf>.
Imports: Matrix
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2020-01-12 10:34:04 UTC; lizichong
RoxygenNote: 6.1.1
Repository: CRAN
Date/Publication: 2020-01-12 14:40:18 UTC

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New package orderly with initial version 1.0.4
Package: orderly
Title: Lightweight Reproducible Reporting
Version: 1.0.4
Description: Order, create and store reports from R. By defining a lightweight interface around the inputs and outputs of an analysis, a lot of the repetitive work for reproducible research can be automated. We define a simple format for organising and describing work that facilitates collaborative reproducible research and acknowledges that all analyses are run multiple times over their lifespans.
License: MIT + file LICENSE
Encoding: UTF-8
Authors@R: c(person("Rich", "FitzJohn", role = c("aut", "cre"), email = "rich.fitzjohn@gmail.com"), person("Robert", "Ashton", role = "aut"), person("Alex", "Hill", role = "aut"), person("Martin", "Eden", role = "aut"), person("Wes", "Hinsley", role = "aut"), person("Emma", "Russell", role = "aut"), person("James", "Thompson", role = "aut"), person("Imperial College of Science, Technology and Medicine", role = "cph"))
URL: https://github.com/vimc/orderly
BugReports: https://github.com/vimc/orderly/issues
SystemRequirements: git
Imports: DBI, R6, RSQLite, digest, docopt, fs (>= 1.2.7), ids, withr, yaml, zip (>= 2.0.0)
Suggests: httr, jsonlite, knitr, mockery, processx, rmarkdown, testthat, vaultr (>= 1.0.0)
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Language: en-GB
NeedsCompilation: no
Packaged: 2020-01-12 13:07:22 UTC; rich
Author: Rich FitzJohn [aut, cre], Robert Ashton [aut], Alex Hill [aut], Martin Eden [aut], Wes Hinsley [aut], Emma Russell [aut], James Thompson [aut], Imperial College of Science, Technology and Medicine [cph]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-12 14:40:02 UTC

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New package sanzo with initial version 0.1.0
Package: sanzo
Title: Color Palettes Based on the Works of Sanzo Wada
Version: 0.1.0
Authors@R: person(given = "Jacqueline", family = "Maasch", role = c("aut", "cre"), email = "jacqueline.maasch@gmail.com")
Description: Inspired by the art and color research of Sanzo Wada (1883-1967), his "Dictionary Of Color Combinations" (2011, ISBN:978-4861522475), and the interactive site by Dain M. Blodorn Kim <https://github.com/dblodorn/sanzo-wada>, this package brings Wada's color combinations to R for easy use in data visualizations. This package honors 60 of Wada's color combinations: 20 duos, 20 trios, and 20 quads.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/jmaasch/sanzo
BugReports: https://github.com/jmaasch/sanzo/issues
RoxygenNote: 7.0.2
Suggests: datasets, graphics, stats, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-08 21:57:19 UTC; razel
Author: Jacqueline Maasch [aut, cre]
Maintainer: Jacqueline Maasch <jacqueline.maasch@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-12 11:30:02 UTC

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New package nhlscrape with initial version 0.1.2
Package: nhlscrape
Type: Package
Title: Scrapes the 'NHL' API for Statistical Analysis
Version: 0.1.2
Author: Adam Azoulay [aut, cre]
Authors@R: person("Adam", "Azoulay", email = "adam1azoulay@gmail.com", role = c("aut", "cre"))
Maintainer: Adam Azoulay <adam1azoulay@gmail.com>
URL: https://github.com/adamazoulay/nhlscrape
BugReports: https://github.com/adamazoulay/nhlscrape/issues
Description: Add game events to a database file to use for statistical analysis of hockey games. This means we only call the 'NHL' API once for each game we want to add. We will have very fast retrieval of data once games have been added since the data is stored locally. We use the API located at <https://statsapi.web.nhl.com/api/v1/teams> with supplemental data from <https://www.nhl.com/scores/>. Other endpoints can be found at <https://gitlab.com/dword4/nhlapi>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: httr, jsonlite, RSQLite, rvest, DBI, xml2
RoxygenNote: 7.0.1
NeedsCompilation: no
Packaged: 2020-01-08 22:34:30 UTC; Adam
Suggests: testthat
Repository: CRAN
Date/Publication: 2020-01-12 11:40:02 UTC

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New package modelbased with initial version 0.1.0
Package: modelbased
Type: Package
Title: Estimation of Model-Based Predictions, Contrasts and Means
Version: 0.1.0
Authors@R: c( person("Dominique", "Makowski", email = "dom.makowski@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5375-9967")), person("Daniel", "Lüdecke", role = c("aut"), email = "d.luedecke@uke.de", comment = c(ORCID = "0000-0002-8895-3206")), person("Mattan S.", "Ben-Shachar", role = c("aut"), email = "matanshm@post.bgu.ac.il", comment = c(ORCID = "0000-0002-4287-4801")) )
Maintainer: Dominique Makowski <dom.makowski@gmail.com>
URL: https://github.com/easystats/modelbased
BugReports: https://github.com/easystats/modelbased/issues
Description: Implements a general interface for model-based estimations for a wide variety of models (see support list of insight; Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), used in the computation of marginal means, contrast analysis and predictions.
Imports: insight (>= 0.7.1), bayestestR (>= 0.4.0), parameters (>= 0.3.0), effectsize (>= 0.0.1), emmeans
Suggests: coda, covr, dplyr, gganimate, ggplot2, knitr, lme4, MASS, merTools, rmarkdown, rstanarm, brms, see, testthat
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-08 00:52:02 UTC; Dom
Author: Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>)
Repository: CRAN
Date/Publication: 2020-01-12 11:00:02 UTC

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New package fcaR with initial version 1.0.2
Package: fcaR
Title: Formal Concept Analysis
Version: 1.0.2
Authors@R: c( person(given = "Domingo", family = "Lopez Rodriguez", role = c("aut", "cre"), email = c("dominlopez@uma.es", "neuroimaginador@gmail.com"), comment = c(ORCID = "0000-0002-0172-1585")), person(given = "Angel", family = "Mora", role = "aut", email = "amorabonilla@gmail.com"), person(given = "Jesus", family = "Dominguez", role = "aut"), person(given = "Ana", family = "Villalon", role = "aut"), person(given = "Ian", family = "Johnson", role = "ctb") )
Maintainer: Domingo Lopez Rodriguez <dominlopez@uma.es>
Description: Provides tools to perform fuzzy formal concept analysis, presented in Wille (1982) <doi:10.1007/978-3-642-01815-2_23> and in Ganter and Obiedkov (2016) <doi:10.1007/978-3-662-49291-8>. It provides functions to load and save a formal context, extract its concept lattice and implications. In addition, one can use the implications to compute semantic closures of fuzzy sets and, thus, build recommendation systems.
License: GPL-3
Imports: stringr, hasseDiagram, RColorBrewer, scales, arules, tictoc, knitr, Matrix, Rcpp, methods
Suggests: testthat (>= 2.1.0), covr, rmarkdown
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.1.9000
URL: https://github.com/neuroimaginador/fcaR
BugReports: https://github.com/neuroimaginador/fcaR/issues
Depends: R (>= 3.1)
LinkingTo: Rcpp
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-08 19:23:31 UTC; domingo
Author: Domingo Lopez Rodriguez [aut, cre] (<https://orcid.org/0000-0002-0172-1585>), Angel Mora [aut], Jesus Dominguez [aut], Ana Villalon [aut], Ian Johnson [ctb]
Repository: CRAN
Date/Publication: 2020-01-12 10:50:06 UTC

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New package BioPETsurv with initial version 0.1.0
Package: BioPETsurv
Type: Package
Title: Biomarker Prognostic Enrichment Tool for Time-to-Event Trial
Version: 0.1.0
Authors@R: c( person("Si", "Cheng", email="chengsi@uw.edu", role = c("cre", "aut")), person("Kathleen F.","Kerr", email="katiek@uw.edu", role = "ctb"))
Description: Prognostic Enrichment is a strategy of enriching a clinical trial for testing an intervention intended to prevent or delay an unwanted clinical event. A prognostically enriched trial enrolls only patients who are more likely to experience the unwanted clinical event than the broader patient population (R. Temple (2010) <doi:10.1038/clpt.2010.233>). By testing the intervention in an enriched study population, the trial may be adequately powered with a smaller sample size, which can have both practical and ethical advantages. This package provides tools to evaluate biomarkers for prognostic enrichment of clinical trials with survival/time-to-event outcomes.
Depends: R (>= 3.1.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: survival, ggplot2, gridExtra
NeedsCompilation: no
Packaged: 2020-01-08 18:03:28 UTC; Si Cheng
Author: Si Cheng [cre, aut], Kathleen F. Kerr [ctb]
Maintainer: Si Cheng <chengsi@uw.edu>
Repository: CRAN
Date/Publication: 2020-01-12 10:20:02 UTC

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Sat, 11 Jan 2020

New package babette with initial version 2.1.1
Package: babette
Title: Control 'BEAST2'
Version: 2.1.1
Authors@R: c( person("Richèl J.C.", "Bilderbeek", email = "richel@richelbilderbeek.nl", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1107-7049")), person("Joëlle", "Barido-Sottani", role = "rev", comment = "Joëlle reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/209"), person("David", "Winter", role = "rev", comment = "David reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/209"), person("Giovanni", "Laudanno", email = "glaudanno@gmail.com", role = "ctb"))
Maintainer: Richèl J.C. Bilderbeek <richel@richelbilderbeek.nl>
Description: 'BEAST2' (<http://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'BEAST2' is commonly accompanied by 'BEAUti 2', 'Tracer' and 'DensiTree'. 'babette' provides for an alternative workflow of using all these tools separately. This allows doing complex Bayesian phylogenetics easily and reproducibly from 'R'.
License: GPL-3
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
URL: https://docs.ropensci.org/babette, https://github.com/ropensci/babette
BugReports: https://github.com/ropensci/babette/issues
Depends: R (>= 3.5.0), beautier (>= 2.3), beastier (>= 2.1), mauricer, tracerer
Imports: phangorn, remotes, stringr, testit, xml2
Suggests: ape, ggplot2, hunspell, knitr, lintr, nLTT, rappdirs, rmarkdown, spelling, testthat (>= 2.1.0)
Language: en-US
Encoding: UTF-8
SystemRequirements: BEAST2 (http://www.beast2.org/)
NeedsCompilation: no
Packaged: 2019-12-31 06:52:51 UTC; richel
Author: Richèl J.C. Bilderbeek [aut, cre] (<https://orcid.org/0000-0003-1107-7049>), Joëlle Barido-Sottani [rev] (Joëlle reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/209), David Winter [rev] (David reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/209), Giovanni Laudanno [ctb]
Repository: CRAN
Date/Publication: 2020-01-11 12:50:02 UTC

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Fri, 10 Jan 2020

New package esaddle with initial version 0.0.6
Package: esaddle
Type: Package
Title: Extended Empirical Saddlepoint Density Approximations
Version: 0.0.6
Date: 2020-01-01
Author: Matteo Fasiolo and Simon N. Wood
Maintainer: Matteo Fasiolo <matteo.fasiolo@gmail.com>
Description: Tools for fitting the Extended Empirical Saddlepoint (EES) density of Fasiolo et al. (2018) <doi:10.1214/18-EJS1433>.
License: GPL (>= 2)
URL: https://github.com/mfasiolo/esaddle
Imports: compiler, stats, graphics, parallel, plyr, doParallel, mvnfast
Suggests: knitr, testthat
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
RoxygenNote: 7.0.2
NeedsCompilation: yes
Packaged: 2020-01-10 16:54:02 UTC; teo
Repository: CRAN
Date/Publication: 2020-01-10 22:50:02 UTC

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New package coxed with initial version 0.3.2
Package: coxed
Type: Package
Title: Duration-Based Quantities of Interest for the Cox Proportional Hazards Model
Version: 0.3.2
Depends: R (>= 3.5.0), rms, survival, mgcv
Authors@R: c( person("Kropko,", "Jonathan", email = "jkropko@virginia.edu", role = c("aut", "cre")), person("Harden,", "Jeffrey J.", email = "jeff.harden@nd.edu", role = c("aut")))
Description: Functions for generating, simulating, and visualizing expected durations and marginal changes in duration from the Cox proportional hazards model as described in Kropko and Harden (2017) <doi:10.1017/S000712341700045X> and Harden and Kropko (2018) <doi:10.1017/psrm.2018.19>.
License: GPL-2
Encoding: UTF-8
URL: https://github.com/jkropko/coxed
LazyData: true
Imports: PermAlgo, dplyr, tidyr, ggplot2, gridExtra, utils
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, bindrcpp
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-10 15:12:49 UTC; jk8sd
Author: Kropko, Jonathan [aut, cre], Harden, Jeffrey J. [aut]
Maintainer: "Kropko, Jonathan" <jkropko@virginia.edu>
Repository: CRAN
Date/Publication: 2020-01-10 23:00:03 UTC

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New package biomartr with initial version 0.9.2
Package: biomartr
Title: Genomic Data Retrieval
Version: 0.9.2
Authors@R: person("Hajk-Georg", "Drost", role = c("aut", "cre"), email = "hajk-georg.drost@tuebingen.mpg.de", comment = c(ORCID = "http://orcid.org/0000-0002-1567-306X"))
Description: Perform large scale genomic data retrieval and functional annotation retrieval. This package aims to provide users with a standardized way to automate genome, proteome, 'RNA', coding sequence ('CDS'), 'GFF', and metagenome retrieval from 'NCBI RefSeq', 'NCBI Genbank', 'ENSEMBL', 'ENSEMBLGENOMES', and 'UniProt' databases. Furthermore, an interface to the 'BioMart' database (Smedley et al. (2009) <doi:10.1186/1471-2164-10-22>) allows users to retrieve functional annotation for genomic loci. In addition, users can download entire databases such as 'NCBI RefSeq' (Pruitt et al. (2007) <doi:10.1093/nar/gkl842>), 'NCBI nr', 'NCBI nt', 'NCBI Genbank' (Benson et al. (2013) <doi:10.1093/nar/gks1195>), etc. as well as 'ENSEMBL' and 'ENSEMBLGENOMES' with only one command.
VignetteBuilder: knitr
NeedsCompilation: yes
Depends: R (>= 3.1.1)
Imports: biomaRt, Biostrings, curl, tibble, jsonlite, data.table (>= 1.9.4), dplyr (>= 0.3.0), readr (>= 0.2.2), downloader (>= 0.3), RCurl (>= 1.95-4.5), XML (>= 3.98-1.1), httr (>= 0.6.1), stringr (>= 0.6.2), purrr, R.utils, philentropy, fs (>= 1.3.1)
Suggests: knitr (>= 1.6), rmarkdown (>= 0.3.3), devtools (>= 1.6.1), testthat, seqinr, magrittr
License: GPL-2
LazyData: true
URL: https://docs.ropensci.org/biomartr, https://github.com/ropensci/biomartr
BugReports: https://github.com/ropensci/biomartr/issues
RoxygenNote: 7.0.2
Encoding: UTF-8
X-schema.org-keywords: BioMart, genomic-data-retrieval, annotation-retrieval, database-retrieval, NCBI, ENSEMBL, biological-data-retrieval
X-schema.org-applicationCategory: Data Access
X-schema.org-isPartof: "ropensci.org"
Packaged: 2020-01-10 15:28:22 UTC; hdrost
Author: Hajk-Georg Drost [aut, cre] (<https://orcid.org/0000-0002-1567-306X>)
Maintainer: Hajk-Georg Drost <hajk-georg.drost@tuebingen.mpg.de>
Repository: CRAN
Date/Publication: 2020-01-10 23:00:06 UTC

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New package skedastic with initial version 0.1.0
Package: skedastic
Type: Package
Title: Heteroskedasticity Diagnostics for Linear Regression Models
Version: 0.1.0
Authors@R: c(person(given = "Thomas", family = "Farrar", email = "tjfarrar@alumni.uwaterloo.ca", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0744-6972")), person(given = "University of the Western Cape", role = "cph"))
Description: Implements numerous methods for detecting heteroskedasticity (sometimes called heteroscedasticity) in the classical linear regression model. These include the parametric and nonparametric tests of Goldfeld and Quandt (1965) <doi:10.1080/01621459.1965.10480811>, the test of Glejser (1969) <doi:10.1080/01621459.1969.10500976> as formulated by Mittelhammer, Judge and Miller (2000, ISBN: 0-521-62394-4), the BAMSET Test of Ramsey (1969) <doi:10.1111/j.2517-6161.1969.tb00796.x>, which uses the BLUS residuals derived by Theil (1965) <doi:10.1080/01621459.1965.10480851>, the test of Harvey (1976) <doi:10.2307/1913974>, the test of Breusch and Pagan (1979) <doi:10.2307/1911963> with and without the modification proposed by Koenker (1981) <doi:10.1016/0304-4076(81)90062-2>, the test of White (1980) <doi:10.2307/1912934>, the test and graphical Cook and Weisberg (1983) <doi:10.1093/biomet/70.1.1>, and the test of Li and Yao (2019) <doi:10.1016/j.ecosta.2018.01.001>. Homoskedasticity refers to the assumption of constant variance that is imposed on the model errors (disturbances); heteroskedasticity is the violation of this assumption.
RdMacros: Rdpack
Depends: R (>= 3.5.0)
Imports: stats (>= 3.5.0), utils (>= 3.5.0), Rdpack (>= 0.11.0), tibble (>= 2.1.3), broom (>= 0.5.3), magrittr (>= 1.5.0), pracma (>= 2.2.5), gmp (>= 0.5.13), Rmpfr (>= 0.7.2), matrixcalc (>= 1.0.3), lubridate (>= 1.7.4), lmtest (>= 0.9.37), car (>= 3.0.5), het.test (>= 0.1), tseries (>= 0.10.47)
Suggests:
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
URL: http://github.com/tjfarrar/skedastic
BugReports: http://github.com/tjfarrar/skedastic/issues
NeedsCompilation: no
Packaged: 2020-01-08 14:04:34 UTC; tom
Author: Thomas Farrar [aut, cre] (<https://orcid.org/0000-0003-0744-6972>), University of the Western Cape [cph]
Maintainer: Thomas Farrar <tjfarrar@alumni.uwaterloo.ca>
Repository: CRAN
Date/Publication: 2020-01-10 17:40:06 UTC

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New package MLMOI with initial version 0.1.1
Package: MLMOI
Type: Package
Title: Estimating Frequencies, Prevalence and Multiplicity of Infection
Version: 0.1.1
Authors@R: c(person("Meraj", "Hashemi", role = c("cre", "aut", "com"), email = "mhashemi@hs-mittweida.de"), person("Kristan", "Schneider", role = c("aut", "ths"), email = "kristan.schneider@hs-mittweida.de"))
Maintainer: Meraj Hashemi <mhashemi@hs-mittweida.de>
Description: The implemented methods reach out to scientists that seek to estimate multiplicity of infection (MOI) and lineage (allele) frequencies and prevalences at molecular markers using the maximum-likelihood method described in Schneider (2018) <doi:10.1371/journal.pone.0194148>, and Schneider and Escalante (2014) <doi:10.1371/journal.pone.0097899>. Users can import data from Excel files in various formats, and perform maximum-likelihood estimation on the imported data by the package's moimle() function.
Depends: R (>= 3.3.0)
Imports: XLConnect (>= 0.2-15), rJava (>= 0.9-10), Rdpack (>= 0.10-1), Rmpfr (>= 0.7-1),
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2020-01-08 11:35:01 UTC; Meraj
Author: Meraj Hashemi [cre, aut, com], Kristan Schneider [aut, ths]
Repository: CRAN
Date/Publication: 2020-01-10 17:30:02 UTC

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New package ldaPrototype with initial version 0.1.1
Package: ldaPrototype
Type: Package
Title: Prototype of Multiple Latent Dirichlet Allocation Runs
Version: 0.1.1
Date: 2020-01-08
Authors@R: person("Jonas", "Rieger", email="jonas.rieger@tu-dortmund.de", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0007-4478"))
Description: Determine a Prototype from a number of runs of Latent Dirichlet Allocation (LDA) measuring its similarities with S-CLOP: A procedure to select the LDA run with highest mean pairwise similarity, which is measured by S-CLOP (Similarity of multiple sets by Clustering with Local Pruning), to all other runs. LDA runs are specified by its assignments leading to estimators for distribution parameters. Repeated runs lead to different results, which we encounter by choosing the most representative LDA run as prototype.
URL: https://github.com/JonasRieger/ldaPrototype, https://doi.org/10.5281/zenodo.3597978
BugReports: https://github.com/JonasRieger/ldaPrototype/issues
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: checkmate (>= 1.8.5), colorspace (>= 1.4-1), data.table (>= 1.11.2), dendextend, fs (>= 1.2.0), lda (>= 1.4.2), progress (>= 1.1.1), stats, utils
Suggests: batchtools (>= 0.9.11), future, parallelMap, RColorBrewer (>= 1.1-2), testthat, tosca
RoxygenNote: 7.0.2
LazyData: true
NeedsCompilation: no
Packaged: 2020-01-08 16:29:17 UTC; rieger
Author: Jonas Rieger [aut, cre] (<https://orcid.org/0000-0002-0007-4478>)
Maintainer: Jonas Rieger <jonas.rieger@tu-dortmund.de>
Repository: CRAN
Date/Publication: 2020-01-10 17:40:09 UTC

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New package dmdScheme with initial version 1.0.0
Package: dmdScheme
Title: Domain Specific MetaData Scheme
Description: Forms the core for developing own domain specific metadata schemes. It contains the basic functionality needed for all metadata schemes based on the 'dmdScheme'. See R.M. Krug and O.L. Petchey (2019) <DOI:10.5281/zenodo.3581970>.
Version: 1.0.0
Date: 2019-12-17
Authors@R: c(person(given = "Rainer M.", family = "Krug", role = c("aut", "cre"), email = "Rainer.Krug@uzh.ch", comment = c(ORCID = "0000-0002-7490-0066")), person(given = "Owen L.", family = "Petchey", role = "ctb", email = "Owen.Petchey@uzh.ch", comment = c(ORCID = "0000-0002-7724-1633")))
URL: https://exp-micro-ecol-hub.github.io/dmdScheme/, https://github.com/Exp-Micro-Ecol-Hub/dmdScheme
BugReports: https://github.com/rkrug/dmdScheme/issues
Depends: R (>= 3.5.0)
Imports: tools, methods, utils, magrittr (>= 1.5), dplyr (>= 0.1.8), tibble (>= 2.1.1), readxl (>= 1.2.0), xml2, rlang (>= 0.3.1), rmarkdown, knitr, digest (>= 0.6), openxlsx, writexl, rappdirs, yaml
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
StagedInstall: true
RoxygenNote: 6.1.1
Suggests: covr (>= 3.2.1), testthat (>= 2.0.1), here (>= 0.1), kableExtra (>= 0.9.0), shiny
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-08 10:11:18 UTC; rainerkrug
Author: Rainer M. Krug [aut, cre] (<https://orcid.org/0000-0002-7490-0066>), Owen L. Petchey [ctb] (<https://orcid.org/0000-0002-7724-1633>)
Maintainer: Rainer M. Krug <Rainer.Krug@uzh.ch>
Repository: CRAN
Date/Publication: 2020-01-10 17:20:03 UTC

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New package PopGenome with initial version 2.7.2
Package: PopGenome
Type: Package
Title: An Efficient Swiss Army Knife for Population Genomic Analyses
Version: 2.7.2
Date: 2019-12-30
Authors@R: c( person("Bastian", "Pfeifer", role = c("aut", "cre"), email = "bastianxpfeifer@gmail.com"), person("Ulrich", "Wittelsbuerger", role = "ctb"), person("Heng", "Li", role = "ctb"), person("Bob", "Handsaker", role = "ctb") )
Depends: R (>= 2.14.2), ff
Imports: methods
Suggests: parallel, bigmemory, BASIX, WhopGenome, BlockFeST
Description: Provides efficient tools for population genomics data analysis, able to process individual loci, large sets of loci, or whole genomes. PopGenome <DOI:10.1093/molbev/msu136> not only implements a wide range of population genetics statistics, but also facilitates the easy implementation of new algorithms by other researchers. PopGenome is optimized for speed via the seamless integration of C code.
License: GPL-3
LazyLoad: yes
Copyright: inst/COPYRIGHTS
SystemRequirements: zlib headers and library.
Repository: CRAN
NeedsCompilation: yes
Packaged: 2020-01-10 09:15:58 UTC; bastian
Author: Bastian Pfeifer [aut, cre], Ulrich Wittelsbuerger [ctb], Heng Li [ctb], Bob Handsaker [ctb]
Maintainer: Bastian Pfeifer <bastianxpfeifer@gmail.com>
Date/Publication: 2020-01-10 12:40:03 UTC

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New package varTestnlme with initial version 0.1.0
Package: varTestnlme
Type: Package
Title: Variance Components Testing for Linear and Nonlinear Mixed Effects Models
Version: 0.1.0
Authors@R: c( person("Charlotte","Baey", ,"charlotte.baey@univ-lille.fr", role = c("aut", "cre"), comment = c(ORCID= "0000-0002-1413-1058") ), person("Estelle","Kuhn", ,"estelle.kuhn@inra.fr", role = c("aut")) )
URL: http://github.com/baeyc/varTestnlme/
BugReports: http://github.com/baeyc/varTestnlme/issues
Maintainer: Charlotte Baey <charlotte.baey@univ-lille.fr>
Description: An implementation of the Likelihood ratio Test (LRT) for testing that, in a (non)linear mixed effects model, the variances of a subset of the random effects are equal to zero. There is no restriction on the subset of variances that can be tested: for example, it is possible to test that all the variances are equal to zero. Note that the implemented test is asymptotic. This package should be used on model fits from packages 'nlme', 'lmer', and 'saemix'. Charlotte Baey, Paul-Henry Cournède and Estelle Kuhn (2019) <doi:10.1016/j.csda.2019.01.014>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: mvtnorm, alabama, Matrix, merDeriv, matrixcalc, anocva, corpcor, quadprog, lme4, nlme, saemix, msm, foreach, methods, doParallel, parallel
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-07 10:45:08 UTC; charlotte
Author: Charlotte Baey [aut, cre] (<https://orcid.org/0000-0002-1413-1058>), Estelle Kuhn [aut]
Repository: CRAN
Date/Publication: 2020-01-10 11:30:02 UTC

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Thu, 09 Jan 2020

New package raustats with initial version 0.15.0
Package: raustats
Type: Package
Title: Access Data and Statistics from the ABS and RBA Websites
Description: Functions for downloading Australian economic statistics from the Australian Bureau of Statistics (ABS) (see <https://www.abs.gov.au/>) and Reserve Bank of Australia (RBA) (see <https://www.rba.gov.au/>) websites.
Version: 0.15.0
Date: 2019-12-20
Authors@R: c( person("David", "Mitchell", email = "david.pk.mitchell@gmail.com", role = c("aut", "cre")) )
Maintainer: David Mitchell <david.pk.mitchell@gmail.com>
URL: https://github.com/mitcda/raustats
License: GPL-3
Depends: R (>= 3.3.0), readxl
Imports: stats, dplyr, httr, jsonlite, rvest, tidyr, xml2, lubridate
Suggests: repo, knitr, rmarkdown, testthat, ggplot2
LazyData: TRUE
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Encoding: UTF-8
Packaged: 2019-12-22 10:42:36 UTC; david
Author: David Mitchell [aut, cre]
Repository: CRAN
Date/Publication: 2020-01-09 18:10:02 UTC

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New package mbsts with initial version 1.0
Package: mbsts
Type: Package
Title: Multivariate Bayesian Structural Time Series
Version: 1.0
Author: Jinwen Qiu <qjwsnow_ctw@hotmail.com>
Maintainer: Jinwen Qiu <qjwsnow_ctw@hotmail.com>
Description: Multivariate time series regression using dynamic linear models fit by MCMC. See Qiu, Jammalamadaka and Ning (2018) <http://www.jmlr.org/papers/volume19/18-009/18-009.pdf>.
License: LGPL-2.1
NeedsCompilation: no
Depends: pscl, MASS, KFAS, MCMCpack, Matrix, R(>= 3.5)
Repository: CRAN
Date: 2020-01-07
Packaged: 2020-01-08 03:05:45 UTC; william
Date/Publication: 2020-01-09 18:10:05 UTC

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New package riceidconverter with initial version 1.0.5
Package: riceidconverter
Type: Package
Title: Convert Biological ID from RAP or MSU to SYMBOL for Oryza Sativa
Version: 1.0.5
Author: Xiang LI
Maintainer: Xiang LI <ynaulx@gmail.com>
Description: Convert one biological ID to another of rice (Oryza sativa). Rice(Oryza sativa) has more than one form gene ID for the genome. The two main gene ID for rice genome are the RAP (The Rice Annotation Project, <https://rapdb.dna.affrc.go.jp/>, and the MSU(The Rice Genome Annotation Project, <http://rice.plantbiology.msu.edu/>. All RAP rice gene IDs are of the form Os##g####### as explained on the website <https://rapdb.dna.affrc.go.jp/>. All MSU rice gene IDs are of the form LOC_Os##g##### as explained on the website <http://rice.plantbiology.msu.edu/analyses_nomenclature.shtml>. All SYMBOL rice gene IDs are the unique name on the NCBI(National Center for Biotechnology Information, <https://www.ncbi.nlm.nih.gov/>. The TRANSCRIPTID, is the transcript id of rice, are of the form Os##t#######. The researchers usually need to converter between various IDs. Such as converter RAP to SYMBOLS for function searching on NCBI. There are a lot of websites with the function for converting RAP to MSU or MSU to RA, such as 'ID Converter' <https://rapdb.dna.affrc.go.jp/tools/converter>. But it is difficult to convert super multiple IDs on these websites. The package can convert all IDs between the three IDs (RAP, MSU and SYMBOL) regardless of the number.
Depends: R (>= 3.5.0)
Imports: dplyr
License: Artistic-2.0
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-08 00:47:12 UTC; xiang
Repository: CRAN
Date/Publication: 2020-01-09 17:50:02 UTC

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New package PenIC with initial version 1.0.0
Package: PenIC
Type: Package
Version: 1.0.0
Title: Semiparametric Regression Analysis of Interval-Censored Data using Penalized Splines
Authors@R: c(person("Yan", "Liu", email = "yanliuresearch@gmail.com", role = c("aut","cre")), person("Minggen", "Lu", role = "aut"))
Maintainer: Yan Liu <yanliuresearch@gmail.com>
Description: Currently incorporate the generalized odds-rate model (a type of linear transformation model) for interval-censored data based on penalized monotonic B-Spline. More methods under other semiparametric models such as cure model or additive model will be included in future versions. For more details see Lu, M., Liu, Y., Li, C. and Sun, J. (2019) <arXiv:1912.11703>.
Depends: R (>= 3.3.0)
License: GPL (>= 2)
Imports: stats, numDeriv, splines, Matrix, MASS
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2020-01-07 21:41:37 UTC; yliu23
Author: Yan Liu [aut, cre], Minggen Lu [aut]
Repository: CRAN
Date/Publication: 2020-01-09 16:40:07 UTC

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New package mudata2 with initial version 1.1.0
Package: mudata2
Title: Interchange Tools for Multi-Parameter Spatiotemporal Data
Version: 1.1.0
Authors@R: person("Dewey", "Dunnington", email = "dewey@fishandwhistle.net", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9415-4582") )
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>
Description: Formatting and structuring multi-parameter spatiotemporal data is often a time-consuming task. This package offers functions and data structures designed to easily organize and visualize these data for applications in geology, paleolimnology, dendrochronology, and paleoclimate. See Dunnington and Spooner (2018) <doi:10.1139/facets-2017-0026>.
Imports: ggplot2, dplyr (>= 0.7), jsonlite (>= 1.2), tibble, magrittr, stringr, readr, tidyr, lubridate, rlang, tidyselect, withr, glue, fs
Depends: R (>= 3.2.0)
Suggests: testthat (>= 2.1.0), RSQLite, dbplyr, sf (>= 0.5.5), covr, hms, knitr, rmarkdown
License: GPL-2
URL: https://paleolimbot.github.io/mudata2, https://github.com/paleolimbot/mudata2
BugReports: https://github.com/paleolimbot/mudata2/issues
LazyData: true
RoxygenNote: 7.0.1
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-08 15:21:10 UTC; dewey
Author: Dewey Dunnington [aut, cre] (<https://orcid.org/0000-0002-9415-4582>)
Repository: CRAN
Date/Publication: 2020-01-09 16:50:02 UTC

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New package mcp with initial version 0.2.0
Package: mcp
Title: Regression with Multiple Change Points
Version: 0.2.0
Date: 2020-01-02
URL: http://lindeloev.github.io/mcp/, https://github.com/lindeloev/mcp
BugReports: https://github.com/lindeloev/mcp/issues
Authors@R: person(given = "Jonas Kristoffer", family = "Lindeløv", role = c("aut", "cre"), email = "jonas@lindeloev.dk", comment = c(ORCID = "0000-0003-4565-0595"))
Description: Flexible and informed regression with Multiple Change Points (MCP). 'mcp' can infer change points in means, variances, autocorrelation structure, and any combination of these, as well as the parameters of the segments in between. All parameters are estimated with uncertainty and prediction intervals are supported - also near the change points. 'mcp' supports hypothesis testing via Savage-Dickey density ratio, posterior contrasts, and cross-validation. 'mcp' provides a generalization of the approach described in Carlin, Gelfand, & Smith (1992) <doi:10.2307/2347570> and Stephens (1994) <doi:10.2307/2986119>.
License: GPL-2
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.0.2
Depends: R (>= 3.5.0)
Imports: parallel, future, future.apply, rjags (>= 4.9), coda (>= 0.19.3), loo (>= 2.1.0), bayesplot (>= 1.7.0), tidybayes (>= 1.1.0), dplyr (>= 0.8.3), magrittr (>= 1.5), tidyr (>= 1.0.0), tidyselect (>= 0.2.5), purrr (>= 0.3.3), tibble (>= 2.1.3), stringr (>= 1.4.0), ggplot2 (>= 3.2.1), patchwork (>= 1.0.0), methods, stats, rlang (>= 0.4.1)
Suggests: hexbin, testthat (>= 2.1.0), knitr, rmarkdown, covr
NeedsCompilation: no
Packaged: 2020-01-07 21:14:32 UTC; jonas
Author: Jonas Kristoffer Lindeløv [aut, cre] (<https://orcid.org/0000-0003-4565-0595>)
Maintainer: Jonas Kristoffer Lindeløv <jonas@lindeloev.dk>
Repository: CRAN
Date/Publication: 2020-01-09 16:30:02 UTC

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New package FABInference with initial version 0.1
Package: FABInference
Title: FAB p-Values and Confidence Intervals
Version: 0.1
Description: Frequentist assisted by Bayes (FAB) p-values and confidence interval construction. See Hoff (2019) <arXiv:1907.12589> "Smaller p-values via indirect information", Hoff and Yu (2019) <doi:10.1214/18-EJS1517> "Exact adaptive confidence intervals for linear regression coefficients", and Yu and Hoff (2018) <doi:10.1093/biomet/asy009> "Adaptive multigroup confidence intervals with constant coverage".
Date: 2019-12-27
Author: Peter Hoff
Maintainer: Peter Hoff <peter.hoff@duke.edu>
License: GPL-3
Imports: MASS
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-12-28 00:37:01 UTC; pdhoff
Repository: CRAN
Date/Publication: 2020-01-09 17:00:06 UTC

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New package codebook with initial version 0.8.2
Package: codebook
Title: Automatic Codebooks from Metadata Encoded in Dataset Attributes
Description: Easily automate the following tasks to describe data frames: Summarise the distributions, and labelled missings of variables graphically and using descriptive statistics. For surveys, compute and summarise reliabilities (internal consistencies, retest, multilevel) for psychological scales. Combine this information with metadata (such as item labels and labelled values) that is derived from R attributes. To do so, the package relies on 'rmarkdown' partials, so you can generate HTML, PDF, and Word documents. Codebooks are also available as tables (CSV, Excel, etc.) and in JSON-LD, so that search engines can find your data and index the metadata. The metadata are also available at your fingertips via RStudio Addins.
Version: 0.8.2
Authors@R: person("Ruben", "Arslan", email = "ruben.arslan@gmail.com", role = c("aut", "cre"))
Depends: R (>= 3.0.1)
Language: en_GB
URL: https://github.com/rubenarslan/codebook
BugReports: https://github.com/rubenarslan/codebook/issues
License: MIT + file LICENSE
Imports: stats, methods, graphics, utils, rmarkdown, forcats (>= 0.4.0), ggplot2 (>= 2.0.0), stringr, psych, likert, knitr, rlang, dplyr, tidyr, tidyselect, pander, skimr (>= 2.0.0), DT, jsonlite, future, haven (>= 2.0.0), tibble, purrr, htmltools, labeling, labelled, rio, shiny (>= 0.13), miniUI (>= 0.1.1), rstudioapi (>= 0.5), glue, lubridate, userfriendlyscience
Suggests: testthat, shinytest, lme4, roxygen2, renv, webshot
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-08 13:25:10 UTC; rubenarslan
Author: Ruben Arslan [aut, cre]
Maintainer: Ruben Arslan <ruben.arslan@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-09 16:20:07 UTC

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New package pcts with initial version 0.14-3
Package: pcts
Type: Package
Title: Periodically Correlated and Periodically Integrated Time Series
Description: Classes and methods for modelling and simulation of periodically correlated (PC) and periodically integrated time series. Compute theoretical periodic autocovariances and related properties of PC autoregressive moving average models. Some original methods including Boshnakov & Iqelan (2009) <doi:10.1111/j.1467-9892.2009.00617.x>, Boshnakov (1996) <doi:10.1111/j.1467-9892.1996.tb00281.x>.
Version: 0.14-3
Date: 2020-01-07
Author: Georgi N. Boshnakov
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>
Depends: R (>= 3.5.0), sarima
Imports: methods, Matrix, BB, PolynomF (>= 2.0-2), gbutils, zoo, ltsa, stats4, lagged (>= 0.2.2), mcompanion, Rdpack (>= 0.9), lubridate
Suggests: testthat, pear, fUnitRoots, partsm
RdMacros: Rdpack
LazyData: yes
URL: https://geobosh.github.io/pcts https://github.com/GeoBosh/pcts
BugReports: https://github.com/GeoBosh/pcts/issues
License: GPL (>= 2)
Collate: utils.R test1.r PeriodicCalc.R pcstat.R pc00smallutil.r pc02filters.r pc03simu.r acfsums.R pcls.R pcarma_model.R pcarma_acf.R generics.R autocovariances.R classCycle.R pcFilterClasses.R PeriodicClasses.R cyclic.R FittedPeriodicModels.R fitPM.R pcTest.R PeriodicVector.R sim.R optimcore.R
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-07 19:48:22 UTC; georgi
Repository: CRAN
Date/Publication: 2020-01-09 15:30:02 UTC

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New package bikedata with initial version 0.2.4
Package: bikedata
Title: Download and Aggregate Data from Public Hire Bicycle Systems
Version: 0.2.4
Authors@R: c( person("Mark", "Padgham", email = "mark.padgham@email.com", role = c("aut", "cre"), comment = c(ORCID = "https://orcid.org/0000-0003-2172-5265")), person("Richard", "Ellison", role = "aut"), person("Tom", "Buckley", role = "aut"), person("Ryszard", "Szymański", email = "ryszard.szymanski@outlook.com", role = "ctb"), person("Bea", "Hernández", role = "rev", comment = "Bea reviewed the package for ropensci, see https://github.com/ropensci/onboarding/issues/116"), person("Elaine", "McVey", role = "rev", comment = "Elaine reviewed the package for ropensci, see https://github.com/ropensci/onboarding/issues/116"), person(family = "SQLite Consortium", role = "ctb", comment = "Authors of included SQLite code"))
Description: Download and aggregate data from all public hire bicycle systems which provide open data, currently including 'Santander' Cycles in London, U.K.; from the U.S.A., 'Ford GoBike' in San Francisco CA, 'citibike' in New York City NY, 'Divvy' in Chicago IL, 'Capital Bikeshare' in Washington DC, 'Hubway' in Boston MA, 'Metro' in Los Angeles LA, 'Indego' in Philadelphia PA, and 'Nice Ride' in Minnesota; 'Bixi' from Montreal, Canada; and 'mibici' from Guadalajara, Mexico.
License: GPL-3
Depends: R (>= 3.0)
Imports: DBI, httr, lubridate, magrittr, methods, Rcpp, readxl, RSQLite, reshape2, tibble, xml2
Suggests: dodgr, knitr, rmarkdown, roxygen2, testthat, covr
LinkingTo: BH, Rcpp
VignetteBuilder: knitr
SystemRequirements: C++11
NeedsCompilation: yes
URL: https://docs.ropensci.org/bikedata, https://github.com/ropensci/bikedata
BugReports: https://github.com/ropensci/bikedata/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.1
X-schema.org-applicationCategory: Data Access
X-schema.org-keywords: bicycle-hire-systems, bike-hire-systems, bike-hire, bicycle-hire, database, bike-data
X-schema.org-isPartOf: https://ropensci.org
Packaged: 2020-01-08 12:34:28 UTC; markus
Author: Mark Padgham [aut, cre] (<https://orcid.org/0000-0003-2172-5265>), Richard Ellison [aut], Tom Buckley [aut], Ryszard Szymański [ctb], Bea Hernández [rev] (Bea reviewed the package for ropensci, see https://github.com/ropensci/onboarding/issues/116), Elaine McVey [rev] (Elaine reviewed the package for ropensci, see https://github.com/ropensci/onboarding/issues/116), SQLite Consortium [ctb] (Authors of included SQLite code)
Maintainer: Mark Padgham <mark.padgham@email.com>
Repository: CRAN
Date/Publication: 2020-01-09 14:40:06 UTC

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New package fasstr with initial version 0.3.1
Package: fasstr
Title: Analyze, Summarize, and Visualize Daily Streamflow Data
Version: 0.3.1
Authors@R: c(person("Jon", "Goetz", email = "jon.goetz@gov.bc.ca", role = c("aut", "cre")), person("Carl James", "Schwarz", email = "cschwarz.stat.sfu.ca@gmail.com", role = "aut"), person("Robin", "Pike", email = "robin.g.pike@gov.bc.ca", role = "ctb"), person("Province of British Columbia", role = "cph"))
Description: The Flow Analysis Summary Statistics Tool for R, 'fasstr', provides various functions to clean and screen daily stream discharge data; calculate and visualize various summary statistics and metrics; and compute annual trending (using 'zyp' package methods <https://CRAN.R-project.org/package=zyp>) and volume frequency analyses (using methods similar to HEC-SSP (2019) <https://www.hec.usace.army.mil/software/hec-ssp/>). It features useful function arguments for filtering of and handling dates, customizing data and metrics, and the ability to pull daily data directly from the Water Survey of Canada hydrometric database (<https://collaboration.cmc.ec.gc.ca/cmc/hydrometrics/www/>).
Depends: R (>= 3.2.0)
License: Apache License 2.0
URL: https://github.com/bcgov/fasstr, https://www2.gov.bc.ca/gov/content/environment/air-land-water/water
BugReports: https://github.com/bcgov/fasstr/issues
Encoding: UTF-8
Imports: dplyr (>= 0.8.1), e1071 (>= 1.7.0.1), fitdistrplus (>= 1.0.14), ggplot2 (>= 3.1.0), grDevices, lubridate (>= 1.7.4), PearsonDS (>= 1.1), plyr (>= 1.8.4), purrr (>= 0.3.2), RcppRoll (>= 0.3.0), scales (>= 1.0.0), tidyhydat (>= 0.4.0), tidyr (>= 0.8.3), openxlsx (>= 4.1.0), zyp (>= 0.10.1.1)
Suggests: knitr, rmarkdown, testthat
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-08 23:07:20 UTC; JGOETZ
Author: Jon Goetz [aut, cre], Carl James Schwarz [aut], Robin Pike [ctb], Province of British Columbia [cph]
Maintainer: Jon Goetz <jon.goetz@gov.bc.ca>
Repository: CRAN
Date/Publication: 2020-01-09 12:40:02 UTC

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New package RFmerge with initial version 0.1-6
Package: RFmerge
Type: Package
Title: Merging of Satellite Datasets with Ground Observations using Random Forests
Version: 0.1-6
Author: Mauricio Zambrano-Bigiarini [aut, cre, cph] (<https://orcid.org/0000-0002-9536-643X>), Oscar M. Baez-Villanueva [aut, cph], Juan Giraldo-Osorio [ctb]
Authors@R: c(person("Mauricio Zambrano-Bigiarini", email = "mzb.devel@gmail.com", role=c("aut", "cre", "cph"), comment=c(ORCID = "0000-0002-9536-643X")), person("Oscar M. Baez-Villanueva", email = "obaezvil@th-koeln.de", role=c("aut", "cph")), person("Juan Giraldo-Osorio", email = "j.giraldoo@javeriana.edu.co", role=c("ctb")) )
Maintainer: Mauricio Zambrano-Bigiarini <mzb.devel@gmail.com>
Description: S3 implementation of the Random Forest MErging Procedure (RF-MEP), which combines two or more satellite-based datasets (e.g., precipitation products, topography) with ground observations to produce a new dataset with improved spatio-temporal distribution of the target field. In particular, this package was developed to merge different Satellite-based Rainfall Estimates (SREs) with measurements from rain gauges, in order to obtain a new precipitation dataset where the time series in the rain gauges are used to correct different types of errors present in the SREs. However, this package might be used to merge other hydrological/environmental satellite fields with point observations. For details, see Baez-Villanueva et al. (2020) <doi:10.1016/j.rse.2019.111606>. Bugs / comments / questions / collaboration of any kind are very welcomed.
License: GPL (>= 3)
Depends: R (>= 3.5.0)
Imports: raster, sp, sf, randomForest, zoo, parallel, methods, stats, utils, pbapply
Suggests: knitr, rmarkdown, rgdal
VignetteBuilder: knitr
URL: https://github.com/hzambran/RFmerge
MailingList: https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
BugReports: https://github.com/hzambran/RFmerge/issues
LazyLoad: yes
NeedsCompilation: no
Repository: CRAN
Packaged: 2020-01-08 00:21:08 UTC; hzambran
Date/Publication: 2020-01-09 11:10:02 UTC

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New package echelon with initial version 0.1.0
Package: echelon
Type: Package
Title: The Echelon Analysis and the Detection of Spatial Clusters using Echelon Scan Method
Version: 0.1.0
Author: Fumio Ishioka
Maintainer: Fumio Ishioka <fishioka@okayama-u.ac.jp>
Description: Functions for the echelon analysis developed proposed by Myers et al. (1997) <doi:10.1023/A:1018518327329>, and the detection of spatial clusters using echelon scan method proposed by Kurihara (2003) <doi:10.20551/jscswabun.15.2_171>.
License: GPL-3
Depends: R (>= 3.3.0)
Suggests: sf, spData
NeedsCompilation: no
Packaged: 2020-01-08 06:51:01 UTC; fishi
Repository: CRAN
Date/Publication: 2020-01-09 11:30:02 UTC

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New package cbq with initial version 0.1.0.0
Package: cbq
Title: Conditional Binary Quantile Models
Version: 0.1.0.0
Author: Xiao Lu
Maintainer: Xiao LU <xiao.lu.research@gmail.com>
Description: Estimates conditional binary quantile models developed by Lu (2019) <doi:10.1017/pan.2019.29>. The estimation procedure is implemented based on Markov chain Monte Carlo methods.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Biarch: true
Depends: R (>= 3.4.0)
Imports: methods, Formula, Rcpp (>= 0.12.0), rstan (>= 2.18.1)
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
SystemRequirements: GNU make
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-12-23 06:51:29 UTC; xiaolu
Repository: CRAN
Date/Publication: 2020-01-09 11:20:02 UTC

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New package vectools with initial version 0.1.1
Package: vectools
Title: Supplementary Vector-Related Tools
Version: 0.1.1
Date: 2020-01-08
License: GPL (>= 2)
Maintainer: Abby Spurdle <spurdle.a@gmail.com>
Author: Abby Spurdle
URL: https://sites.google.com/site/spurdlea/r
Description: Supports formatted nested/partitioned matrices, formatted object arrays and similar formatted data.frame(s), via coercion. These objects can be printed with plain text mark up, including their partitions and submatrices. Also, includes an SQL-like select function, grouped head functions and combined head and tail functions.
Imports: methods
Suggests: intoo, Matrix, barsurf
NeedsCompilation: no
Packaged: 2020-01-07 17:39:45 UTC; spurdle
Repository: CRAN
Date/Publication: 2020-01-09 10:10:02 UTC

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New package shinyloadtest with initial version 1.0.1
Package: shinyloadtest
Type: Package
Title: Load Test Shiny Applications
Version: 1.0.1
Authors@R: c( person("Alan", "Dipert", role = c("aut", "cre"), email = "alan@rstudio.com"), person("Barret", "Schloerke", role = c("aut"), email = "barret@rstudio.com"), person("Barbara", "Borges", role = c("aut")), person("RStudio", role = c("cph", "fnd")) )
Description: Assesses the number of concurrent users 'shiny' applications are capable of supporting, and for directing application changes in order to support a higher number of users. Provides facilities for recording 'shiny' application sessions, playing recorded sessions against a target server at load, and analyzing the resulting metrics.
License: GPL-3
Depends: R (>= 2.10)
Encoding: UTF-8
LazyData: true
URL: https://rstudio.github.io/shinyloadtest/, https://github.com/rstudio/shinyloadtest
BugReports: https://github.com/rstudio/shinyloadtest/issues
Collate: 'enum.R' 'data.R' 'analysis.R' 'detect.R' 'auth.R' 'make_report.R' 'plotting.R' 'shiny-recorder.R' 'url.R' 'util.R' 'util-pipe.R'
Imports: R6, curl, dplyr (>= 0.8.0.1), getPass, ggplot2, glue, gtable, htmltools, httpuv (>= 1.5.2), jsonlite, lubridate, magrittr, progress, readr, rlang (>= 0.1.2), rmarkdown, scales, stringr, tibble, svglite, websocket (>= 1.0.0), xml2
RoxygenNote: 7.0.2
Suggests: testthat, usethis
SystemRequirements: pandoc (>= 2.2) - http://pandoc.org
NeedsCompilation: no
Packaged: 2020-01-07 16:19:00 UTC; alan
Author: Alan Dipert [aut, cre], Barret Schloerke [aut], Barbara Borges [aut], RStudio [cph, fnd]
Maintainer: Alan Dipert <alan@rstudio.com>
Repository: CRAN
Date/Publication: 2020-01-09 10:20:02 UTC

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New package bggum with initial version 1.0.1
Package: bggum
Title: Bayesian Estimation of Generalized Graded Unfolding Model Parameters
Version: 1.0.1
Date: 2019-12-27
Authors@R: c(person(given = "JBrandon", family = "Duck-Mayr", email = "j.duckmayr@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-2231-1294")), person(given = "Jacob", family = "Montgomery", role = c("aut")), person(given = "Patrick", family = "Silva", role = "ctb"), person(given = "Luwei", family = "Ying", role = "ctb") )
Description: Provides a Metropolis-coupled Markov chain Monte Carlo sampler, post-processing and parameter estimation functions, and plotting utilities for the generalized graded unfolding model of Roberts, Donoghue, and Laughlin (2000) <doi:10.1177/01466216000241001>.
URL: https://github.com/duckmayr/bggum
BugReports: https://github.com/duckmayr/bggum/issues
Depends: R (>= 3.5.0)
Imports: stats, graphics, Rcpp (>= 0.12.14)
LinkingTo: Rcpp, RcppDist
License: GPL (>= 2)
Suggests: devtools, testthat, covr, knitr, rmarkdown, dplyr, tidyr
Collate: 'bggum-package.R' 'RcppExports.R' 'ggumProbability.R' 'tune_proposals.R' 'tune_temps.R' 'ggumMCMC.R' 'ggumMC3.R' 'ggum_simulation.R' 'color_palettes.R' 'irf.R' 'icc.R' 'summary.R' 'post_process.R'
Encoding: UTF-8
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-08 03:13:21 UTC; jb
Author: JBrandon Duck-Mayr [aut, cre] (<https://orcid.org/0000-0002-2231-1294>), Jacob Montgomery [aut], Patrick Silva [ctb], Luwei Ying [ctb]
Maintainer: JBrandon Duck-Mayr <j.duckmayr@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-09 10:50:03 UTC

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New package xnet with initial version 0.1.10
Package: xnet
Type: Package
Title: Two-Step Kernel Ridge Regression for Network Predictions
Version: 0.1.10
Authors@R: c(person("Joris","Meys", email = "Joris.Meys@UGent.be", role = c("cre","aut")), person("Michiel", "Stock", email = "Michiel.Stock@UGent.be", role = "aut"))
Description: Fit a two-step kernel ridge regression model for predicting edges in networks, and carry out cross-validation using shortcuts for swift and accurate performance assessment (Stock et al, 2018 <doi:10.1093/bib/bby095> ).
Date: 2019-12-09
BugReports: https://github.com/CenterForStatistics-UGent/xnet/issues
URL: https://github.com/CenterForStatistics-UGent/xnet
Depends: R(>= 3.4.0)
Imports: methods, utils, graphics, stats, grDevices
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.0
Suggests: testthat, knitr, rmarkdown, ChemmineR, covr, fmcsR
VignetteBuilder: knitr
Collate: 'Class_linearFilter.R' 'all_generics.R' 'Class_permtest.R' 'Class_tskrr.R' 'Class_tskrrHeterogeneous.R' 'Class_tskrrHomogeneous.R' 'Class_tskrrImpute.R' 'Class_tskrrImputeHeterogeneous.R' 'Class_tskrrImputeHomogeneous.R' 'Class_tskrrTune.R' 'Class_tskrrTuneHeterogeneous.R' 'Class_tskrrTuneHomogeneous.R' 'as_tuned.R' 'create_grid.R' 'data_drugtarget.R' 'data_proteinInteraction.R' 'dim.R' 'eigen2hat.R' 'fitted.R' 'get_loo_fun.R' 'getlooInternal.R' 'getters_linearFilter.R' 'getters_permtest.R' 'getters_tskrr.R' 'getters_tskrrImpute.R' 'getters_tskrrTune.R' 'hat.R' 'impute_tskrr.R' 'impute_tskrr.fit.R' 'internal_helpers.R' 'is_symmetric.R' 'labels.R' 'linear_filter.R' 'loo.R' 'looInternal.R' 'loss.R' 'loss_functions.R' 'match_labels.R' 'permtest.R' 'plot.tskrr.R' 'plot_grid.R' 'predict.R' 'prepare_lambdas.R' 'residuals.R' 'test_input.R' 'test_symmetry.R' 'tskrr.R' 'tskrr.fit.R' 'tune.R' 'update.R' 'valid_dimensions.R' 'valid_labels.R' 'weights.R' 'xnet-package.R'
NeedsCompilation: no
Packaged: 2019-12-20 14:29:47 UTC; Joris
Author: Joris Meys [cre, aut], Michiel Stock [aut]
Maintainer: Joris Meys <Joris.Meys@UGent.be>
Repository: CRAN
Date/Publication: 2020-01-09 09:30:02 UTC

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Wed, 08 Jan 2020

New package psych with initial version 1.9.12.31
Package: psych
Version: 1.9.12.31
Date: 2019-12-31
Title: Procedures for Psychological, Psychometric, and Personality Research
Authors@R: person("William", "Revelle", role =c("aut","cre"), email="revelle@northwestern.edu", comment=c(ORCID = "0000-0003-4880-9610") )
Description: A general purpose toolbox for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Functions for simulating and testing particular item and test structures are included. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometric theory as well as publications in personality research. For more information, see the <https://personality-project.org/r> web page.
License: GPL (>= 2)
Imports: mnormt,parallel,stats,graphics,grDevices,methods,lattice,nlme
Suggests: psychTools, GPArotation, lavaan, sem, lme4,Rcsdp, graph, Rgraphviz
LazyData: yes
ByteCompile: TRUE
URL: https://personality-project.org/r/psych https://personality-project.org/r/psych-manual.pdf
NeedsCompilation: no
Packaged: 2020-01-06 20:42:21 UTC; WR
Author: William Revelle [aut, cre] (<https://orcid.org/0000-0003-4880-9610>)
Maintainer: William Revelle <revelle@northwestern.edu>
Repository: CRAN
Date/Publication: 2020-01-08 23:00:27 UTC

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New package publipha with initial version 0.1.0
Package: publipha
Title: Bayesian Meta-Analysis with Publications Bias and P-Hacking
Version: 0.1.0
Authors@R: c( person("Jonas", "Moss", , "jonas.gjertsen@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-6876-6964") ), person("Trustees of Columbia University", role = "cph"))
Description: Tools for Bayesian estimation of meta-analysis models that account for publications bias or p-hacking. For publication bias, this package implements a variant of the p-value based selection model of Hedges (1992) <doi:10.1214/ss/1177011364> with discrete selection probabilities. It also implements the mixture of truncated normals model for p-hacking described in Moss and De Bin (2019) <arXiv:1911.12445>.
License: GPL-3
Depends: methods, R (>= 3.5.0), Rcpp (>= 0.12.19)
Imports: rstan (>= 2.18.1), rstantools (>= 1.5.1), loo, truncnorm
LinkingTo: BH (>= 1.72.0-2), Rcpp (>= 0.12.19), RcppEigen (>= 0.3.3.4.0), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
SystemRequirements: GNU make
RoxygenNote: 7.0.2
Suggests: testthat (>= 2.1.0), covr, knitr, rmarkdown, metafor, qtl, spelling
Collate: 'data-anderson2010.R' 'data-baskerville2012.R' 'data-cuddy2018.R' 'data-dang2018.R' 'data-motyl2017.R' 'densities-helpers.R' 'densities-mpsnorm.R' 'densities-phnorm.R' 'densities-psnorm.R' 'densities-snorm.R' 'ma.R' 'generics.R' 'publipha-package.R' 'stanmodels.R' 'tools.R' 'utility.R' 'zzz.R'
Language: en-US
Packaged: 2020-01-07 13:39:23 UTC; jonas
Author: Jonas Moss [aut, cre] (<https://orcid.org/0000-0002-6876-6964>), Trustees of Columbia University [cph]
Maintainer: Jonas Moss <jonas.gjertsen@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-08 17:20:02 UTC

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New package mlr3viz with initial version 0.1.0
Package: mlr3viz
Title: Visualizations for 'mlr3'
Version: 0.1.0
Authors@R: person(given = "Michel", family = "Lang", role = c("cre", "aut"), email = "michellang@gmail.com", comment = c(ORCID = "0000-0001-9754-0393"))
Description: Provides visualizations for 'mlr3' objects such as tasks, predictions, resample results or benchmark results via the autoplot() generic of 'ggplot2'. The returned 'ggplot' objects are intended to provide sensible defaults, yet can easily be customized to create camera-ready figures. Visualizations include barplots, boxplots, histograms, ROC curves, and Precision-Recall curves.
License: LGPL-3
URL: https://mlr3viz.mlr-org.com, https://github.com/mlr-org/mlr3viz
BugReports: https://github.com/mlr-org/mlr3viz/issues
Depends: R (>= 3.1.0)
Imports: checkmate, data.table, ggplot2, mlr3misc, utils
Suggests: GGally, lgr, mlr3 (>= 0.1.6), mlr3filters, mlr3proba, precrec, rpart, survival, testthat
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
RoxygenNote: 7.0.2
Packaged: 2020-01-07 13:04:47 UTC; michel
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>)
Maintainer: Michel Lang <michellang@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-08 17:10:02 UTC

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New package jfa with initial version 0.1.0
Package: jfa
Title: Bayesian and Classical Audit Sampling
Version: 0.1.0
Authors@R: person(given = "Koen", family = "Derks", role = c("aut", "cre"), email = "k.derks@nyenrode.nl")
Description: Implements the audit sampling workflow as discussed in Derks et al. (2019) <doi:10.31234/osf.io/9f6ub>. The package makes it easy for an auditor to plan an audit sample, sample from the population, and evaluating that sample using various confidence bounds according to the International Standards on Auditing. Furthermore, the package implements Bayesian equivalents of these methods.
Language: en-US
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
Suggests: testthat, knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-01-07 13:00:46 UTC; derksk
Author: Koen Derks [aut, cre]
Maintainer: Koen Derks <k.derks@nyenrode.nl>
Repository: CRAN
Date/Publication: 2020-01-08 17:10:10 UTC

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New package wrProteo with initial version 1.0.0
Package: wrProteo
Version: 1.0.0
Title: Proteomics Data Analysis Functions
Authors@R: person("Wolfgang", "Raffelsberger", email = "w.raffelsberger@unistra.fr", role = c("aut", "cre"))
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@unistra.fr>
Description: Data analysis of proteomics experiments by mass spectrometry is supported by this collection of functions mostly dedicated to the analysis of (bottom-up) quantitative (XIC) data. Fasta-formatted proteomes (eg from Uniprot) can be read with automatic parsing and multiple annotation types (like species origin, abbreviated gene names, etc) extracted. Quantitative proteomics measurements frequently contain multiple NA values, due to physical absence of given peptides in some samples, limitations in sensitivity or other reasons. The functions provided here help to inspect graphically the data to investigate the nature of NA-values via their respective replicate measurements and to help/confirm the choice of NA-replacement by low random values. Dedicated filtering and statistical testing using the framework of package 'limma' can be run, enhanced by multiple rounds of NA-replacements to provide robustness towards rare stochastic events. Multi-species samples, as frequently used in benchmark-tests, can be run with special options consideration separating the data into sub-groups during normalization and testing. Subsequently, ROC curves can be constructed to compare multiple analysis approaches.
Depends: R (>= 3.1.0)
Imports: graphics, limma, stats, wrMisc
Suggests: fdrtool, grDevices, MASS, RColorBrewer, ROTS, readxl
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-01-07 09:42:08 UTC; wraff
Repository: CRAN
Date/Publication: 2020-01-08 16:10:02 UTC

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New package syslognet with initial version 0.1.2.1
Package: syslognet
Type: Package
Title: Send Log Messages to Remote 'syslog' Server
Version: 0.1.2.1
Authors@R: c( person("Panagiotis", "Cheilaris", role = c("aut", "cre"), email = "philaris@gmail.com") )
Author: Panagiotis Cheilaris [aut, cre]
Maintainer: Panagiotis Cheilaris <philaris@gmail.com>
Description: Send 'syslog' protocol messages to a remote 'syslog' server specified by host name and TCP network port.
URL: https://github.com/philaris/syslognet
BugReports: https://github.com/philaris/syslognet/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Imports: utils
NeedsCompilation: no
Packaged: 2020-01-07 10:08:27 UTC; philaris
Repository: CRAN
Date/Publication: 2020-01-08 16:10:05 UTC

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New package r2sundials with initial version 5.0.0-4
Package: r2sundials
Type: Package
Title: Wrapper for 'SUNDIALS' Solving ODE and Sensitivity Problem
Version: 5.0.0-4
Date: 2020-01-06
Authors@R: c( person("Serguei", "Sokol", role=c("cre", "aut"), email="sokol@insa-toulouse.fr"), person("Carol S.", "Woodward", role="ctb"), person("Daniel R.", "Reynolds", role="ctb"), person("Alan C.", "Hindmarsh", role="ctb"), person("David J.", "Gardner", role="ctb"), person("Cody J.", "Balos", role="ctb"), person("Radu", "Serban", role="ctb"), person("Scott D.", "Cohen", role="ctb"), person("Peter N.", "Brown", role="ctb"), person("George", "Byrne", role="ctb"), person("Allan G.", "Taylor", role="ctb"), person("Steven L.", "Lee", role="ctb"), person("Keith E.", "Grant", role="ctb"), person("Aaron", "Collier", role="ctb"), person("Lawrence E.", "Banks", role="ctb"), person("Steve", "Smith", role="ctb"), person("Cosmin", "Petra", role="ctb"), person("Slaven", "Peles", role="ctb"), person("John", "Loffeld", role="ctb"), person("Dan", "Shumaker", role="ctb"), person("Ulrike", "Yang", role="ctb"), person("James", "Almgren-Bell", role="ctb"), person("Shelby L.", "Lockhart", role="ctb"), person("Hilari C.", "Tiedeman", role="ctb"), person("Ting", "Yan", role="ctb"), person("Jean M.", "Sexton", role="ctb"), person("Chris", "White", role="ctb"), person("Lawrence Livermore National Security", role="cph"), person("Southern Methodist University", role="cph"), person("INRAE", role="cph") )
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>
Description: Wrapper for widely used 'SUNDIALS' software (SUite of Nonlinear and DIfferential/ALgebraic Equation Solvers) and more precisely to its 'CVODES' solver. It is aiming to solve ordinary differential equations (ODE) and optionally pending forward sensitivity problem. The wrapper is made 'R' friendly by allowing to pass custom parameters to user's callback functions. Such functions can be both written in 'R' and in 'C++' ('RcppArmadillo' flavor). In case of 'C++', performance is greatly improved so this option is highly advisable when performance matters. If provided, Jacobian matrix can be calculated either in dense or sparse format. In the latter case 'rmumps' package is used to solve corresponding linear systems. Root finding and pending event management are optional and can be specified as 'R' or 'C++' functions too. This makes them a very flexible tool for controlling the ODE system during the time course simulation. 'SUNDIALS' library was published in Hindmarsh et al. (2005) <doi:10.1145/1089014.1089020>.
BugReports: https://github.com/sgsokol/r2sundials/issues
Depends: R (>= 3.0.2), rmumps (>= 5.2.1-6)
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppArmadillo, rmumps (>= 5.2.1-6)
Suggests: RcppXPtrUtils, slam, RUnit, deSolve, RcppArmadillo
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
Biarch: FALSE
Packaged: 2020-01-06 09:16:51 UTC; sokol
Author: Serguei Sokol [cre, aut], Carol S. Woodward [ctb], Daniel R. Reynolds [ctb], Alan C. Hindmarsh [ctb], David J. Gardner [ctb], Cody J. Balos [ctb], Radu Serban [ctb], Scott D. Cohen [ctb], Peter N. Brown [ctb], George Byrne [ctb], Allan G. Taylor [ctb], Steven L. Lee [ctb], Keith E. Grant [ctb], Aaron Collier [ctb], Lawrence E. Banks [ctb], Steve Smith [ctb], Cosmin Petra [ctb], Slaven Peles [ctb], John Loffeld [ctb], Dan Shumaker [ctb], Ulrike Yang [ctb], James Almgren-Bell [ctb], Shelby L. Lockhart [ctb], Hilari C. Tiedeman [ctb], Ting Yan [ctb], Jean M. Sexton [ctb], Chris White [ctb], Lawrence Livermore National Security [cph], Southern Methodist University [cph], INRAE [cph]
Repository: CRAN
Date/Publication: 2020-01-08 16:30:02 UTC

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New package ipfr with initial version 1.0.1
Package: ipfr
Title: List Balancing for Reweighting and Population Synthesis
Version: 1.0.1
Authors@R: c( person( "Kyle", "Ward", email = "kyleward084@gmail.com", role = c("aut", "cre", "cph") ), person("Greg", "Macfarlane", email = "gregmacfarlane@byu.edu", role = c("ctb")))
Description: Performs iterative proportional updating given a seed table and an arbitrary number of marginal distributions. This is commonly used in population synthesis, survey raking, matrix rebalancing, and other applications. For example, a household survey may be weighted to match the known distribution of households by size from the census. An origin/ destination trip matrix might be balanced to match traffic counts. The approach used by this package is based on a paper from Arizona State University (Ye, Xin, et. al. (2009) <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.537.723&rep=rep1&type=pdf>). Some enhancements have been made to their work including primary and secondary target balance/importance, general marginal agreement, and weight restriction.
License: Apache License (== 2.0)
URL: https://github.com/dkyleward/ipfr
BugReports: https://github.com/dkyleward/ipfr/issues
Depends: R (>= 3.2.0)
Imports: dplyr (>= 0.7.3), ggplot2 (>= 2.2.1), magrittr (>= 1.5), tidyr (>= 0.5.1), mlr (>= 2.11)
LazyData: true
Suggests: knitr, rmarkdown, testthat (>= 2.1.0), covr
VignetteBuilder: knitr
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-07 15:06:26 UTC; kyle
Author: Kyle Ward [aut, cre, cph], Greg Macfarlane [ctb]
Maintainer: Kyle Ward <kyleward084@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-08 16:30:08 UTC

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New package diversityForest with initial version 0.1.0
Package: diversityForest
Type: Package
Title: Diversity Forests
Version: 0.1.0
Date: 2020-01-07
Author: Roman Hornung [aut, cre], Marvin N. Wright [ctb, cph]
Maintainer: Roman Hornung <hornung@ibe.med.uni-muenchen.de>
Description: Implements diversity forests as described in an upcoming paper by the author of the package. This package is a fork of the R package 'ranger' (main author: Marvin N. Wright) that implements random forests using an efficient C++ implementation. More precisely, 'diversityForest' was written by modifying the code of 'ranger', version 0.11.0. Therefore, details on further functionalities of the code that are not presented in the help pages of 'diversityForest' are found in the help pages of 'ranger' (version 0.11.0). The code in the example sections of the 'diversityForest' manual can be used as a template for all basic application scenarios with respect to classification using univariate, binary splitting. Some function arguments adopted from the 'ranger' package are not be useable with diversity forests (for the current package version).
SystemRequirements: C++11
Encoding: UTF-8
License: GPL-3
Imports: Rcpp (>= 0.11.2), Matrix
LinkingTo: Rcpp, RcppEigen
Depends: R (>= 3.1)
Suggests: survival, testthat
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2020-01-07 08:43:34 UTC; hornung
Repository: CRAN
Date/Publication: 2020-01-08 16:20:09 UTC

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New package akc with initial version 0.9.0
Package: akc
Title: Automatic Knowledge Classification
Version: 0.9.0
Authors@R: person(given = "Tian-Yuan", family = "Huang", role = c("aut", "cre"), email = "huang.tian-yuan@qq.com", comment = c(ORCID = "0000-0002-3591-4203"))
Description: A tidy framework for automatic knowledge classification and visualization. Currently, the core functionality of the framework is mainly supported by modularity-based clustering (community detection) in keyword co-occurrence network, and focuses on co-word analysis of bibliometric research. However, the designed functions in 'akc' are general, and could be extended to solve other tasks in text mining as well.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.0)
Imports: igraph, dplyr, ggplot2, stringr, ggraph (>= 1.0.2), tidygraph (>= 1.1.2), ggforce, textstem, tibble, tidytext, widyr, rlang, magrittr, data.table (>= 1.12.6)
URL: https://github.com/hope-data-science/akc
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-07 11:30:09 UTC; Hope
Author: Tian-Yuan Huang [aut, cre] (<https://orcid.org/0000-0002-3591-4203>)
Maintainer: Tian-Yuan Huang <huang.tian-yuan@qq.com>
Repository: CRAN
Date/Publication: 2020-01-08 16:30:11 UTC

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New package sbtools with initial version 1.1.9
Package: sbtools
Title: USGS ScienceBase Tools
Maintainer: David Blodgett <dblodgett@usgs.gov>
Version: 1.1.9
Authors@R: c(person("David", "Blodgett", role=c("cre"), email = "dblodgett@usgs.gov"), person("Tim", "Kern", role=c("aut"), email = "kernt@usgs.gov"), person("Luke", "Winslow", role = c("aut"), email = "lwinslow@usgs.gov"), person("Scott", "Chamberlain", role = c("aut"), email = "scott@ropensci.org"), person("Alison", "Appling", role = c("aut"), email = "aappling@usgs.gov"), person("Jordan", "Read", role = c("aut"), email = "jread@usgs.gov"))
Description: Tools for interacting with U.S. Geological Survey ScienceBase <https://www.sciencebase.gov> interfaces. ScienceBase is a data cataloging and collaborative data management platform. Functions included for querying ScienceBase, and creating and fetching datasets.
Imports: jsonlite, curl, httr (>= 1.0.0), stringr, methods
Suggests: testthat, xml2, sf, sp
License: CC0
URL: https://github.com/USGS-R/sbtools
BugReports: https://github.com/USGS-R/sbtools/issues
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-01-07 14:28:34 UTC; dblodgett
Author: David Blodgett [cre], Tim Kern [aut], Luke Winslow [aut], Scott Chamberlain [aut], Alison Appling [aut], Jordan Read [aut]
Repository: CRAN
Date/Publication: 2020-01-08 09:10:03 UTC

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New package qgg with initial version 1.0.2
Package: qgg
Type: Package
Title: Statistical Tools for Quantitative Genetic Analyses
Version: 1.0.2
Date: 2020-01-06
Authors@R: c(person("Peter", "Soerensen", email = "peter.sorensen@r-qgg.org", role = c("aut", "cre")), person("Palle", "Duun Rohde", email = "palle.d.rohde@mbg.au.dk", role = "aut"), person("Izel", "Fourie Soerensen", email = "izel.sorensen@gmail.com", role = "aut"))
Maintainer: Peter Soerensen <peter.sorensen@r-qgg.org>
Description: Provides an infrastructure for efficient processing of large-scale genetic and phenotypic data including core functions for: 1) fitting linear mixed models, 2) constructing marker-based genomic relationship matrices, 3) estimating genetic parameters (heritability and correlation), 4) performing genomic prediction and genetic risk profiling, and 5) single or multi-marker association analyses. Rohde et al. (2019) <doi:10.1101/503631>.
License: GPL-3
Encoding: UTF-8
Imports: data.table, parallel, statmod, stats, MCMCpack, MASS
RoxygenNote: 6.1.1
URL: https://github.com/psoerensen/qgg
BugReports: https://github.com/psoerensen/qgg/issues
NeedsCompilation: yes
Packaged: 2020-01-07 07:45:10 UTC; Peter
Author: Peter Soerensen [aut, cre], Palle Duun Rohde [aut], Izel Fourie Soerensen [aut]
Repository: CRAN
Date/Publication: 2020-01-08 09:00:03 UTC

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Tue, 07 Jan 2020

New package brinton with initial version 0.1.3
Package: brinton
Type: Package
Version: 0.1.3
Title: A Graphical EDA Tool
Description: An automated graphical exploratory data analysis (EDA) tool that introduces: a.) wideplot() graphics for exploring the structure of a dataset through a grid of variables and graphic types. b.) longplot() graphics, which present the entire catalog of available graphics for representing a particular variable using a grid of graphic types and variations on these types. c.) plotup() function, which presents a particular graphic for a specific variable of a dataset. The plotup() function also makes it possible to obtain the code used to generate the graphic, meaning that the user can adjust its properties as needed.
Authors@R: c(person(given = "Pere", family = "Millán-Martínez", email="info@sciencegraph.org", role = c("aut", "cre")), person(given = "Ramon", family = "Oller Piqué", email="ramon.oller@uvic.cat", role = "ctb"))
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: ggplot2, gridExtra, rmarkdown
Imports: grid, pander, lubridate, tibble, grDevices, sm, RColorBrewer, forcats, stats, qpdf
RoxygenNote: 7.0.2
Suggests: knitr
VignetteBuilder: knitr
SystemRequirements: Pandoc (>= 1.12.3), web browser
NeedsCompilation: no
Packaged: 2020-01-04 05:07:29 UTC; 34601
Author: Pere Millán-Martínez [aut, cre], Ramon Oller Piqué [ctb]
Maintainer: Pere Millán-Martínez <info@sciencegraph.org>
Repository: CRAN
Date/Publication: 2020-01-08 00:50:08 UTC

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New package PCRedux with initial version 1.0-4
Package: PCRedux
Type: Package
Title: Quantitative Polymerase Chain Reaction (qPCR) Data Mining and Machine Learning Toolkit
Version: 1.0-4
Date: 2019-12-22
Authors@R: c(person("Stefan", "Roediger", email = "stefan.roediger@b-tu.de", comment = c(ORCID = "0000-0002-1441-6512"), role = c("cre", "aut")), person("Michal", "Burdukiewicz", email = "michalburdukiewicz@gmail.com", comment = c(ORCID = "0000-0001-8926-582X"), role = c("aut")), person("Andrej-Nikolai", "Spiess", email = "a.spiess@uke.de", role = c("aut")), person("Konstantin A.", "Blagodatskikh", email = "k.blag@yandex.ru", role = c("aut")), person("Dominik", "Rafacz", email = "dominikrafacz@gmail.com", role = c("ctb")))
Description: Extracts features from amplification curve data of quantitative Polymerase Chain Reactions (qPCR) (Pabinger S. et al. (2014) <doi:10.1016/j.bdq.2014.08.002>) for machine learning purposes. Helper functions prepare the amplification curve data for processing as functional data (e.g., Hausdorff distance) or enable the plotting of amplification curve classes (negative, ambiguous, positive). The hookreg() and hookregNL() functions (Burdukiewicz M. et al. (2018) <doi:10.1016/j.bdq.2018.08.001>) can be used to predict amplification curves with an hook effect-like curvature. The pcrfit_single() function can be used to extract features from an amplification curve.
License: MIT + file LICENSE
LazyLoad: yes
LazyData: yes
URL: https://CRAN.R-project.org/package=PCRedux
BugReports: https://github.com/PCRuniversum/PCRedux/issues
Depends: R (>= 3.5.0)
Imports: bcp, changepoint, chipPCR, ecp, fda.usc, MBmca, pbapply, pracma, qpcR, robustbase, shiny, stats, utils, zoo
Suggests: DT, FFTrees, knitr, RDML, randomForest, readxl, rmarkdown, spelling, testthat, xtable, future, listenv
NeedsCompilation: no
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.0.2
Packaged: 2020-01-07 10:51:15 UTC; tux
Author: Stefan Roediger [cre, aut] (<https://orcid.org/0000-0002-1441-6512>), Michal Burdukiewicz [aut] (<https://orcid.org/0000-0001-8926-582X>), Andrej-Nikolai Spiess [aut], Konstantin A. Blagodatskikh [aut], Dominik Rafacz [ctb]
Maintainer: Stefan Roediger <stefan.roediger@b-tu.de>
Repository: CRAN
Date/Publication: 2020-01-07 22:40:02 UTC

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New package LRQMM with initial version 1.2.0
Package: LRQMM
Type: Package
Title: Fitting Linear Quantile Regression Mixed Models
Version: 1.2.0
Author: Sayyed Reza Alavian[aut,cre] Majid Sarmad[ths] Mehdi Jabbari Nooghabi[ths] Hani Rezaee[ctb] Saeed Zerehdaran[ctb] Ferdowsi University Of Mashhad [cph]
Maintainer: Sayyed Reza Alavian <s.rezaalavian@mail.um.ac.ir>
Description: Fit a quantile regression mixed model using a sparse implementation of the Frisch-Newton interior-point algorithm as described in Portnoy and Koenker (1977, Statistical Science) <https://www.jstor.org/stable/2246217>.
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: GeneticsPed, SparseM, quantreg, Matrix, kinship2, MCMCglmm, sparsesvd, corpcor
Suggests: MASS
NeedsCompilation: no
Packaged: 2020-01-07 12:36:38 UTC; REZA
Repository: CRAN
Date/Publication: 2020-01-07 22:40:06 UTC

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New package GPB with initial version 1.2
Package: GPB
Version: 1.2
Date: 2020-01-01
Title: Generalized Poisson Binomial Distribution
Authors@R: c(person("Yili", "Hong", role = c("aut", "cre"),email = "yilihong@vt.edu"),person("Man", "Zhang", role = c("aut", "ctb")),person("", "R Core Team", role = c("aut", "cph")))
Author: Yili Hong [aut, cre], Man Zhang [aut, ctb], R Core Team [aut, cph]
Maintainer: Yili Hong <yilihong@vt.edu>
Description: Functions that compute the distribution functions for the Generalized Poisson Binomial distribution as described in Zhang et al. (2018)<doi: 10.1080/00949655.2018.1440294>, which provides the cdf, pmf, quantile function, and random number generation for the distribution. The C code for fast Fourier transformation (FFT) is written by R Core Team (2019)<https://www.R-project.org/>, which implements the FFT algorithm in Singleton (1969) <doi: 10.1109/TAU.1969.1162042>.
License: GPL-2
Depends: stats
NeedsCompilation: yes
Packaged: 2020-01-01 22:04:01 UTC; yilih
Repository: CRAN
Date/Publication: 2020-01-07 21:50:08 UTC

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New package conjurer with initial version 1.0.0
Package: conjurer
Type: Package
Title: A Parametric Method for Generating Synthetic Data
Version: 1.0.0
Date: 2020-01-07
Authors@R: person("Sidharth", "Macherla", email = "msidharthrasik@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4825-2026"))
Description: Builds synthetic data applicable across multiple domains. This package also provides flexibility to control data distribution to make it relevant to many industry examples.
License: MIT + file LICENSE
URL: https://github.com/SidharthMacherla/conjurer
BugReports: https://github.com/SidharthMacherla/conjurer/issues
Encoding: UTF-8
LazyData: FALSE
RoxygenNote: 7.0.2.9000
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-07 04:50:49 UTC; sidharth.macherla
Author: Sidharth Macherla [aut, cre] (<https://orcid.org/0000-0002-4825-2026>)
Maintainer: Sidharth Macherla <msidharthrasik@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-07 19:50:02 UTC

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New package transplantr with initial version 0.1.0
Package: transplantr
Type: Package
Title: Audit and Research Functions for Transplantation
Version: 0.1.0
Authors@R: person("John", "Asher", email = "john.asher@outlook.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8735-6453"))
Description: A set of vectorised functions to calculate medical equations used in transplantation, focused mainly on transplantation of abdominal organs. These functions include donor and recipient risk indices as used by NHS Blood & Transplant, OPTN/UNOS and Eurotransplant, tools for quantifying HLA mismatches, functions for calculating estimated glomerular filtration rate (eGFR), a function to calculate the APRI score used in initial screening of suitability to receive a transplant from a hepatitis C seropositive donor and some biochemical unit converter functions. All functions are designed to work with either US or international units. References for the equations are provided in the vignettes and function documentation.
URL: https://transplantr.txtools.net, https://github.com/johnasher/transplantr
BugReports: https://github.com/johnasher/transplantr/issues
Depends: R (>= 3.1.0)
Suggests: dplyr, stringr, knitr, rmarkdown, testthat, spelling
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Language: en-GB
NeedsCompilation: no
Packaged: 2020-01-07 07:35:53 UTC; john
Author: John Asher [aut, cre] (<https://orcid.org/0000-0001-8735-6453>)
Maintainer: John Asher <john.asher@outlook.com>
Repository: CRAN
Date/Publication: 2020-01-07 17:30:02 UTC

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New package ppmHR with initial version 1.0
Package: ppmHR
Type: Package
Title: Privacy-Protecting Hazard Ratio Estimation in Distributed Data Networks
Version: 1.0
Date: 2020-01-06
Author: Di Shu <shudi1991@gmail.com>, Sengwee Toh <darren_toh@harvardpilgrim.org>
Maintainer: Di Shu <shudi1991@gmail.com>
Description: An implementation of the one-step privacy-protecting method for estimating the overall and site-specific hazard ratios using inverse probability weighted Cox models in distributed data network studies, as proposed by Shu, Yoshida, Fireman, and Toh (2019) <doi: 10.1177/0962280219869742>. This method only requires sharing of summary-level riskset tables instead of individual-level data. Both the conventional inverse probability weights and the stabilized weights are implemented.
License: GPL (>= 2)
Imports: nleqslv, stats
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-06 19:09:32 UTC; dishu
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2020-01-07 17:20:02 UTC

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New package PROJ with initial version 0.1.0
Package: PROJ
Title: Generic Coordinate System Transformations Using 'PROJ'
Version: 0.1.0
Authors@R: c(person(given = "Michael D.", family = "Sumner", role = c("aut", "cre"), email = "mdsumner@gmail.com", comment = c(ORCID = "0000-0002-2471-7511")), person("Jeroen", "Ooms", role = c("ctb"), comment = "provided PROJ library support on Windows, and assistance with Windows configuration"), person("Simon", "Urbanek", role = c("cph", "ctb"), comment = "wrote original code versions for PROJ version 6"))
Description: A wrapper around the generic coordinate transformation software 'PROJ' that transforms geospatial coordinates from one coordinate reference system ('CRS') to another. This includes cartographic projections as well as geodetic transformations. Version 6.0.0 or higher is required. The intention is for this package to be used by user-packages such as 'reproj', and that the older 'PROJ.4' and version 5 pathways be provided by the legacy package. The 'PROJ' library is available from <https://proj.org/>.
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
SystemRequirements: PROJ (>= 6.0.0)
Suggests: testthat (>= 2.1.0), covr, spelling, knitr, rmarkdown
URL: https://github.com/hypertidy/PROJ
BugReports: https://github.com/hypertidy/PROJ/issues
RoxygenNote: 7.0.2
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-07 06:56:06 UTC; mdsumner
Author: Michael D. Sumner [aut, cre] (<https://orcid.org/0000-0002-2471-7511>), Jeroen Ooms [ctb] (provided PROJ library support on Windows, and assistance with Windows configuration), Simon Urbanek [cph, ctb] (wrote original code versions for PROJ version 6)
Maintainer: Michael D. Sumner <mdsumner@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-07 17:00:13 UTC

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Wed, 01 Jan 2020

New package DCCA with initial version 0.1.1
Package: DCCA
Version: 0.1.1
Date: 2019-12-18
Title: Detrended Fluctuation and Detrended Cross-Correlation Analysis
Authors@R: c(person("Taiane Schaedler","Prass", email = "taianeprass@gmail.com", role = c("aut","cre"), comment = c(ORCID="0000-0003-3136-909X")), person("Guilherme","Pumi", email = "guilherme.pumi@ufrgs.br", role = c("aut"), comment = c(ORCID="0000-0002-6256-3170")))
Depends: R (>= 3.5.0)
Imports: checkmate
Suggests: lattice
Description: A collection of functions to perform Detrended Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA). This package implements the results presented in Prass, T.S. and Pumi, G. (2019). "On the behavior of the DFA and DCCA in trend-stationary processes" <arXiv:1910.10589>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2019-12-19 00:11:21 UTC; Taiane
Author: Taiane Schaedler Prass [aut, cre] (<https://orcid.org/0000-0003-3136-909X>), Guilherme Pumi [aut] (<https://orcid.org/0000-0002-6256-3170>)
Maintainer: Taiane Schaedler Prass <taianeprass@gmail.com>
Repository: CRAN
Date/Publication: 2020-01-01 15:10:02 UTC

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Mon, 30 Dec 2019

New package slurmR with initial version 0.3-0
Package: slurmR
Title: A Lightweight Wrapper for 'Slurm'
Version: 0.3-0
Authors@R: c( person("George", "Vega Yon", email = "g.vegayon@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3171-0844")), person("Paul", "Marjoram", email = "pmarjora@usc.edu", role = c("ctb", "ths"), comment = c(ORCID = "0000-0003-0824-7449")), person("National Cancer Institute (NCI)", role = "fnd", comment = "Grant Number 5P01CA196569-02"), person("Michael", "Schubert", role = "rev", comment = c(what = "JOSS reviewer", ORCID = "0000-0002-6862-5221")), person("Michel", "Lang", role = "rev", comment = c(what = "JOSS reviewer", ORCID = "0000-0001-9754-0393")) )
Description: 'Slurm', Simple Linux Utility for Resource Management <https://slurm.schedmd.com/>, is a popular 'Linux' based software used to schedule jobs in 'HPC' (High Performance Computing) clusters. This R package provides a specialized lightweight wrapper of 'Slurm' with a syntax similar to that found in the 'parallel' R package. The package also includes a method for creating socket cluster objects spanning multiple nodes that can be used with the 'parallel' package.
Depends: R (>= 3.3.0), parallel
License: MIT + file LICENSE
BugReports: https://github.com/USCbiostats/slurmR/issues
URL: https://github.com/USCbiostats/slurmR, https://slurm.schedmd.com/
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: rslurm, knitr, rmarkdown, covr, tinytest
Imports: utils
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2019-12-19 22:37:54 UTC; george
Author: George Vega Yon [aut, cre] (<https://orcid.org/0000-0002-3171-0844>), Paul Marjoram [ctb, ths] (<https://orcid.org/0000-0003-0824-7449>), National Cancer Institute (NCI) [fnd] (Grant Number 5P01CA196569-02), Michael Schubert [rev] (JOSS reviewer, <https://orcid.org/0000-0002-6862-5221>), Michel Lang [rev] (JOSS reviewer, <https://orcid.org/0000-0001-9754-0393>)
Maintainer: George Vega Yon <g.vegayon@gmail.com>
Repository: CRAN
Date/Publication: 2019-12-31 02:00:02 UTC

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New package Quartet with initial version 1.0.3
Package: Quartet
Version: 1.0.3
Title: Comparison of Phylogenetic Trees Using Quartet and Bipartition Measures
Description: Calculates the number of four-taxon subtrees consistent with a pair of cladograms, calculating the symmetric quartet distance of Bandelt & Dress (1986), Reconstructing the shape of a tree from observed dissimilarity data, Advances in Applied Mathematics, 7, 309-343 <doi:10.1016/0196-8858(86)90038-2>, and using the tqDist algorithm of Sand et al. (2014), tqDist: a library for computing the quartet and triplet distances between binary or general trees, Bioinformatics, 30, 2079–2080 <doi:10.1093/bioinformatics/btu157> for pairs of bifurcating trees.
URL: https://github.com/ms609/Quartet
BugReports: https://github.com/ms609/Quartet/issues
Authors@R: c(person("Martin R.", 'Smith', email='martin.smith@durham.ac.uk', role=c("aut", "cre", "cph"), comment=c(ORCID = "0000-0001-5660-1727")), person('Andreas', 'Sand', role=c('ant')), person('Gerth', 'Stølting Brodal', role=c('ant')), person('Rolf', 'Fagerberg', role=c('ant')), person('Thomas', 'Mailund', role=c('ant')), person('Christian N. S.', 'Pedersen', email='cstorm@birc.au.dk', role=c('ant')), person('Jens', 'Johansen', role=c('ant')), person('Morten K.', 'Holt', role=c('ant')) )
Copyright: Incorporates code modified from tqDist <doi:10.1093/bioinformatics/btu157>.
License: GPL (>= 2)
Encoding: UTF-8
Language: en-GB
Depends: R (>= 3.4.0)
Imports: ape, memoise, Rdpack, Ternary (>= 1.0), TreeSearch (> 0.3.0)
Suggests: bookdown, knitr, phangorn, Rcpp, rmarkdown, testthat, usethis
SystemRequirements: C++11
RdMacros: Rdpack
LinkingTo: Rcpp
LazyData: true
ByteCompile: true
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-12-16 16:22:03 UTC; ms609
Author: Martin R. Smith [aut, cre, cph] (<https://orcid.org/0000-0001-5660-1727>), Andreas Sand [ant], Gerth Stølting Brodal [ant], Rolf Fagerberg [ant], Thomas Mailund [ant], Christian N. S. Pedersen [ant], Jens Johansen [ant], Morten K. Holt [ant]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>
Repository: CRAN
Date/Publication: 2019-12-30 17:30:02 UTC

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New package multilinguer with initial version 0.0.3
Package: multilinguer
Title: Gentle Language Installer for R User
Version: 0.0.3
Authors@R: person(given = "Chanyub", family = "Park", role = c("aut","cre"), email = "mrchypark@gmail.com", comment = c(ORCID = "0000-0001-6474-2570"))
Description: Provides install functions of other languages such as 'java', 'python' for windows and macos.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/mrchypark/multilinguer
BugReports: https://github.com/mrchypark/multilinguer/issues
RoxygenNote: 7.0.2
Imports: sys, fs, usethis, zip, askpass, xml2, rvest, rstudioapi
NeedsCompilation: no
Packaged: 2019-12-14 08:23:30 UTC; mrchypark
Author: Chanyub Park [aut, cre] (<https://orcid.org/0000-0001-6474-2570>)
Maintainer: Chanyub Park <mrchypark@gmail.com>
Repository: CRAN
Date/Publication: 2019-12-30 17:00:02 UTC

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New package sbw with initial version 1.0
Package: sbw
Type: Package
Version: 1.0
Date: 2019-12-06
Title: Stable Balancing Weights for Causal Inference and Estimation with Incomplete Outcome Data
Authors@R: c(person("Jose R.", "Zubizarreta", role = c("aut", "cre"), email = "zubizarreta@hcp.med.harvard.edu"), person("Yige", "Li", role = "aut", email = "yige_li@hcp.med.harvard.edu"), person("Amine", "Allouah", role = "ctb", email = "mallouah19@gsb.columbia.edu"), person("Noah", "Greifer", role = "ctb", email = "ngreifer@live.unc.edu"))
Maintainer: Jose R. Zubizarreta <zubizarreta@hcp.med.harvard.edu>
Depends: R (>= 3.2), Matrix, quadprog, slam
Imports: MASS, spatstat
Enhances: gurobi, Rcplex, Rmosek, pogs
License: GPL-2 | GPL-3
Description: Weights of minimum variance that approximately balance the empirical distribution of the observed covariates.
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2019-12-17 23:10:25 UTC; yige
Author: Jose R. Zubizarreta [aut, cre], Yige Li [aut], Amine Allouah [ctb], Noah Greifer [ctb]
Repository: CRAN
Date/Publication: 2019-12-30 15:20:02 UTC

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