CRANberries

Sun, 20 Oct 2019

New package cumulocityr with initial version 0.1.0
Package: cumulocityr
Type: Package
Title: Client for the 'Cumulocity' API
Version: 0.1.0
Authors@R: c( person("Dmitriy", "Bolotov", email = "dmitriy.bolotov@softwareag.com", role = c("aut", "cre")), person("Software AG", role = c("cph")))
Imports: httr, jsonlite
Suggests: testthat, knitr, rmarkdown, covr
Description: Access the 'Cumulocity' API and retrieve data on devices, measurements, and events. Documentation for the API can be found at <https://www.cumulocity.com/guides/reference/rest-implementation/>.
License: GPL-3
URL: https://softwareag.github.io/cumulocityr/, https://github.com/SoftwareAG/cumulocityr
BugReports: https://github.com/SoftwareAG/cumulocityr/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-16 22:31:16 UTC; dmitriy
Author: Dmitriy Bolotov [aut, cre], Software AG [cph]
Maintainer: Dmitriy Bolotov <dmitriy.bolotov@softwareag.com>
Repository: CRAN
Date/Publication: 2019-10-20 12:10:02 UTC

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New package RepaymentPlan with initial version 0.1.0
Package: RepaymentPlan
Type: Package
Title: Calculation of Mortgage Plan or Repayment Plan
Version: 0.1.0
Author: Gourav Kumar Vani <kumaragri.vani1@gmail.com>, Dr. Vivek Badhe <vivekbadhe.jbp@gmail.com>
Maintainer: Gourav Kumar Vani <kumaragri.vani1@gmail.com>
Imports: graphics
Description: The function RepaymentPlan() calculates repayment schedule for repayment/mortgage plans.
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-10-16 16:53:29 UTC; Dell
Repository: CRAN
Date/Publication: 2019-10-20 11:20:02 UTC

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New package lillies with initial version 0.2.4
Package: lillies
Title: Estimation of Life Years Lost
Version: 0.2.4
Authors@R: person(given = "Oleguer", family = "Plana-Ripoll", role = c("aut", "cre"), email = "opr@econ.au.dk", comment = c(ORCID = "0000-0002-6470-7465"))
Description: Estimation of life expectancy and Life Years Lost (LYL, or lillies for short) for a given population, for example those with a given disease or condition. In addition, the package can be used to compare estimates from different populations, or to estimate confidence intervals. Technical details of the method are available in Andersen (2017) <doi:10.1002/sim.7357>.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: ddpcr, dplyr, knitr, pracma, progress, rlang, survival, tidyr, utils
Suggests: ggplot2
NeedsCompilation: no
Packaged: 2019-10-16 21:03:47 UTC; au464894
Author: Oleguer Plana-Ripoll [aut, cre] (<https://orcid.org/0000-0002-6470-7465>)
Maintainer: Oleguer Plana-Ripoll <opr@econ.au.dk>
Repository: CRAN
Date/Publication: 2019-10-20 12:00:03 UTC

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New package GIFTr with initial version 0.1.0
Package: GIFTr
Type: Package
Title: GIFT Questions Format Generator from Dataframes
Version: 0.1.0
Author: Omar I. Elashkar
Maintainer: Omar I. Elashkar <omar.ibrahim@miuegypt.edu.eg>
Depends: R (>= 3.5.0)
Imports: stringr, glue
Description: A framework and functions to create 'MOODLE' quizzes. 'GIFTr' takes dataframe of questions of four types: multiple choices, numerical, true or false and short answer questions, and exports a text file formatted in 'MOODLE' GIFT format. You can prepare a spreadsheet in any software and import it into R to generate any number of questions with 'HTML', 'markdown' and 'LaTeX' support.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/omarelashkar/GIFTr
Suggests: knitr, rmarkdown, kableExtra,
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-16 17:33:13 UTC; xxxmar
Repository: CRAN
Date/Publication: 2019-10-20 11:30:05 UTC

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New package GetQuandlData with initial version 0.1.0
Package: GetQuandlData
Type: Package
Title: Fast and Cached Import of Data from 'Quandl' Using the 'json API'
Version: 0.1.0
Author: Marcelo S. Perlin
Maintainer: Marcelo S. Perlin <marceloperlin@gmail.com>
Description: Imports time series data from the 'Quandl' database <https://www.quandl.com>. The package uses the 'json api' at <https://www.quandl.com/tools/api>, local caching ('memoise' package) and the tidy format by default. Also allows queries of databases, allowing the user to see which time series are available for each database id. In short, it is an alternative to package 'Quandl', with faster data importation in the tidy/long format.
Imports: jsonlite, memoise, dplyr, purrr, utils, readr, scales, stringr
License: GPL-2
BugReports: https://github.com/msperlin/GetQuandlData/issues
URL: https://github.com/msperlin/GetQuandlData/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat, ggplot2, tidyverse
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-16 18:56:55 UTC; msperlin
Repository: CRAN
Date/Publication: 2019-10-20 11:30:02 UTC

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New package robin with initial version 0.99.0
Package: robin
Title: ROBustness in Network
Version: 0.99.0
Authors@R: c( person("Valeria", "Policastro", role=c("aut", "cre"), email="valeria.policastro@gmail.com"), person("Dario", "Righelli", role=c("aut"), email="dario.righelli@gmail.com"), person("Luisa", "Cutillo", role=c("aut"), email="l.cutillo@leeds.ac.uk"), person("Italia", "De Feis", role=c("aut"), email="i.defeis@na.iac.cnr.it"), person("Annamaria", "Carissimo", role=c("aut"), email="a.carissimo@na.iac.cnr.it"))
Maintainer: Valeria Policastro <valeria.policastro@gmail.com>
Description: Many community detection algorithms have been developed in network analysis. However, their applications leave unaddressed the statistical validation of the results, for this reason we developed ROBIN (ROBustness In Network), a useful method for the validation of community detection. It has a double aim, it studies the robustness of a single community detection algorithm and compares two community detection algorithms to understand which provides the best partition. Reference in Annamaria Carissimo, Luisa Cutillo, Italia De Feis (2018) <doi:10.1016/j.csda.2017.10.006>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/ValeriaPolicastro/robin
Depends: R (>= 3.5), igraph, gprege
Imports: ggplot2, networkD3, DescTools, fdatest, gridExtra, methods
VignetteBuilder: knitr
Suggests: devtools, cowplot, knitr, rmarkdown, testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2019-10-16 12:30:54 UTC; vpoli
Author: Valeria Policastro [aut, cre], Dario Righelli [aut], Luisa Cutillo [aut], Italia De Feis [aut], Annamaria Carissimo [aut]
Repository: CRAN
Date/Publication: 2019-10-20 09:40:02 UTC

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New package noctua with initial version 1.0.0
Package: noctua
Type: Package
Title: Connect to 'AWS Athena' using R 'AWS SDK' 'paws' ('DBI' Interface)
Version: 1.0.0
Authors@R: person("Dyfan", "Jones", email="dyfan.r.jones@gmail.com", role= c("aut", "cre"))
Description: Designed to be compatible with the 'R' package 'DBI' (Database Interface) when connecting to Amazon Web Service ('AWS') Athena <https://aws.amazon.com/athena/>. To do this the 'R' 'AWS' Software Development Kit ('SDK') 'paws' <https://github.com/paws-r/paws> is used as a driver.
Imports: DBI (>= 0.7), methods, paws, stats, utils
Suggests: arrow, data.table, dplyr, dbplyr, testthat
Depends: R (>= 3.2.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/DyfanJones/noctua
BugReports: https://github.com/DyfanJones/noctua/issues
Collate: 'noctua.R' 'Driver.R' 'Connection.R' 'DataTypes.R' 'Result.R' 'Table.R' 'athena_low_api.R' 'dplyr_integration.R' 'utils.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2019-10-16 14:03:21 UTC; lmar763
Author: Dyfan Jones [aut, cre]
Maintainer: Dyfan Jones <dyfan.r.jones@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-20 10:00:02 UTC

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New package ezcox with initial version 0.1.0
Type: Package
Package: ezcox
Title: Easily Process a Batch of Cox Models
Version: 0.1.0
Authors@R: person(given = "Shixiang", family = "Wang", role = c("aut", "cre"), email = "w_shixiang@163.com", comment = c(ORCID = "0000-0001-9855-7357"))
Maintainer: Shixiang Wang <w_shixiang@163.com>
Description: A tool to operate a batch of univariate or multivariate Cox models and return tidy result.
License: GPL-3
URL: https://github.com/ShixiangWang/ezcox
BugReports: https://github.com/ShixiangWang/ezcox/issues
Depends: R (>= 3.5)
Imports: dplyr (>= 0.8.3), magrittr (>= 1.5), purrr (>= 0.3.2), survival, rlang (>= 0.1.2)
Suggests: covr (>= 3.2.1), testthat (>= 2.1.0), roxygen2 (>= 6.1.1), knitr, rmarkdown
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-16 07:52:03 UTC; wsx
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>)
Repository: CRAN
Date/Publication: 2019-10-20 09:10:02 UTC

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New package binmapr with initial version 0.1.3
Package: binmapr
Type: Package
Title: Call Marker from Snp Data using Binmap
Description: The raw NGS (Next Generation Sequencing) variants called from GBS (Genotyping by Sequencing) / WES (Whole Exon Sequencing)/ WGS (Whole Genome Sequencing) may include many error sites. The 'binmapr' could fix the potential error sites and generate highly confident markers for downstream analysis, such as QTL (quantitative trait locus) mapping, genetic map construction. Davey, J.W. (2011) <doi:10.1038/nrg3012>.
Version: 0.1.3
Authors@R: c(person(given = "Zhougeng", family = "Xu", email = "xuzhougeng@163.com", role = c("aut", "cre")), person(given = "Guangwei", family = "Li", role = "aut"))
Maintainer: Zhougeng Xu <xuzhougeng@163.com>
License: Artistic-2.0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
URL: https://github.com/xuzhougeng/binmapr
BugReports: https://github.com/xuzhougeng/binmapr/issues
Depends: R (>= 3.5.0)
Imports: vcfR
Packaged: 2019-10-16 13:33:32 UTC; DELL
Author: Zhougeng Xu [aut, cre], Guangwei Li [aut]
Repository: CRAN
Date/Publication: 2019-10-20 09:50:02 UTC

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Fri, 18 Oct 2019

New package SourceSet with initial version 0.1.3
Package: SourceSet
Type: Package
Title: A Graphical Model Approach to Identify Primary Genes in Perturbed Biological Pathways
Version: 0.1.3
Date: 2019-10-17
Authors@R: c(person("Elisa", "Salviato", email = "elisa.salviato.88@gmail.com", role = c("aut", "cre")), person("Vera", "Djordjilovic", email = "vera.djordjilovic@medisin.uio.no", role = "aut"), person("Chiara","Romualdi",email="chiara.romualdi@unipd.it",role="aut"), person("Monica","Chiogna",email="monica@stat.unipd.it",role="aut"))
Maintainer: Elisa Salviato <elisa.salviato.88@gmail.com>
Description: The algorithm pursues the identification of the set of variables driving the differences in two different experimental conditions (i.e., the primary genes) within a graphical model context. It uses the idea of simultaneously looking for the differences between two multivariate normal distributions in all marginal and conditional distributions associated with a decomposable graph, which represents the pathway under exam. The implementation accommodates genomics specific issues (low sample size and multiple testing issues) and provides a number of functions offering numerical and visual summaries to help the user interpret the obtained results. In order to use the (optional) 'Cytoscape' functionalities, the suggested 'r2cytoscape' package must be installed from the 'GitHub' repository ('devtools::install_github('cytoscape/r2cytoscape')').
Depends: R (>= 2.10)
Imports: gRbase, progress, reshape2, graph, igraph, gtools, methods, plyr, scales
License: AGPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: networkD3, ggplot2, grDevices, Rgraphviz, knitr, rmarkdown, r2cytoscape, BiocStyle, Biobase, graphite, hgu95av2.db, ALL, mvtnorm, org.Hs.eg.db
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-17 09:07:27 UTC; esalviat
Author: Elisa Salviato [aut, cre], Vera Djordjilovic [aut], Chiara Romualdi [aut], Monica Chiogna [aut]
Repository: CRAN
Date/Publication: 2019-10-18 22:00:03 UTC

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New package simPATHy with initial version 0.3
Package: simPATHy
Type: Package
Title: A Method for Simulating Data from Perturbed Biological Pathways
Version: 0.3
Date: 2019-10-16
Authors@R: c(person("Elisa", "Salviato", email = "elisa.salviato.88@gmail.com", role = c("aut", "cre")), person("Vera", "Djordjilovic", email = "djordjilovic@stat.unipd.it", role = "aut"), person("Chiara","Romualdi",email="chiara.romualdi@unipd.it",role="aut"), person("Monica","Chiogna",email="monica@stat.unipd.it",role="aut"))
Description: Simulate data from a Gaussian graphical model or a Gaussian Bayesian network in two conditions. Given a covariance matrix of a reference condition simulate plausible disregulations.
Depends: R (>= 3.0)
Imports: mvtnorm, gRbase, graph, igraph, ggm, qpgraph, R.utils, htmlwidgets, shiny, shinydashboard ,grDevices, graphics
License: AGPL-3
LazyData: TRUE
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, clipper, topologyGSA
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-10-18 08:27:01 UTC; esalviat
Author: Elisa Salviato [aut, cre], Vera Djordjilovic [aut], Chiara Romualdi [aut], Monica Chiogna [aut]
Maintainer: Elisa Salviato <elisa.salviato.88@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-18 21:20:02 UTC

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New package NHMM with initial version 3.9
Package: NHMM
Type: Package
Title: Bayesian Non-Homogeneous Markov and Mixture Models for Multiple Time Series
Version: 3.9
Date: 2019-10-10
Author: Tracy Holsclaw
Acknowledgements: This work was supported by a grant from the U.S. Department of Energy, (through the Earth System Models (EaSM) program.( This package was developed under the direction of Padhraic Smyth at the Department of Computer Science and Statistics at the University of California, Irvine and in collaboration with Andrew Robertson and Arthur Greene of the International Research Institute for Climate and Society at The Earth Institute at Columbia University.
Maintainer: Tracy Holsclaw <iamrandom@iamrandom.com>
Description: Holsclaw, Greene, Robertson, and Smyth (2017) <doi:10.1214/16-AOAS1009>. Bayesian HMM and NHMM modeling for multiple time series. The emission distribution can be mixtures of Exponential, Gamma, Poisson, or Normal distributions, and zero inflation is possible.
License: GPL (>= 3)
Imports: Rcpp (>= 0.11.0)
LinkingTo: Rcpp
Depends: BayesLogit, msm, MCMCpack, MASS
URL: http://iamrandom.com/nhmm-package
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-10-18 16:37:13 UTC; iamrandom
Repository: CRAN
Date/Publication: 2019-10-18 21:20:15 UTC

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New package topicdoc with initial version 0.1.0
Type: Package
Package: topicdoc
Title: Topic-Specific Diagnostics for LDA and CTM Topic Models
Version: 0.1.0
Authors@R: person(given = "Doug", family = "Friedman", role = c("aut", "cre"), email = "doug.nhp@gmail.com")
Description: Calculates topic-specific diagnostics (e.g. mean token length, exclusivity) for Latent Dirichlet Allocation and Correlated Topic Models fit using the 'topicmodels' package. For more details, see Chapter 12 in Airoldi et al. (2014, ISBN:9781466504080), pp 262-272 Mimno et al. (2011, ISBN:9781937284114), and Bischof et al. (2014) <arXiv:1206.4631v1>.
License: MIT + file LICENSE
URL: https://github.com/doug-friedman/topicdoc
BugReports: https://github.com/doug-friedman/topicdoc/issues
Depends: R (>= 3.5.0)
Imports: slam, topicmodels
Suggests: knitr, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-15 21:20:39 UTC; Doug
Author: Doug Friedman [aut, cre]
Maintainer: Doug Friedman <doug.nhp@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-18 12:40:02 UTC

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New package ehelp with initial version 1.0
Package: ehelp
Title: Enhanced Help to Enable "Docstring"-Comments in Users Functions
Version: 1.0
Authors@R: person(given = "Marcelo", family = "Ponce", role = c("aut", "cre"), email = "mponce@scinet.utoronto.ca")
Author: Marcelo Ponce [aut, cre]
Maintainer: Marcelo Ponce <mponce@scinet.utoronto.ca>
Description: By overloading the R help() function, this package allows users to use "docstring" style comments within their own defined functions.
URL: https://github.com/mponce0/eHelp
BugReports: https://github.com/mponce0/eHelp/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.99.9001
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, crayon
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-16 00:06:27 UTC; marcelo
Repository: CRAN
Date/Publication: 2019-10-18 12:50:02 UTC

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New package bigparallelr with initial version 0.1.1
Package: bigparallelr
Title: Easy Parallel Tools
Version: 0.1.1
Date: 2019-10-15
Authors@R: person(given = "Florian", family = "Privé", role = c("aut", "cre"), email = "florian.prive.21@gmail.com")
Description: Utility functions for easy parallelism in R. Include some reexports from other packages, utility functions for splitting and parallelizing over blocks, and choosing and setting the number of cores used.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: bigassertr (>= 0.1.1), doParallel, flock, parallel, RhpcBLASctl
Depends: foreach
Suggests: testthat, covr
NeedsCompilation: no
Packaged: 2019-10-15 16:05:15 UTC; privef
Author: Florian Privé [aut, cre]
Maintainer: Florian Privé <florian.prive.21@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-18 12:00:02 UTC

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New package rlc with initial version 0.1.0
Package: rlc
Type: Package
Title: Create Interactive Linked Charts with Minimal Code
Version: 0.1.0
Date: 2019-10-11
Authors@R: c( person("Svetlana", "Ovchinnikova", role = c("aut", "cre"), email = "s.ovchinnikova@zmbh.uni-heidelberg.de"), person("Simon", "Anders", role = c("aut"), email = "sanders@fs.tum.de") )
Description: An easy-to-use tool to employ interactivity in every-day exploratory analysis. It contains a collection of most commonly used types of charts (such as scatter plots, line plots, heatmaps, bar charts), which can be linked to each other or to other interactive elements with just few lines of code.
License: GPL-3
Imports: httpuv, jsonlite, stringr, hwriter, jrc(>= 0.2.0), plyr, methods, stats
Suggests: tidyverse, RColorBrewer
NeedsCompilation: no
RoxygenNote: 6.1.1
Packaged: 2019-10-15 10:00:34 UTC; tyranchick
Author: Svetlana Ovchinnikova [aut, cre], Simon Anders [aut]
Maintainer: Svetlana Ovchinnikova <s.ovchinnikova@zmbh.uni-heidelberg.de>
Repository: CRAN
Date/Publication: 2019-10-18 09:40:02 UTC

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Thu, 17 Oct 2019

New package WaveletGARCH with initial version 0.1.0
Package: WaveletGARCH
Type: Package
Title: Fit the Wavelet-GARCH Model to Volatile Time Series Data
Version: 0.1.0
Author: Dr. Ranjit Kumar Paul, Sandipan Samanta and Ankit Tanwar
Maintainer: Dr. Ranjit Kumar Paul <ranjitstat@gmail.com>
Description: Fits the combination of Wavelet-GARCH model for time series forecasting using algorithm by Paul (2015) <doi:10.3233/MAS-150328>.
License: GPL
Imports: stats, wavelets, FinTS, forecast, parallel, rugarch, fracdiff
LazyData: TRUE
NeedsCompilation: no
Packaged: 2019-10-15 09:56:16 UTC; ranjitstat
Repository: CRAN
Date/Publication: 2019-10-17 08:40:02 UTC

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New package ubiquity with initial version 1.0.0
Package: ubiquity
Type: Package
Title: PKPD, PBPK, and Systems Pharmacology Modeling Tools
Version: 1.0.0
Authors@R: c(person("John", "Harrold", role = c("aut", "cre"), email = "john.m.harrold@gmail.com"))
Author: John Harrold [aut, cre]
Maintainer: John Harrold <john.m.harrold@gmail.com>
Description: Complete work flow for the analysis of pharmacokinetic pharmacodynamic (PKPD), physiologically-based pharmacokinetic (PBPK) and systems pharmacology models including: creation of ordinary differential equation-based models, pooled parameter estimation, individual/population based simulations, rule-based simulations for clinical trial design and modeling assays, deployment with a customizable 'Shiny' app, and non-compartmental analysis. System-specific analysis templates can be generated and each element includes integrated reporting with 'PowerPoint'.
URL: https://ubiquity.tools/rworkflow
SystemRequirements: Perl
BugReports: https://github.com/john-harrold/ubiquity/issues
License: BSD_2_clause + file LICENSE
Encoding: UTF-8
LazyData: TRUE
Imports: deSolve, digest, doParallel, doRNG, flextable, foreach, gridExtra, grid, gdata, ggplot2, knitr, MASS, officer (>= 0.3.5), optimx, PKNCA, pso, rmarkdown, rhandsontable, rstudioapi, stats, shiny,
Suggests: GA, GGally, gridGraphics, webshot, testthat, ggrepel
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-14 22:14:37 UTC; jmh
Repository: CRAN
Date/Publication: 2019-10-17 08:10:02 UTC

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New package orderly with initial version 1.0.1
Package: orderly
Title: Lightweight Reproducible Reporting
Version: 1.0.1
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: 2019-10-14 12:11:45 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: 2019-10-17 08:10:08 UTC

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Wed, 16 Oct 2019

New package pancor with initial version 0.1.0
Package: pancor
Type: Package
Title: Calculation and Plot of Gene Correlationship in TCGA/GTEx/CCLE
Description: The data of TCGA (The Cancer Genome Atlas), GTEx (Genotype-Tissue Expression), and CCLE (Broad Institute Cancer Cell Line Encyclopedia) are downloaded and preprocessed. With the help of 'pancor', one can easily calculate the correlation of two gene in any cancer type. Reference: Huang, H. (2019) <doi:10.1038/s41586-019-1016-7>.
Version: 0.1.0
Authors@R: c(person(given = "Zhougeng", family = "Xu", email = "xuzhougeng@163.com", role = c("aut", "cre")), person(given = "Shipeng", family = "Guo", role = c("aut", "ctb")))
Maintainer: Zhougeng Xu <xuzhougeng@163.com>
License: Artistic-2.0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.5.0)
Imports: ggplot2, rlang
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-10-15 01:28:54 UTC; DELL
Author: Zhougeng Xu [aut, cre], Shipeng Guo [aut, ctb]
Repository: CRAN
Date/Publication: 2019-10-16 12:20:02 UTC

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New package IndexNumber with initial version 1.0
Package: IndexNumber
Type: Package
Title: Index Numbers in Social Sciences
Version: 1.0
Date: 2019-10-11
Author: Alejandro Saavedra-Nieves, Paula Saavedra-Nieves
Maintainer: Alejandro Saavedra-Nieves <alejandro.saavedra.nieves@gmail.com>
Description: We provide an R tool to determine index numbers. It is a measure of the evolution of a fixed magnitude for only a product of for several products. It is very useful in Social Sciences. Among others, we obtain simple index numbers (in chain or in serie), index numbers for not only a product or weighted index numbers as the Laspeyres index (Laspeyres, 1864), the Paasche index (Paasche, 1874) or the Fisher index (Lapedes, 1978).
License: GPL-2
NeedsCompilation: no
Packaged: 2019-10-14 15:57:43 UTC; alexs
Repository: CRAN
Date/Publication: 2019-10-16 12:10:05 UTC

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New package govdown with initial version 0.7.0
Package: govdown
Title: GOV.UK Style Templates for R Markdown
Version: 0.7.0
Authors@R: c(person(given = "Crown Copyright 2018", role = "cph"), person(given = "Duncan", family = "Garmonsway", role = c("aut", "cre"), email = "duncan.garmonsway@digital.cabinet-office.gov.uk"))
Description: A suite of custom R Markdown formats and templates for authoring web pages styled with the GOV.UK Design System.
License: MIT + file LICENSE
URL: https://ukgovdatascience.github.io/govdown
BugReports: https://github.com/ukgovdatascience/govdown/issues
Imports: rmarkdown
Suggests: reticulate, testthat (>= 2.1.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
SystemRequirements: pandoc (>= 2.0) - http://pandoc.org
NeedsCompilation: no
Packaged: 2019-10-14 16:01:40 UTC; nacnudus
Author: Crown Copyright 2018 [cph], Duncan Garmonsway [aut, cre]
Maintainer: Duncan Garmonsway <duncan.garmonsway@digital.cabinet-office.gov.uk>
Repository: CRAN
Date/Publication: 2019-10-16 12:10:02 UTC

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New package BFS with initial version 0.2.1
Package: BFS
Type: Package
Title: Search and Download Data from the Swiss Federal Statistical Office (BFS)
Version: 0.2.1
Authors@R: person("Felix", "Luginbuhl", email = "felix.luginbuhl@protonmail.ch", role = c("aut", "cre"))
Maintainer: Felix Luginbuhl <felix.luginbuhl@protonmail.ch>
Description: Search and download data from the Swiss Federal Statistical Office <https://www.bfs.admin.ch/>.
License: MIT + file LICENSE
Depends: R (>= 3.0.1)
Imports: xml2, rvest, tibble, magrittr, purrr, janitor, progress, pxR
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://felixluginbuhl.com/BFS, https://github.com/lgnbhl/BFS
BugReports: https://github.com/lgnbhl/BFS/issues
NeedsCompilation: no
Packaged: 2019-10-14 16:26:40 UTC; Felix
Author: Felix Luginbuhl [aut, cre]
Repository: CRAN
Date/Publication: 2019-10-16 12:10:08 UTC

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New package ANOVAIREVA with initial version 0.1.0
Package: ANOVAIREVA
Type: Package
Title: Interactive Document for Working with Analysis of Variance
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive document on the topic of one-way and two-way analysis of variance using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at <https://tinyurl.com/ANOVAStatsTool>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,rmarkdown,dplyr,datasets,car,ggplot2,plotly
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-15 06:54:03 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-10-16 12:40:02 UTC

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New package ALassoSurvIC with initial version 0.1.0
Package: ALassoSurvIC
Type: Package
Title: Adaptive Lasso for the Cox Regression with Interval Censored and Possibly Left Truncated Data
Version: 0.1.0
Author: Chenxi Li, Daewoo Pak and David Todem
Maintainer: Daewoo Pak <heavyrain.pak@gmail.com>
Description: Penalized variable selection tools for the Cox proportional hazards model with interval censored and possibly left truncated data. It performs variable selection via penalized nonparametric maximum likelihood estimation with an adaptive lasso penalty. The optimal thresholding parameter can be searched by the package based on the profile Bayesian information criterion (BIC). The asymptotic validity of the methodology is established in Li et al. (2019 <doi:10.1177/0962280219856238>). The unpenalized nonparametric maximum likelihood estimation for interval censored and possibly left truncated data is also available.
Depends: R (>= 3.5.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: Rcpp, parallel
LinkingTo: Rcpp
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-10-14 19:34:35 UTC; dpak
Repository: CRAN
Date/Publication: 2019-10-16 12:20:05 UTC

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New package WaveSampling with initial version 0.1.0
Package: WaveSampling
Type: Package
Title: Weakly Associated Vectors (WAVE) Sampling
Version: 0.1.0
Authors@R: c( person("Raphaël", "Jauslin", email = "raphael.jauslin@unine.ch",role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1088-3356") ), person("Yves", "Tillé",role = c("aut"), comment = c(ORCID = "0000-0003-0904-5523")) )
Description: Spatial data are generally auto-correlated, meaning that if two units selected are close to each other, then it is likely that they share the same properties. For this reason, when sampling in the population it is often needed that the sample is well spread over space. A new method to draw a sample from a population with spatial coordinates is proposed. This method is called wave (Weakly Associated Vectors) sampling. It uses the less correlated vector to a spatial weights matrix to update the inclusion probabilities vector into a sample.
URL: https://github.com/RJauslin/wave
BugReports: https://github.com/RJauslin/wave/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: RcppArmadillo, Rcpp
Imports: Rcpp
Depends: Matrix, R (>= 2.10)
Suggests: knitr, rmarkdown, ggplot2, ggvoronoi, sampling, BalancedSampling, sp, sf, stats
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-10-15 07:42:43 UTC; jauslinr
Author: Raphaël Jauslin [aut, cre] (<https://orcid.org/0000-0003-1088-3356>), Yves Tillé [aut] (<https://orcid.org/0000-0003-0904-5523>)
Maintainer: Raphaël Jauslin <raphael.jauslin@unine.ch>
Repository: CRAN
Date/Publication: 2019-10-16 12:00:11 UTC

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New package trekcolors with initial version 0.1.1
Package: trekcolors
Title: Star Trek Color Palettes
Version: 0.1.1
Authors@R: person("Matthew", "Leonawicz", email = "matt_leonawicz@esource.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9452-2771"))
Description: Provides a dataset of predefined color palettes based on the Star Trek science fiction series, associated color palette functions, and additional functions for generating customized palettes that are on theme. The package also offers functions for applying the palettes to plots made using the 'ggplot2' package.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/leonawicz/trekcolors
BugReports: https://github.com/leonawicz/trekcolors/issues
Depends: R (>= 2.10)
Imports: ggplot2
Suggests: testthat, knitr, rmarkdown, covr
RoxygenNote: 6.1.1
Language: en-US
NeedsCompilation: no
Packaged: 2019-10-15 02:52:51 UTC; Matt
Author: Matthew Leonawicz [aut, cre] (<https://orcid.org/0000-0001-9452-2771>)
Maintainer: Matthew Leonawicz <matt_leonawicz@esource.com>
Repository: CRAN
Date/Publication: 2019-10-16 11:50:03 UTC

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New package test2norm with initial version 0.1.1
Package: test2norm
Type: Package
Title: Normative Standards for Cognitive Tests
Version: 0.1.1
Author: Anya Umlauf
Maintainer: Anya Umlauf <aumlauf@ucsd.edu>
Description: Function test2norm() generates formulas for normative standards applied to cognitive tests. It takes raw test scores (e.g., number of correct responses) and converts them to scaled scores and demographically adjusted scores, using methods described in Heaton et al. (2003) <doi:10.1016/B978-012703570-3/50010-9> & Heaton et al. (2009, ISBN:9780199702800). The scaled scores are calculated as quantiles of the raw test scores, scaled to have the mean of 10 and standard deviation of 3, such that higher values always correspond to better performance on the test. The demographically adjusted scores are calculated from the residuals of a model that regresses scaled scores on demographic predictors (e.g., age). The norming procedure makes use of the mfp() function from the 'mfp' package to explore nonlinear associations between cognition and demographic variables.
License: CPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: mfp
Depends: R (>= 2.10)
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-15 21:03:19 UTC; umlauf
Repository: CRAN
Date/Publication: 2019-10-16 12:00:02 UTC

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New package MTGS with initial version 0.1.0
Package: MTGS
Type: Package
Title: Genomic Selection using Multiple Traits
Version: 0.1.0
Author: Neeraj Budhlakoti, D C Mishra, Anil Rai
Maintainer: Neeraj Budhlakoti <neeraj35669@gmail.com>
Description: Genomic selection (GS) is recent development in animal and plant breeding. In GS whole genome markers information is used to predict genetic merit of an individual. This package is basically developed for genomic predictions by estimating marker effects. These marker effects are then further used for calculation of genotypic merit of individual i.e. genome estimated breeding values (GEBVs). However, as genetic correlations between quantitative traits under breeding studies are obvious. These correlations indicate that one trait carry information over other traits. Current, single-trait genomic selection (STGS) methods could not able to utilize this information. Genomic selection based on multiple traits (MTGS) could be a better alternative to STGS. This package performs genomic selection using multi traits information hence named as MTGS i.e. multi trait genomic selection. MTGS is a comprehensive package which gives single step solution for genomic selection using various MTGS based methods.
License: GPL-3
Depends: R (>= 3.6)
Imports: glmnet, kernlab, MRCE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-15 01:18:16 UTC; Neeraj
Repository: CRAN
Date/Publication: 2019-10-16 11:50:09 UTC

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New package miniparquet with initial version 0.1.1
Package: miniparquet
Title: Read Parquet Files
Version: 0.1.1
Authors@R: c( person("Hannes", "M\u00fchleisen", role = c("aut", "cre"), email = "hannes@cwi.nl", comment = c(ORCID = "0000-0001-8552-0029")), person("Google Inc.", role = "cph"), person("Apache Software Foundation", role = "cph"), person("Daniel", "Lemire", role = "cph"), person("Chad", "Walters", role = "cph"))
Description: Self-sufficient reader for a subset of Parquet files. Nested tables, compression besides Snappy and encryption are not supported.
Depends: R (>= 3.5.0)
Imports: methods
License: MIT + file LICENSE
Encoding: UTF-8
Collate: 'miniparquet.R'
SystemRequirements: C++11
Suggests: testthat
NeedsCompilation: yes
Packaged: 2019-10-15 08:52:48 UTC; hannes
Author: Hannes Mühleisen [aut, cre] (<https://orcid.org/0000-0001-8552-0029>), Google Inc. [cph], Apache Software Foundation [cph], Daniel Lemire [cph], Chad Walters [cph]
Maintainer: Hannes Mühleisen <hannes@cwi.nl>
Repository: CRAN
Date/Publication: 2019-10-16 12:00:04 UTC

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New package geometr with initial version 0.1.1
Package: geometr
Title: Generate and Modify Interoperable Geometric Shapes
Version: 0.1.1
Authors@R: c( person("Steffen", "Ehrmann", role = c("aut", "cre"), email = "steffen@funroll-loops.de", comment = c(ORCID = "0000-0002-2958-0796")), person("Dan", "Sunday", role = c("cph"), comment = "fast point-in-polygon algorithm.") )
Description: Provides tools that generate and process fully accessible and tidy geometric shapes. The package improves interoperability of spatial and other geometric classes by providing getters and setters that produce identical output from various classes.
URL: https://github.com/EhrmannS/geometr
BugReports: https://github.com/EhrmannS/geometr/issues
Depends: R (>= 2.10)
Language: en-gb
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: checkmate, sf, sp, spatstat, raster, crayon, deldir, dplyr, grDevices, grid, methods, rgdal, rlang, tibble
Suggests: testthat, rmarkdown, magrittr, covr, knitr, readr
LinkingTo: Rcpp
RoxygenNote: 6.1.1
SystemRequirements: C++11
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-10-15 11:48:38 UTC; se87kuhe
Author: Steffen Ehrmann [aut, cre] (<https://orcid.org/0000-0002-2958-0796>), Dan Sunday [cph] (fast point-in-polygon algorithm.)
Maintainer: Steffen Ehrmann <steffen@funroll-loops.de>
Repository: CRAN
Date/Publication: 2019-10-16 12:00:07 UTC

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New package CensMFM with initial version 1.4
Package: CensMFM
Type: Package
Title: Finite Mixture of Multivariate Censored/Missing Data
Version: 1.4
Date: 2019-10-14
Authors@R: c( person("Francisco H. C.", "de Alencar", email = "hildemardealencar@gmail.com", role = c("aut", "cre")), person("Christian E.", "Galarza", email = "cgalarza88@gmail.com", role = "aut"), person("Larissa A.", "Matos", email = "larissa.amatos@gmail.com", role = "ctb"), person("Victor H.", "Lachos", email = "hlachos@gmail.com", role = "ctb"))
Imports: MomTrunc, mnormt, mvtnorm, gridExtra, ggplot2
Suggests: mixsmsn
Description: It fits finite mixture models for censored or/and missing data using several multivariate distributions. Point estimation and asymptotic inference (via empirical information matrix) are offered as well as censored data generation. Pairwise scatter and contour plots can be generated. Possible multivariate distributions are the well-known normal, Student-t and skew-normal distributions. This package is an complement of Lachos, V. H., Moreno, E. J. L., Chen, K. & Cabral, C. R. B. (2017) <doi:10.1016/j.jmva.2017.05.005> for the multivariate skew-normal case.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-10-14 18:17:24 UTC; cgala
Author: Francisco H. C. de Alencar [aut, cre], Christian E. Galarza [aut], Larissa A. Matos [ctb], Victor H. Lachos [ctb]
Maintainer: Francisco H. C. de Alencar <hildemardealencar@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-16 11:50:12 UTC

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New package agrostab with initial version 0.1.0
Package: agrostab
Type: Package
Title: Stability Analysis for Agricultural Research
Version: 0.1.0
Date: 2019-10-01
Author: Anna Cheshkova [aut, cre]
Maintainer: Anna Cheshkova <cheshanf@gmail.com>
Description: Statistical procedures to perform stability analysis in plant breeding and to identify stable genotypes under diverse environments. It is possible to calculate coefficient of homeostaticity by Khangildin et al. (1979), variance of specific adaptive ability by Kilchevsky&Khotyleva (1989), weighted homeostaticity index by Martynov (1990), steadiness of stability index by Udachin (1990), superiority measure by Lin&Binn (1988) <doi:10.4141/cjps88-018>, regression on environmental index by Erberhart&Rassel (1966) <doi:10.2135/cropsci1966.0011183X000600010011x>, Tai's (1971) stability parameters <doi:10.2135/cropsci1971.0011183X001100020006x>, stability variance by Shukla (1972) <doi:10.1038/hdy.1972.87>, ecovalence by Wricke (1962), nonparametric stability parameters by Nassar&Huehn (1987) <doi:10.2307/2531947>, Francis&Kannenberg's parameters of stability (1978) <doi:10.4141/cjps78-157>.
Depends: R (>= 3.1)
Imports: ggplot2, dplyr, graphics, stats, rlang
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-15 01:17:51 UTC; anna
Repository: CRAN
Date/Publication: 2019-10-16 11:50:06 UTC

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Mon, 14 Oct 2019

New package fdaPDE with initial version 0.1-6
Package: fdaPDE
Version: 0.1-6
Date: 2019-10-14
Title: Functional Data Analysis and Partial Differential Equations; Statistical Analysis of Functional and Spatial Data, Based on Regression with Partial Differential Regularizations
Authors@R: c(person("Eardi", "Lila", role = c("aut", "cre"), email = "el425@cam.ac.uk"), person("Laura M.", "Sangalli", role = "aut", email = "laura.sangalli@polimi.it"), person("Jim", "Ramsay", role = "aut", email = " ramsay@psych.mcgill.ca"), person("Luca", "Formaggia", role = "aut", email = " luca.formaggia@polimi.it"))
Author: Eardi Lila [aut, cre], Laura M. Sangalli [aut], Jim Ramsay [aut], Luca Formaggia [aut]
Maintainer: Eardi Lila <el425@cam.ac.uk>
Depends: R (>= 3.0.0), stats, grDevices, graphics, rgl
LinkingTo: RcppEigen
Suggests: MASS
Description: An implementation of regression models with partial differential regularizations, making use of the Finite Element Method. The models efficiently handle data distributed over irregularly shaped domains and can comply with various conditions at the boundaries of the domain. A priori information about the spatial structure of the phenomenon under study can be incorporated in the model via the differential regularization.
License: CC BY-NC-SA 4.0
Copyright: See the individual source files for copyrights information
NeedsCompilation: yes
SystemRequirements: C++11
RoxygenNote: 6.1.1
Packaged: 2019-10-14 15:49:36 UTC; eardi
Repository: CRAN
Date/Publication: 2019-10-14 18:10:02 UTC

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New package bigassertr with initial version 0.1.1
Package: bigassertr
Title: Assertion and Message Functions
Version: 0.1.1
Date: 2019-10-12
Authors@R: person(given = "Florian", family = "Privé", role = c("aut", "cre"), email = "florian.prive.21@gmail.com")
Description: Enhanced message functions (cat() / message() / warning() / error()) using wrappers around sprintf(). Also, multiple assertion functions (e.g. to check class, length, values, files, arguments, etc.).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Suggests: testthat, covr
NeedsCompilation: no
Packaged: 2019-10-14 07:47:16 UTC; privef
Author: Florian Privé [aut, cre]
Maintainer: Florian Privé <florian.prive.21@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-14 16:10:02 UTC

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New package BayesSUR with initial version 1.0-0
Package: BayesSUR
Type: Package
Title: Bayesian Seemingly Unrelated Regression
Version: 1.0-0
Date: 2019-10-13
Authors@R: c(person("Marco", "Banterle", email = "marco.banterle@gmail.com", role = c("aut")), person("Zhi", "Zhao", email = "zhi.zhao@medisin.uio.no", role = c("aut", "cre")), person("Leonardo", "Bottolo", email = "lb664@cam.ac.uk", role = c("ctb")), person("Sylvia", "Richardson", email = "sylvia.richardson@mrc-bsu.cam.ac.uk", role = c("ctb")), person("Alex", "Lewin", email = "alex.lewin@lshtm.ac.uk", role = c("aut")), person("Manuela", "Zucknick", email = "manuela.zucknick@medisin.uio.no", role = c("ctb")))
Description: Bayesian seemingly unrelated regression with general variable selection and dense/sparse covariance matrix. The sparse seemingly unrelated regression is described in Banterle et al. (2018) <doi:10.1101/467019>.
License: MIT + file LICENSE
Copyright: The C++ files pugixml.cpp, pugixml.hpp and pugiconfig.hpp are Copyright (C) 2006-2018 by Arseny Kapoulkine (arseny.kapoulkine@gmail.com) and Copyright (C) 2003 by Kristen Wegner (kristen@tima.net).
VignetteBuilder: R.rsp
RoxygenNote: 6.1.1
Depends: R (>= 3.5.0)
Encoding: UTF-8
LinkingTo: Rcpp, RcppArmadillo (>= 0.9.000)
Imports: Rcpp, utils, xml2, stats, igraph, Matrix, fields, tikzDevice, grDevices, graphics, BDgraph, data.table, plyr, scrime, gRbase
Suggests: R.rsp
LazyData: true
NeedsCompilation: yes
SystemRequirements: C++11
Packaged: 2019-10-13 16:52:01 UTC; zhiz
Author: Marco Banterle [aut], Zhi Zhao [aut, cre], Leonardo Bottolo [ctb], Sylvia Richardson [ctb], Alex Lewin [aut], Manuela Zucknick [ctb]
Maintainer: Zhi Zhao <zhi.zhao@medisin.uio.no>
Repository: CRAN
Date/Publication: 2019-10-14 16:10:05 UTC

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New package robregcc with initial version 1.0
Package: robregcc
Type: Package
Title: Robust Regression with Compositional Covariates
Version: 1.0
Date: 2019-10-10
Authors@R: c(person(given = "Aditya", family = "Mishra", role = c("aut", "cre"), email = "amishra@flatironinstitute.org"), person(given = "Christian", family = "Muller", role = "ctb"))
Maintainer: Aditya Mishra <amishra@flatironinstitute.org>
Description: We implement the algorithm estimating the parameters of the robust regression model with compositional covariates. The model simultaneously treats outliers and provides reliable parameter estimates. Publication reference: Mishra, A., Mueller, C.,(2019) <arXiv:1909.04990>.
URL: https://arxiv.org/abs/1909.04990, https://github.com/amishra-simonsfoundation/robregcc
Depends: R (>= 3.5.0), stats, utils
License: GPL (>= 3.0)
LazyData: true
Imports: Rcpp (>= 0.12.0), MASS, magrittr, graphics
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
RoxygenNote: 6.1.1
Encoding: UTF-8
Packaged: 2019-10-13 15:03:06 UTC; amishra
Author: Aditya Mishra [aut, cre], Christian Muller [ctb]
Repository: CRAN
Date/Publication: 2019-10-14 15:40:02 UTC

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New package RAthena with initial version 1.2.0
Package: RAthena
Type: Package
Title: Connect to 'AWS Athena' using 'Boto3' ('DBI' Interface)
Version: 1.2.0
Authors@R: person("Dyfan", "Jones", email="dyfan.r.jones@gmail.com", role= c("aut", "cre"))
Description: Designed to be compatible with the R package 'DBI' (Database Interface) when connecting to Amazon Web Service ('AWS') Athena <https://aws.amazon.com/athena/>. To do this 'Python' 'Boto3' Software Development Kit ('SDK') <https://boto3.amazonaws.com/v1/documentation/api/latest/index.html> is used as a driver.
Imports: DBI (>= 0.7), methods, reticulate (>= 1.13), stats, utils
Suggests: arrow, data.table, dplyr, dbplyr, testthat
Depends: R (>= 3.2.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/DyfanJones/RAthena
BugReports: https://github.com/DyfanJones/RAthena/issues
Collate: 'RAthena.R' 'Driver.R' 'Connection.R' 'DataTypes.R' 'Result.R' 'athena_low_api.R' 'dplyr_integration.R' 'install.R' 'table.R' 'util.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2019-10-13 13:32:39 UTC; lmar763
Author: Dyfan Jones [aut, cre]
Maintainer: Dyfan Jones <dyfan.r.jones@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-14 15:20:02 UTC

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New package ivdesc with initial version 1.0.0
Package: ivdesc
Title: Profiling Compliers and Non-Compliers for Instrumental Variable Analysis
Version: 1.0.0
Author: Moritz Marbach <moritz.marbach@gess.ethz.ch> [aut, cre]
Maintainer: Moritz Marbach <moritz.marbach@gess.ethz.ch>
Description: Estimating the mean and variance of a covariate for the complier, never-taker and always-taker subpopulation in the context of instrumental variable estimation. This package implements the method described in Marbach and Hangartner (2019) <doi:10.2139/ssrn.3380247>.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: icsw, haven
Imports: knitr (>= 1.20.8), purrr (>= 0.2.5), rsample (>= 0.0.3)
NeedsCompilation: no
Packaged: 2019-10-14 15:35:01 UTC; marbacmo
Repository: CRAN
Date/Publication: 2019-10-14 15:50:02 UTC

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New package lss2 with initial version 1.1
Package: lss2
Type: Package
Title: The Accelerated Failure Time Model to Right Censored Data Based on Least-Squares Principle
Version: 1.1
Author: Zhezhen Jin <zj7@columbia.edu>, Arvin Satwani <arvinsatwani@gmail.com>
Maintainer: Arvin Satwani <arvinsatwani@gmail.com>
Description: Due to lack of proper inference procedure and software, the ordinary linear regression model is seldom used in practice for the analysis of right censored data. This paper presents an S-Plus/R program that implements a recently developed inference procedure (Jin, Lin and Ying, 2006) <doi:10.1093/biomet/93.1.147> for the accelerated failure time model based on the least-squares principle.
Depends: R(>= 2.1.0), quantreg
Suggests: survival
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-12 16:19:22 UTC; arvinsatwani
Repository: CRAN
Date/Publication: 2019-10-14 14:30:02 UTC

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New package SDEFSR with initial version 0.7.2
Package: SDEFSR
Type: Package
Title: Subgroup Discovery with Evolutionary Fuzzy Systems
Version: 0.7.2
Date: 2019-10-14
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: 2019-10-14 09:36:06 UTC; agvico
Encoding: UTF-8
Repository: CRAN
Date/Publication: 2019-10-14 10:10:05 UTC

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Sun, 13 Oct 2019

New package fdaPDE with initial version 0.1-5
Package: fdaPDE
Version: 0.1-5
Date: 2019-10-12
Title: Functional Data Analysis and Partial Differential Equations; Statistical Analysis of Functional and Spatial Data, Based on Regression with Partial Differential Regularizations
Authors@R: c(person("Eardi", "Lila", role = c("aut", "cre"), email = "el425@cam.ac.uk"), person("Laura M.", "Sangalli", role = "aut", email = "laura.sangalli@polimi.it"), person("Jim", "Ramsay", role = "aut", email = " ramsay@psych.mcgill.ca"), person("Luca", "Formaggia", role = "aut", email = " luca.formaggia@polimi.it"))
Author: Eardi Lila [aut, cre], Laura M. Sangalli [aut], Jim Ramsay [aut], Luca Formaggia [aut]
Maintainer: Eardi Lila <el425@cam.ac.uk>
Depends: R (>= 3.0.0), stats, grDevices, graphics, rgl
LinkingTo: RcppEigen
Suggests: MASS
Description: An implementation of regression models with partial differential regularizations, making use of the Finite Element Method. The models efficiently handle data distributed over irregularly shaped domains and can comply with various conditions at the boundaries of the domain. A priori information about the spatial structure of the phenomenon under study can be incorporated in the model via the differential regularization.
License: CC BY-NC-SA 4.0
Copyright: See the individual source files for copyrights information
NeedsCompilation: yes
SystemRequirements: C++11
RoxygenNote: 6.1.1
Packaged: 2019-10-13 14:21:44 UTC; eardi
Repository: CRAN
Date/Publication: 2019-10-13 14:50:02 UTC

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New package Hmsc with initial version 3.0-2
Package: Hmsc
Title: Hierarchical Model of Species Communities
Type: Package
Version: 3.0-2
Authors@R: c(person(given = "Gleb", family="Tikhonov", role="aut"), person(given="Otso", family="Ovaskainen", email="otso.ovaskainen@helsinki.fi", comment = c(ORCID="0000-0001-9750-4421"), role=c("aut","cre")), person(given="Jari", family="Oksanen", role="aut"), person(given="Melinda", family=c("de", "Jonge"), role="aut"), person(given="Oystein", family="Opedal", role="aut"), person(given="Tad", family="Dallas", role="aut"))
Description: Hierarchical Modelling of Species Communities (HMSC) is a model-based approach for analyzing community ecological data. This package implements it in the Bayesian framework with Gibbs Markov chain Monte Carlo (MCMC) sampling.
License: GPL-3 | file LICENSE
URL: https://www.helsinki.fi/en/researchgroups/statistical-ecology/hmsc
BugReports: https://github.com/hmsc-r/HMSC/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
Suggests: R.rsp, testthat, corrplot
VignetteBuilder: R.rsp
Depends: R (>= 3.0.2), coda
Imports: abind, ape, BayesLogit, fields, FNN, ggplot2, MASS, Matrix, MCMCpack, methods, mvtnorm, nnet, parallel, pdist, pROC, phytools, statmod, truncnorm
NeedsCompilation: no
Packaged: 2019-10-11 11:55:12 UTC; jarioksa
Author: Gleb Tikhonov [aut], Otso Ovaskainen [aut, cre] (<https://orcid.org/0000-0001-9750-4421>), Jari Oksanen [aut], Melinda de Jonge [aut], Oystein Opedal [aut], Tad Dallas [aut]
Maintainer: Otso Ovaskainen <otso.ovaskainen@helsinki.fi>
Repository: CRAN
Date/Publication: 2019-10-13 14:00:06 UTC

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New package treeHMM with initial version 0.1.0
Package: treeHMM
Type: Package
Title: Tree Structured Hidden Markov Model
Version: 0.1.0
Authors@R: c(person("Prajwal","Bende", role=c("aut","cre"),email="pbende@ualberta.ca"))
Author: Prajwal Bende [aut, cre]
Maintainer: Prajwal Bende <pbende@ualberta.ca>
Description: Used for Inference, Prediction and Parameter learning for tree structured Hidden Markov Model. The package propose a new architecture of Hidden Markov Model(HMM) known as Tree Structured HMM which could be used in various applications which involves graphs, trees etc.
License: GPL (>= 2.0.0)
Encoding: UTF-8
LazyData: true
Imports: Matrix, gtools, future, matrixStats, PRROC
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-11 13:02:11 UTC; Prajwal
Repository: CRAN
Date/Publication: 2019-10-13 11:10:02 UTC

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New package INLAMSM with initial version 0.1
Package: INLAMSM
Type: Package
Title: Multivariate Spatial Models with 'INLA'
Version: 0.1
Authors@R: c( person(given = "Francisco", family = "Palmí-Perales", email = "Francisco.Palmi@uclm.es", role = c("aut") ), person(given = "Virgilio", family = "Gómez-Rubio", email = "Virgilio.Gomez@uclm.es", role = c("aut", "cre") ), person(given = "Miguel A.", family = "Martinez-Beneito", email = "martinez_mig@gva.es", role = c("aut") ) )
Maintainer: Virgilio Gómez-Rubio <Virgilio.Gomez@uclm.es>
Description: Implementation of several multivariate areal latent effects for 'INLA' using the 'rgeneric' latent effect (Palmí-Perales et al., 2019, <arXiv:1909.10804>). The 'INLA' package can be downloaded from <http://www.r-inla.org>. In particular, the package includes latent effects ready to use for several multivariate spatial models: intrinsic CAR, proper CAR and the M-model (Botella-Rocamora et al., 2015, <doi:10.1002/sim.6423>).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: Matrix, MCMCpack
Suggests: INLA, spData, spdep, rgdal
Additional_repositories: https://inla.r-inla-download.org/R/stable/
NeedsCompilation: no
Packaged: 2019-10-11 11:57:29 UTC; virgil
Author: Francisco Palmí-Perales [aut], Virgilio Gómez-Rubio [aut, cre], Miguel A. Martinez-Beneito [aut]
Repository: CRAN
Date/Publication: 2019-10-13 11:00:02 UTC

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New package wyz.code.metaTesting with initial version 1.1.4
Package: wyz.code.metaTesting
Type: Package
Title: Wizardry Code Meta Testing
Version: 1.1.4
Author: Fabien Gelineau <neonira@gmail.com>
Maintainer: Fabien Gelineau <neonira@gmail.com>
Description: Test R any R function without having to provide parameter values. Values will be generated, based on semantic naming of parameters as introduced by package 'wyz.code.offensiveProgramming'. Generated tests can be saved and reused. Value generation logic can be completed with your own specific data types and generation schemes, to meet your requirements. Main benefits of 'wyz.code.metaTesting' is higher developer productivity, reduced time to production, and industrial inference testing. Refer to chapter 10 of Offensive Programming Book, Fabien GELINEAU (2019, ISBN:979-10-699-4075-8), to learn about details and get value from this package.
Encoding: UTF-8
LazyData: true
License: GPL-3
Depends: R (>= 3.5)
Imports: methods, data.table (>= 1.11.8), tidyr, lubridate (>= 1.7.4), wyz.code.offensiveProgramming (>= 1.1.12), crayon, utils, stats
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-11 09:40:17 UTC; fgelineau
Repository: CRAN
Date/Publication: 2019-10-13 10:00:02 UTC

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New package genvar with initial version 0.0.1.4
Package: genvar
Title: An Imperative Library for Data Manipulation
Version: 0.0.1.4
Authors@R: person("Zach", "Flynn", email = "zlflynn@gmail.com", role = c("aut", "cre"))
Description: Implements tools for manipulating data sets and performing regressions in a way that is familiar to users of a popular, but proprietary, statistical package commonly used in the social sciences. Loads a single dataset into memory and implements a set of imperative commands to modify that data and perform regressions and other analysis on the dataset. Offers an alternative to standard R's function-based approach to data manipulation.
Depends: R (>= 3.5.1.0)
Imports: Formula, foreign, readstata13, sandwich, plm, clubSandwich
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
BugReports: https://github.com/flynnzac/genvar
NeedsCompilation: no
Packaged: 2019-10-10 23:45:30 UTC; fzac
Author: Zach Flynn [aut, cre]
Maintainer: Zach Flynn <zlflynn@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-13 09:40:02 UTC

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Sat, 12 Oct 2019

New package spectralGraphTopology with initial version 0.2.0
Package: spectralGraphTopology
Title: Learning Graphs from Data via Spectral Constraints
Version: 0.2.0
Date: 2019-10-08
Description: In the era of big data and hyperconnectivity, learning high-dimensional structures such as graphs from data has become a prominent task in machine learning and has found applications in many fields such as finance, health care, and networks. 'spectralGraphTopology' is an open source, documented, and well-tested R package for learning graphs from data. It provides implementations of state of the art algorithms such as Combinatorial Graph Laplacian Learning (CGL), Spectral Graph Learning (SGL), Graph Estimation based on Majorization-Minimization (GLE-MM), and Graph Estimation based on Alternating Direction Method of Multipliers (GLE-ADMM). In addition, graph learning has been widely employed for clustering, where specific algorithms are available in the literature. To this end, we provide an implementation of the Constrained Laplacian Rank (CLR) algorithm.
Authors@R: c( person("Ze", "Vinicius", role = c("cre", "aut"), email = "jvmirca@gmail.com"), person(c("Daniel", "P."), "Palomar", role = "aut", email = "daniel.p.palomar@gmail.com") )
Maintainer: Ze Vinicius <jvmirca@gmail.com>
URL: https://github.com/dppalomar/spectralGraphTopology, https://mirca.github.io/spectralGraphTopology, https://www.danielppalomar.com
BugReports: https://github.com/dppalomar/spectralGraphTopology/issues
Depends:
License: GPL-3
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
Imports: Rcpp, MASS, Matrix, progress, rlist
RoxygenNote: 6.1.1
Suggests: bookdown, knitr, prettydoc, rmarkdown, R.rsp, testthat, patrick, corrplot, igraph, kernlab, pals, clusterSim, viridis, quadprog, matrixcalc
VignetteBuilder: knitr, rmarkdown, R.rsp
NeedsCompilation: yes
Packaged: 2019-10-10 15:50:11 UTC; mirca
Author: Ze Vinicius [cre, aut], Daniel P. Palomar [aut]
Repository: CRAN
Date/Publication: 2019-10-12 08:00:03 UTC

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New package phaseR with initial version 2.1.3
Package: phaseR
Type: Package
Title: Phase Plane Analysis of One- And Two-Dimensional Autonomous ODE Systems
Version: 2.1.3
Authors@R: c(person(given = "Michael J", family = "Grayling", email = "michael.grayling@newcastle.ac.uk", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0680-6668")), person(given = "Gerhard", family = "Burger", email = "burger.ga@gmail.com", role = "ctb", comment = c(ORCID = "0000-0003-1062-5576")), person(given = "Stephen P", family = "Ellner", role = "ctb"), person(given = "John M", family = "Guckenheimer", role = "ctb"))
Imports: deSolve, graphics, grDevices, utils
Description: Performs a qualitative analysis of one- and two-dimensional autonomous ordinary differential equation systems, using phase plane methods. Programs are available to identify and classify equilibrium points, plot the direction field, and plot trajectories for multiple initial conditions. In the one-dimensional case, a program is also available to plot the phase portrait. Whilst in the two-dimensional case, programs are additionally available to plot nullclines and stable/unstable manifolds of saddle points. Many example systems are provided for the user. For further details can be found in Grayling (2014) <doi:10.32614/RJ-2014-023>.
License: MIT + file LICENSE
LazyData: TRUE
Suggests: knitr, rmarkdown, testthat
Date: 2019-09-10
URL: https://github.com/mjg211/phaseR
BugReports: https://github.com/mjg211/phaseR/issues
RoxygenNote: 6.1.1
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-11 08:35:37 UTC; michaelgrayling
Author: Michael J Grayling [aut, cre] (<https://orcid.org/0000-0002-0680-6668>), Gerhard Burger [ctb] (<https://orcid.org/0000-0003-1062-5576>), Stephen P Ellner [ctb], John M Guckenheimer [ctb]
Maintainer: Michael J Grayling <michael.grayling@newcastle.ac.uk>
Repository: CRAN
Date/Publication: 2019-10-12 07:30:02 UTC

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New package maotai with initial version 0.1.0
Package: maotai
Type: Package
Title: Tools for Matrix Algebra, Optimization and Inference
Version: 0.1.0
Authors@R: c(person("Kisung", "You", role = c("aut", "cre"),email = "kyoustat@gmail.com",comment=c(ORCID="0000-0002-8584-459X")))
Description: Matrix is an universal and sometimes primary object/unit in applied mathematics and statistics. We provide a number of algorithms for selected problems in optimization and statistical inference. For general exposition to the topic with focus on statistical context, see the book by Banerjee and Roy (2014, ISBN:9781420095388).
Encoding: UTF-8
License: GPL (>= 3)
Suggests: igraph, rstiefel
Imports: Rcpp, Rdpack, RSpectra, Matrix, shapes, stats, utils
LinkingTo: Rcpp, RcppArmadillo
RdMacros: Rdpack
RoxygenNote: 6.1.1
URL: http://github.com/kyoustat/maotai
BugReports: http://github.com/kyoustat/maotai/issues
NeedsCompilation: yes
Packaged: 2019-10-09 18:39:30 UTC; kisung
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyoustat@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-12 07:50:02 UTC

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Fri, 11 Oct 2019

New package discrim with initial version 0.0.1
Package: discrim
Title: Model Wrappers for Discriminant Analysis
Version: 0.0.1
Authors@R: c( person(given = "Max", family = "Kuhn", email = "max@rstudio.com", role = c("aut", "cre")), person("RStudio", role = "cph") )
Description: Bindings for additional classification models for use with the 'parsnip' package. Models include flavors of discriminant analysis, such as linear (Fisher (1936) <doi:10.1111/j.1469-1809.1936.tb02137.x>), regularized (Friedman (1989) <doi:10.1080/01621459.1989.10478752>), and flexible (Hastie, Tibshirani, and Buja (1994) <doi:10.1080/01621459.1994.10476866>), as well as naive Bayes classifiers (Hand and Yu (2007) <doi:10.1111/j.1751-5823.2001.tb00465.x>).
License: GPL-2
Depends: parsnip, R (>= 2.10)
Imports: purrr, rlang, tibble, withr, dials
Suggests: testthat, MASS, mda, klaR, earth, mlbench, covr, ggplot2, xml2, spelling
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Language: en-US
NeedsCompilation: no
Packaged: 2019-10-10 16:56:57 UTC; max
Author: Max Kuhn [aut, cre], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>
Repository: CRAN
Date/Publication: 2019-10-11 12:10:02 UTC

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New package BayesBEKK with initial version 0.1.0
Package: BayesBEKK
Type: Package
Title: Bayesian Estimation of Bivariate Volatility Model
Version: 0.1.0
Author: Achal Lama, Girish K Jha, K N Singh and Bishal Gurung
Maintainer: Achal Lama <achal.lama@icar.gov.in>
Depends: R (>= 3.3.0),MTS,coda,mvtnorm
Description: The Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) models are used for modelling the volatile multivariate data sets. In this package a variant of MGARCH called BEKK (Baba, Engle, Kraft, Kroner) proposed by Engle and Kroner (1995) <http://www.jstor.org/stable/3532933> has been used to estimate the bivariate time series data using Bayesian technique.
Encoding: UTF-8
LazyData: true
License: GPL-3
NeedsCompilation: no
Packaged: 2019-10-11 11:28:22 UTC; USER
Repository: CRAN
Date/Publication: 2019-10-11 12:10:05 UTC

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New package usefun with initial version 0.4.1
Package: usefun
Type: Package
Title: A Collection of Useful Functions by John
Version: 0.4.1
Authors@R: person("John", "Zobolas", role = c("aut", "cph", "cre"), email = "bblodfon@gmail.com", comment = c(ORCID = "0000-0002-3609-8674"))
Description: A set of general functions that I have used in various projects and in other R packages. They support some miscellaneous operations on data frames, matrices and vectors: adding a row on a ternary (3-value) data.frame based on positive and negative vector-indicators, rearranging a list of data.frames by rownames, pruning rows or columns of a data.frame that contain only one specific value given by the user, checking for matrix equality, pruning and reordering a vector according to the common elements between its names and elements of another given vector, finding the non-common elements between two vectors (outer-section), normalization of a vector, matrix or data.frame's numeric values in a specified range, pretty printing of vector names and values in an R notebook (common names and values between two vectors also supported), retrieving the parent directory of any string path, checking whether a numeric value is inside a given interval, trim the decimal points of a given numeric value, quick saving of data to a file, making a multiple densities plot and a color bar plot and executing a plot string expression while generating the result to the specified file format.
License: MIT + file LICENSE
URL: https://github.com/bblodfon/usefun
BugReports: https://github.com/bblodfon/usefun/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: grDevices, graphics, stats, utils
Suggests: testthat, covr
NeedsCompilation: no
Packaged: 2019-10-10 13:07:02 UTC; john
Author: John Zobolas [aut, cph, cre] (<https://orcid.org/0000-0002-3609-8674>)
Maintainer: John Zobolas <bblodfon@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-11 11:40:02 UTC

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New package tangles with initial version 0.8.1
Package: tangles
Type: Package
Title: Anonymization of Spatial Point Patterns and Raster Objects
Version: 0.8.1
Date: 2019-10-10
Authors@R: c(person("Brendan", "Malone", email = "brendan.malone@csiro.au", role = c("cre", "aut")))
Description: Spatial data anonymization preserves confidentiality. Using methods described in Zandbergen (2014) <doi:10.1155/2014/567049>, spatial data anonymization is achieved by dithering original spatial coordinates with combinations of randomized vertical, horizontal and rotational shifts. This can apply to non-grid spatial point patterns and raster objects, and the methods preserve the same spatial characteristics and relationships of the original data. Unique hash keying enables data subjected to anonymization sequences to be re-identified where required.
Depends: R (>= 3.0.1)
Imports: raster, digest, sp
Suggests: rasterVis, rgdal, knitr, rmarkdown
VignetteBuilder: knitr
License: GPL-2
LazyData: no
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-10-10 09:18:20 UTC; mal181
Author: Brendan Malone [cre, aut]
Maintainer: Brendan Malone <brendan.malone@csiro.au>
Repository: CRAN
Date/Publication: 2019-10-11 11:30:02 UTC

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New package SailoR with initial version 1.0
Package: SailoR
Type: Package
Title: An Extension of the Taylor Diagram to Two-Dimensional Vector Data
Version: 1.0
Date: 2019-10-09
Authors@R: c(person(given = "Jon", family = "Sáenz", role = c("aut", "cph"), comment = c(ORCID = "0000-0002-5920-7570")), person(given = "Sheila", family = "Carreno-Madinabeitia", role = c("aut", "cph"), comment = c(ORCID = "0000-0003-4625-6178")), person(given = "Santos J.", family = "González-Rojí", role = c("aut", "cre", "cph"), email = "santosjose.gonzalez@ehu.eus", comment = c(ORCID = "0000-0003-4737-0984")), person(given = "Ganix", family = "Esnaola", role = c("ctb","cph"), comment = c(ORCID = "0000-0001-9058-043X")), person(given = "Gabriel", family = "Ibarra-Berastegi", role = c("ctb","cph"), comment = c(ORCID = "0000-0001-8681-3755")), person(given = "Alain", family = "Ulazia", role = c("ctb","cph"), comment = c(ORCID = "0000-0002-4124-2853")))
Author: Jon Sáenz [aut, cph] (<https://orcid.org/0000-0002-5920-7570>), Sheila Carreno-Madinabeitia [aut, cph] (<https://orcid.org/0000-0003-4625-6178>), Santos J. González-Rojí [aut, cre, cph] (<https://orcid.org/0000-0003-4737-0984>), Ganix Esnaola [ctb, cph] (<https://orcid.org/0000-0001-9058-043X>), Gabriel Ibarra-Berastegi [ctb, cph] (<https://orcid.org/0000-0001-8681-3755>), Alain Ulazia [ctb, cph] (<https://orcid.org/0000-0002-4124-2853>)
Maintainer: Santos J. González-Rojí <santosjose.gonzalez@ehu.eus>
Description: A new diagram for the verification of vector variables (wind, current, etc) generated by multiple models against a set of observations is presented in this package. It has been designed as a generalization of the Taylor diagram to two dimensional quantities. It is based on the analysis of the two-dimensional structure of the mean squared error matrix between model and observations. The matrix is divided into the part corresponding to the relative rotation and the bias of the empirical orthogonal functions of the data. The full set of diagnostics produced by the analysis of the errors between model and observational vector datasets comprises the errors in the means, the analysis of the total variance of both datasets, the rotation matrix corresponding to the principal components in observation and model, the angle of rotation of model-derived empirical orthogonal functions respect to the ones from observations, the standard deviation of model and observations, the root mean squared error between both datasets and the squared two-dimensional correlation coefficient. See the output of function UVError() in this package.
Depends: R (>= 3.5.0)
License: GPL-3
Repository: CRAN
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-10-10 12:05:37 UTC; Santitxu
Date/Publication: 2019-10-11 11:40:05 UTC

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New package GRPtests with initial version 0.1.0
Package: GRPtests
Type: Package
Title: Goodness-of-Fit Tests in High-Dimensional GLMs
Version: 0.1.0
Date: 2019-09-14
Author: Jana Jankova [aut, cre], Rajen Shah [aut], Peter Buehlmann [aut], Richard Samworth [aut]
Maintainer: Jana Jankova <jana.jankova@gmail.com>
Description: Methodology for testing nonlinearity in the conditional mean function in low- or high-dimensional generalized linear models, and the significance of (potentially large) groups of predictors. Details on the algorithms can be found in the paper by Jankova, Shah, Buehlmann and Samworth (2019) <arXiv:1908.03606>.
License: GPL
Imports: glmnet, randomForest, MASS, stats, RPtests
Suggests: xyz
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-10 14:50:53 UTC; janajankova
Repository: CRAN
Date/Publication: 2019-10-11 12:00:04 UTC

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New package chlorpromazineR with initial version 0.1.2
Package: chlorpromazineR
Title: Convert Antipsychotic Doses to Chlorpromazine Equivalents
Version: 0.1.2
Authors@R: c(person("Eric", "Brown", role = c("aut", "cre"), email = "eb@ericebrown.com", comment = c(ORCID = "0000-0002-1575-2606")), person("Parita", "Shah", role = "aut", comment = c(ORCID = "0000-0002-7302-0411")), person("Julia", "Kim", role = "aut", comment = c(ORCID = "0000-0002-0379-1333")), person("Frederick", "Boehm", role = "rev", comment = c(ORCID = "0000-0002-1644-5931")))
Description: As different antipsychotic medications have different potencies, the doses of different medications cannot be directly compared. Various strategies are used to convert doses into a common reference so that comparison is meaningful. Chlorpromazine (CPZ) has historically been used as a reference medication into which other antipsychotic doses can be converted, as "chlorpromazine-equivalent doses". Using conversion keys generated from widely-cited scientific papers (Gardner et. al 2010 <doi:10.1176/appi.ajp.2009.09060802>, Leucht et al. 2016 <doi:10.1093/schbul/sbv167>), antipsychotic doses are converted to CPZ (or any specified antipsychotic) equivalents. The use of the package is described in the included vignette. Not for clinical use.
URL: https://github.com/ropensci/chlorpromazineR
BugReports: https://github.com/ropensci/chlorpromazineR/issues
Depends: R (>= 3.5)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-10 15:55:55 UTC; ericbrown
Author: Eric Brown [aut, cre] (<https://orcid.org/0000-0002-1575-2606>), Parita Shah [aut] (<https://orcid.org/0000-0002-7302-0411>), Julia Kim [aut] (<https://orcid.org/0000-0002-0379-1333>), Frederick Boehm [rev] (<https://orcid.org/0000-0002-1644-5931>)
Maintainer: Eric Brown <eb@ericebrown.com>
Repository: CRAN
Date/Publication: 2019-10-11 12:00:02 UTC

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New package pedtools with initial version 0.9.0
Package: pedtools
Type: Package
Title: Creating and Working with Pedigrees and Marker Data
Version: 0.9.0
Authors@R: person("Magnus Dehli", "Vigeland", email = "m.d.vigeland@medisin.uio.no", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9134-4962"))
Description: A lightweight, but comprehensive collection of tools for creating, manipulating and visualising pedigrees and genetic marker data. Pedigrees can be read from text files or created on the fly with built-in functions. A range of utilities enable modifications like adding or removing individuals, breaking loops, and merging pedigrees. Pedigree plots are produced by wrapping the plotting functionality of the 'kinship2' package.
License: GPL-3
URL: https://github.com/magnusdv/pedtools
Encoding: UTF-8
Language: en-GB
LazyData: true
Imports: kinship2
Suggests: testthat, igraph, knitr, rmarkdown, pedmut, kableExtra
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-09 21:16:29 UTC; magnusdv
Author: Magnus Dehli Vigeland [aut, cre] (<https://orcid.org/0000-0002-9134-4962>)
Maintainer: Magnus Dehli Vigeland <m.d.vigeland@medisin.uio.no>
Repository: CRAN
Date/Publication: 2019-10-11 11:00:02 UTC

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New package fgdr with initial version 1.0.0
Package: fgdr
Title: Utilities for Fundamental Geo-Spatial Data
Version: 1.0.0
Authors@R: c( person(given = "Shinya", family = "Uryu", email = "suika1127@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0493-6186")) )
Description: Read and Parse for Fundamental Geo-Spatial Data (FGD) which downloads XML file from providing site (<https://fgd.gsi.go.jp/download/menu.php>). The JPGIS format file provided by FGD so that it can be handled as an R spatial object such as 'sf' and 'raster' or 'stars'. Supports the FGD version 4.1, and accepts fundamental items and digital elevation models.
License: MIT + file LICENSE
Imports: jpmesh (>= 1.1.1), magrittr (>= 1.5), purrr (>= 0.2.5), raster (>= 2.6.7), readr (>= 1.3.1), rlang (>= 0.2.2), sf (>= 0.6.3), sp (>= 1.3.1), stars (>= 0.3-1), stringr (>= 1.3.1), tibble (>= 1.4.2), xml2 (>= 1.2.0)
Encoding: UTF-8
LazyData: true
URL: https://github.com/uribo/fgdr
BugReports: https://github.com/uribo/fgdr/issues
RoxygenNote: 6.1.1
Suggests: covr, roxygen2 (>= 6.1.1), testthat
Depends: R (>= 3.1)
NeedsCompilation: no
Packaged: 2019-10-09 22:51:41 UTC; suryu
Author: Shinya Uryu [aut, cre] (<https://orcid.org/0000-0002-0493-6186>)
Maintainer: Shinya Uryu <suika1127@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-11 10:30:03 UTC

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New package dynwrap with initial version 1.1.4
Package: dynwrap
Type: Package
Title: Representing and Inferring Single-Cell Trajectories
Description: Provides functionality to infer trajectories from single-cell data, represent them into a common format, and adapt them. Other biological information can also be added, such as cellular grouping, RNA velocity and annotation. Saelens et al. (2019) <doi:10.1038/s41587-019-0071-9>.
Version: 1.1.4
Authors@R: c( person( "Robrecht", "Cannoodt", email = "rcannood@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3641-729X", github = "rcannood") ), person( "Wouter", "Saelens", email = "wouter.saelens@ugent.be", role = c("aut"), comment = c(ORCID = "0000-0002-7114-6248", github = "zouter") ) )
URL: https://github.com/dynverse/dynwrap
BugReports: https://github.com/dynverse/dynwrap/issues
License: GPL-3
LazyData: TRUE
RoxygenNote: 6.1.1
Encoding: UTF-8
Depends: R (>= 3.0.0)
Imports: assertthat, babelwhale, dplyr, dynutils (>= 1.0.3), dynparam, FNN, hdf5r, igraph, glue, jsonlite, magrittr, Matrix, methods, purrr, processx, readr, stringr, reshape2, testthat, tibble, tidyr, yaml, crayon
Suggests: curl, devtools, dyndimred, ggplot2, knitr, lhs, pkgload, ranger, rmarkdown, viridis
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-10 15:34:51 UTC; rcannood
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [aut] (<https://orcid.org/0000-0002-7114-6248>, zouter)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-11 10:40:02 UTC

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New package BlythStillCasellaCI with initial version 1.0.0
Package: BlythStillCasellaCI
Title: Blyth-Still-Casella Exact Binomial Confidence Intervals
Version: 1.0.0
Authors@R: c( person("Ron", "Yu", email = "ronyu5135@gmail.com", role = c("aut", "cre")), person("Peiwen", "Wu", email = "pwu.stat@gmail.com", role = "aut"))
Description: Computes Blyth-Still-Casella exact binomial confidence intervals based on a refining procedure proposed by George Casella (1986) <doi:10.2307/3314658>.
Depends: R (>= 3.2.0)
License: GPL-3
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-10-09 16:21:10 UTC; pwu01
Author: Ron Yu [aut, cre], Peiwen Wu [aut]
Maintainer: Ron Yu <ronyu5135@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-11 10:30:06 UTC

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New package xlsx2dfs with initial version 0.1.0
Package: xlsx2dfs
Type: Package
Title: Read and Write 'Excel' Sheets into and from List of Data Frames
Version: 0.1.0
Authors@R: person("Gwang-Jin", "Kim", email = "gwang.jin.kim.phd@gmail.com", role = c("aut", "cre"))
Maintainer: Gwang-Jin Kim <gwang.jin.kim.phd@gmail.com>
Description: Reading and writing sheets of a single 'Excel' file into and from a list of data frames. Eases I/O of tabular data in bioinformatics while keeping them in a human readable format.
Depends: openxlsx
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-10 08:40:32 UTC; josephus
Author: Gwang-Jin Kim [aut, cre]
Repository: CRAN
Date/Publication: 2019-10-11 09:10:02 UTC

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New package varycoef with initial version 0.2.9
Package: varycoef
Type: Package
Title: Varying Coefficients
Version: 0.2.9
Authors@R: c(person("Jakob", "Dambon", role = c("aut", "cre"), email = "jakob.dambon@math.uzh.ch"), person("Fabio", "Sigrist", role = c("ctb")), person("Reinhard", "Furrer", role = c("ctb")))
Depends: spam
Imports: fields, methods, sp, RandomFields
Suggests: tmap, knitr, rmarkdown, microbenchmark
Description: Gives maximum likelihood estimation (MLE) method to estimate and predict spatially varying coefficient (SVC) Models. It supports covariance tapering by Furrer et al. (2006) <doi:10.1198/106186006X132178> to allow MLE on large data.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-10 12:50:06 UTC; jdambo
Author: Jakob Dambon [aut, cre], Fabio Sigrist [ctb], Reinhard Furrer [ctb]
Maintainer: Jakob Dambon <jakob.dambon@math.uzh.ch>
Repository: CRAN
Date/Publication: 2019-10-11 09:20:02 UTC

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New package nhm with initial version 0.1.0
Package: nhm
Type: Package
Title: Non-Homogeneous Markov and Hidden Markov Multistate Models
Version: 0.1.0
Authors@R: person("Andrew", "Titman", role=c("aut", "cre"), email = "a.titman@lancaster.ac.uk")
Maintainer: Andrew Titman <a.titman@lancaster.ac.uk>
Description: Fits non-homogeneous Markov multistate models and misclassification-type hidden Markov models in continuous time to intermittently observed data. Implements the methods in Titman (2011) <doi:10.1111/j.1541-0420.2010.01550.x>. Uses direct numerical solution of the Kolmogorov forward equations to calculate the transition probabilities.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: stats, deSolve, maxLik, mvtnorm
Suggests: msm, parallel, splines
NeedsCompilation: yes
Packaged: 2019-10-10 11:14:34 UTC; andre
Author: Andrew Titman [aut, cre]
Repository: CRAN
Date/Publication: 2019-10-11 09:10:05 UTC

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New package mnj with initial version 1.0
Package: mnj
Title: Machine Learning and Judgement
Version: 1.0
Authors@R: person(given = "Yong-Seok", family = "Jeon", role = c("aut","cre"), email = "flywade@skku.edu")
Description: Perform FlexBoost in R. FlexBoost is a newly suggested algorithm based on AdaBoost by adjusting adaptive loss functions. Not only FlexBoost but also other machine learning algorithms (e.g. Support Vector Machines) will be added. For more details on FlexBoost see Jeon, Y. S., Yang, D. H., & Lim, D. J. (2019) <doi:10.1109/access.2019.2938356>.
Imports: rpart(>= 4.1-15)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-10 10:01:30 UTC; jeon
Author: Yong-Seok Jeon [aut, cre]
Maintainer: Yong-Seok Jeon <flywade@skku.edu>
Repository: CRAN
Date/Publication: 2019-10-11 09:10:08 UTC

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New package LogrankPower with initial version 1.0.0
Package: LogrankPower
Type: Package
Title: Log-Rank Test Power Calculation
Version: 1.0.0
Date: 2019-10-10
Author: Rong Lu
Maintainer: Rong Lu <rong.lu@utsw.edu>
Depends: R (>= 2.15.0), survival, survminer
Description: Power of the log-rank test is estimated using simulation datasets, with user specified total sample size (in one simulation dataset), type I error, effect size, the total number of simulation datasets, sample size ratio between two comparison groups, the death rate in the reference group, and the distribution of follow-up time (simulated from a negative binomial distribution). Method reference: Hogg, R. V., McKean, J., and Craig, A. T. (2004, ISBN 10: 0130085073). <https://github.com/RongUTSW/Methods/blob/master/LRPowerSimulation.pdf>.
License: GPL-2
NeedsCompilation: no
Packaged: 2019-10-10 15:10:41 UTC; ronglu
Repository: CRAN
Date/Publication: 2019-10-11 09:20:08 UTC

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New package locStra with initial version 1.0
Package: locStra
Type: Package
Title: Fast Implementation of (Local) Population Stratification Methods
Version: 1.0
Date: 2019-10-07
Author: Georg Hahn [aut,cre], Sharon M. Lutz [ctb], Christoph Lange [ctb]
Maintainer: Georg Hahn <ghahn@hsph.harvard.edu>
Description: Fast and fully sparse 'cpp' implementations to compute the genetic covariance matrix, the genomic relationship matrix, the Jaccard matrix, and the s-matrix of an input matrix. Full support for sparse matrices from the R-package 'Matrix'. Additionally, a 'cpp' implementation of the power method (von Mises iteration) algorithm to compute the largest eigenvector of a matrix is included, and a function to compute sliding windows.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.13), Rdpack, Matrix
RdMacros: Rdpack
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-10-10 16:02:05 UTC; acer
Repository: CRAN
Date/Publication: 2019-10-11 09:20:05 UTC

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New package linearOrdering with initial version 1.0.0
Package: linearOrdering
Type: Package
Title: Methods of Linear Ordering of Data
Version: 1.0.0
Authors@R: person("Antoni", "Baum", email = "antoni.baum@protonmail.com", role = c("aut", "cre"))
Description: Provides various methods of linear ordering of data. Supports weights and positive/negative impacts. Currently included methods: * Sum of ranks * Standardized sums * Hellwig's (Hellwig, 1968, <https://unesdoc.unesco.org/ark:/48223/pf0000158559.locale=en>) * TOPSIS (Yoon & Hwang, 1981, ISBN:978-3-642-48318-9).
URL: https://github.com/Yard1/linearOrdering
BugReports: https://github.com/Yard1/linearOrdering/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-10 00:08:53 UTC; baum
Author: Antoni Baum [aut, cre]
Maintainer: Antoni Baum <antoni.baum@protonmail.com>
Repository: CRAN
Date/Publication: 2019-10-11 09:30:02 UTC

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New package GWASbyCluster with initial version 0.1.7
Package: GWASbyCluster
Type: Package
Title: Identifying Significant SNPs in Genome Wide Association Studies (GWAS) via Clustering
Version: 0.1.7
Date: 2019-10-09
Author: Yan Xu, Li Xing, Jessica Su, Xuekui Zhang<UBC.X.Zhang@gmail.com>, Weiliang Qiu <Weiliang.Qiu@gmail.com>
Maintainer: Li Xing <sfulxing@gmail.com>
Depends: R (>= 3.5.0), Biobase
Imports: stats, snpStats, methods, rootSolve, limma
Description: Identifying disease-associated significant SNPs using clustering approach. This package is implementation of method proposed in Xu et al (2019) <DOI:10.1038/s41598-019-50229-6>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-10-10 01:10:31 UTC; weiliangqiu
Repository: CRAN
Date/Publication: 2019-10-11 09:30:06 UTC

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New package labelmachine with initial version 1.0.0
Package: labelmachine
Title: Make Labeling of R Data Sets Easy
Version: 1.0.0
Authors@R: person(given = "Adrian", family = "Maldet", role = c("aut", "cre"), email = "maldet@posteo.at")
Description: Assign meaningful labels to data frame columns. 'labelmachine' manages your label assignment rules in 'yaml' files and makes it easy to use the same labels in multiple projects.
Depends: R (>= 3.5.0)
Imports: yaml (>= 2.2.0)
Suggests: testthat (>= 2.1.0), roxygen2 (>= 6.1.1), magrittr (>= 1.5), rlang (>= 0.4.0), covr, knitr, rmarkdown
Encoding: UTF-8
VignetteBuilder: knitr
RoxygenNote: 6.1.1
License: GPL-3
URL: https://a-maldet.github.io/labelmachine, https://github.com/a-maldet/labelmachine
BugReports: https://github.com/a-maldet/labelmachine/issues
Collate: 'composerr.R' 'imports.R' 'utilities.R' 'lama_dictionary.R' 'lama_merge.R' 'lama_mutate.R' 'lama_read.R' 'lama_select.R' 'lama_rename.R' 'lama_translate.R' 'lama_translate_all.R' 'lama_write.R' 'lappli.R'
NeedsCompilation: no
Packaged: 2019-10-08 08:58:31 UTC; maldet
Author: Adrian Maldet [aut, cre]
Maintainer: Adrian Maldet <maldet@posteo.at>
Repository: CRAN
Date/Publication: 2019-10-11 07:30:03 UTC

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Thu, 10 Oct 2019

New package BivRegBLS with initial version 1.1.1
Package: BivRegBLS
Type: Package
Title: Tolerance Interval and EIV Regression - Method Comparison Studies
Version: 1.1.1
Date: 2019-10-10
Authors@R: c(person(given="Bernard G",family="Francq",email="BivRegBLS@gmail.com",role=c("cre","aut")),person(given="Marion",family="Berger",email="marion.berger@sanofi.com",role=c("aut")),person(given="Christophe",family="Agut",role=c("ctb")), person(given="Guy",family="Mathieu",role=c("ctb")), person(given="Armand",family="Berges",role=c("ctb")), person(given="Franck",family="Pellissier",role=c("ctb")), person(given="Veronique",family="Onado",role=c("ctb")))
Maintainer: Bernard G Francq <BivRegBLS@gmail.com>
Description: Assess the agreement in method comparison studies by tolerance intervals and errors-in-variables (EIV) regressions. The Ordinary Least Square regressions (OLSv and OLSh), the Deming Regression (DR), and the (Correlated)-Bivariate Least Square regressions (BLS and CBLS) can be used with unreplicated or replicated data. The BLS() and CBLS() are the two main functions to estimate a regression line, while XY.plot() and MD.plot() are the two main graphical functions to display, respectively an (X,Y) plot or (M,D) plot with the BLS or CBLS results. Four hyperbolic statistical intervals are provided: the Confidence Interval (CI), the Confidence Bands (CB), the Prediction Interval and the Generalized prediction Interval. Assuming no proportional bias, the (M,D) plot (Band-Altman plot) may be simplified by calculating univariate tolerance intervals (beta-expectation (type I) or beta-gamma content (type II)). Major updates from last version 1.0.0 are: title shortened, include the new functions BLS.fit() and CBLS.fit() as shortcut of the, respectively, functions BLS() and CBLS(). References: B.G. Francq, B. Govaerts (2016) <doi:10.1002/sim.6872>, B.G. Francq, B. Govaerts (2014) <doi:10.1016/j.chemolab.2014.03.006>, B.G. Francq, B. Govaerts (2014) <http://publications-sfds.fr/index.php/J-SFdS/article/view/262>, B.G. Francq (2013), PhD Thesis, UCLouvain, Errors-in-variables regressions to assess equivalence in method comparison studies, <https://dial.uclouvain.be/pr/boreal/object/boreal%3A135862/datastream/PDF_01/view>.
Depends: R (>= 3.1.0), ellipse
License: AGPL-3
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-10-10 21:02:59 UTC; Bernard
Author: Bernard G Francq [cre, aut], Marion Berger [aut], Christophe Agut [ctb], Guy Mathieu [ctb], Armand Berges [ctb], Franck Pellissier [ctb], Veronique Onado [ctb]
Repository: CRAN
Date/Publication: 2019-10-10 22:40:06 UTC

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New package SwimmeR with initial version 0.1.0.0
Package: SwimmeR
Title: Formatting and Conversions for Swimming Times
Version: 0.1.0.0
Authors@R: person(given = "Greg", family = "Pilgrim", role = c("aut", "cre"), email = "gpilgrim2670@gmail.com")
Description: There are two goals for 'SwimmeR' as presently constructed. First, it converts swimming times (performances) between the computationally useful format of seconds, reported to the 100ths place (eg 95.37) and the conventional reporting format (1:35.37) used in the swimming community. Secondly 'SwimmeR' converts times between the various pool sizes used in competitive swimming, namely 50m length (LCM), 25m length (SCM) and 25y length (SCY).
License: MIT + file LICENSE
Imports: purrr, dplyr, stringr, tibble, utils
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2019-10-09 12:12:00 UTC; gpilgrim
Author: Greg Pilgrim [aut, cre]
Maintainer: Greg Pilgrim <gpilgrim2670@gmail.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-10-10 14:40:03 UTC

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New package simTargetCov with initial version 1.0
Package: simTargetCov
Type: Package
Title: Data Transformation or Simulation with Empirical Covariance Matrix
Version: 1.0
Date: 2019-10-02
Author: Anthony Christidis <anthony.christidis@stat.ubc.ca>, Stefan Van Aelst <stefan.vanaelst@kuleuven.be>, Ruben Zamar <ruben@stat.ubc.ca>
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>
Description: Transforms or simulates data with a target empirical covariance matrix supplied by the user. The method to obtain the data with the target empirical covariance matrix is described in Section 5.1 of Christidis, Van Aelst and Zamar (2019) <arXiv:1812.05678>.
License: GPL (>= 2)
Biarch: true
Imports: MASS, stats
Depends:
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-10-07 19:10:24 UTC; antho
Repository: CRAN
Date/Publication: 2019-10-10 13:30:02 UTC

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New package MatchThem with initial version 0.8.1
Package: MatchThem
Title: Matching Multiply Imputed Datasets
Description: Provides the necessary tools for the pre-processing technique of matching in multiply imputed datasets, to improve the robustness and transparency of deriving causal inferences from studying these datasets. This package includes functions to perform propensity score matching within or across the imputed datasets as well as to estimate weights (including inverse propensity score weights) of observations, to analyze each matched or weighted datasets using parametric or non-parametric statistical models, and to combine the obtained results from these models according to Rubin’s rules. Please see the package repository <https://github.com/FarhadPishgar/MatchThem> for details.
Version: 0.8.1
Authors@R: c(person("Farhad", "Pishgar", role = c("aut","cre"), email = "Farhad.Pishgar@Gmail.com"), person("Clémence", "Leyrat", role = "ctb", email = "Clemence.Leyrat@lshtm.ac.uk"))
Maintainer: Farhad Pishgar <Farhad.Pishgar@Gmail.com>
Depends: graphics, MatchIt, methods, mice, WeightIt, R (>= 3.5.0)
Imports: stats
Suggests: Amelia, cobalt
URL: https://github.com/FarhadPishgar/MatchThem
BugReports: https://github.com/FarhadPishgar/MatchThem/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-09 14:08:05 UTC; Farhad
Author: Farhad Pishgar [aut, cre], Clémence Leyrat [ctb]
Repository: CRAN
Date/Publication: 2019-10-10 13:40:02 UTC

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New package dodgr with initial version 0.2.5
Package: dodgr
Title: Distances on Directed Graphs
Version: 0.2.5
Authors@R: c( person("Mark", "Padgham", email="mark.padgham@email.com", role=c("aut", "cre")), person("Andreas", "Petutschnig", role="aut"), person("Robin", "Lovelace", role="ctb"), person("Andrew", "Smith", role="ctb"), person("Malcolm", "Morgan", role="ctb"), person("Shane", "Saunders", role="cph", comment="Original author of included code for priority heaps"))
Description: Distances on dual-weighted directed graphs using priority-queue shortest paths (Padgham (2019) <doi:10.32866/6945>). Weighted directed graphs have weights from A to B which may differ from those from B to A. Dual-weighted directed graphs have two sets of such weights. A canonical example is a street network to be used for routing in which routes are calculated by weighting distances according to the type of way and mode of transport, yet lengths of routes must be calculated from direct distances.
Depends: R (>= 3.5.0)
License: GPL-3
Imports: callr, digest, igraph, magrittr, methods, osmdata, Rcpp (>= 0.12.6), RcppParallel
Suggests: dplyr, geodist, ggplot2, igraphdata, jsonlite, knitr, purrr, rbenchmark, RColorBrewer, rmarkdown, roxygen2, scales, sf, testthat, tidygraph
LinkingTo: Rcpp, RcppParallel
SystemRequirements: C++11, GNU make
VignetteBuilder: knitr
NeedsCompilation: yes
Encoding: UTF-8
LazyData: true
URL: https://github.com/ATFutures/dodgr
BugReports: https://github.com/ATFutures/dodgr/issues
RoxygenNote: 6.1.1
Packaged: 2019-10-06 19:54:34 UTC; markus
Author: Mark Padgham [aut, cre], Andreas Petutschnig [aut], Robin Lovelace [ctb], Andrew Smith [ctb], Malcolm Morgan [ctb], Shane Saunders [cph] (Original author of included code for priority heaps)
Maintainer: Mark Padgham <mark.padgham@email.com>
Repository: CRAN
Date/Publication: 2019-10-10 14:00:02 UTC

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New package MEclustnet with initial version 1.2.2
Package: MEclustnet
Title: Fit the Mixture of Experts Latent Position Cluster Model to Network Data
Version: 1.2.2
Authors@R: c(person(given = "Isobel Claire", family = "Gormley", role = c("aut", "cre"), email = "claire.gormley@ucd.ie"), person(given = "Thomas Brendan", family = "Murphy", role = c("aut"), email = "brendan.murphy@ucd.ie"))
Description: Functions to facilitate model-based clustering of nodes in a network in a mixture of experts setting, which incorporates covariate information on the nodes in the modelling process. Isobel Claire Gormley and Thomas Brendan Murphy (2010) <doi:10.1016/j.stamet.2010.01.002>.
Imports: MASS, mvtnorm, nnet, ellipse, latentnet, vegan, e1071
Depends: R (>= 2.10)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-10 08:50:57 UTC; clairegormley
Author: Isobel Claire Gormley [aut, cre], Thomas Brendan Murphy [aut]
Maintainer: Isobel Claire Gormley <claire.gormley@ucd.ie>
Repository: CRAN
Date/Publication: 2019-10-10 11:50:05 UTC

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Wed, 09 Oct 2019

New package intePareto with initial version 0.0.1
Package: intePareto
Type: Package
Title: Integrative Analysis of RNA-Seq and ChIP-Seq Data
Version: 0.0.1
Date: 2019-10-08
Authors@R: person(given = "Yingying", family = "Cao", role = c("aut", "cre"), email = "yingying.cao@uni-due.de")
Description: Integrative analysis of gene expression (RNA-Seq data), and histone modification data for user-defined sets of histone marks (ChIP-Seq data) to discover consistent changes in genes between biological conditions. Additionally, Pareto optimization is used to prioritize genes based on the level of consistent changes in both RNA-Seq and ChIP-Seq data.
License: GPL (>= 2)
Depends: R (>= 3.6.0)
Imports: GenomicRanges, GenomeInfoDb, IRanges, GenomicAlignments, biomaRt, Rsamtools, rPref, DESeq2, apeglm
Suggests: knitr, rmarkdown
LazyLoad: yes
NeedsCompilation: no
ByteCompile: true
Encoding: UTF-8
Packaged: 2019-10-08 18:20:45 UTC; yingying
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Author: Yingying Cao [aut, cre]
Maintainer: Yingying Cao <yingying.cao@uni-due.de>
Repository: CRAN
Date/Publication: 2019-10-09 16:10:02 UTC

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New package DAFOT with initial version 0.0.1
Package: DAFOT
Title: Detector of Active Flow on a Tree
Version: 0.0.1
Date: 2019-10-7
Author: Shulei Wang, T. Tony Cai and Hongzhe Li
Maintainer: Shulei Wang <Shulei.Wang@pennmedicine.upenn.edu>
Description: Quantitative comparison of microbial composition from different populations is a fundamental task in various microbiome studies. The main goal of this package is to provide a new method for two-sample testing for microbial compositional data by leveraging the phylogenetic tree information. Empirical evidence from real data sets suggests that the phylogenetic microbial composition difference between two populations is usually sparse. Motivated by this observation, this package implements a new maximum type test, Detector of Active Flow on a Tree (DAFOT). It is shown that DAFOT is particularly powerful against sparse phylogenetic composition difference and enjoys certain optimality. Chen, J., Bittinger, K., Charlson, E. S., Hoffmann, C., Lewis, J., Wu, G. D., Collman, R. G., Bushman, F. D., Li, H. (2012) <doi:10.1093/bioinformatics/bts342>.
Imports: tidytree, stats, methods, gtools, tibble, ape
Suggests: metagenomeFeatures
License: MIT+file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
NeedsCompilation: no
Packaged: 2019-10-09 14:54:15 UTC; shuleiwang
Repository: CRAN
Date/Publication: 2019-10-09 16:20:02 UTC

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New package YPPE with initial version 1.0.0
Package: YPPE
Title: Yang and Prentice Model with Piecewise Exponential Baseline Distribution
Version: 1.0.0
Authors@R: person(given = "Fabio", family = "Demarqui", email = "fndemarqui@est.ufmg.br", role = c("aut", "cre"))
Description: Semiparametric modeling of lifetime data with crossing survival curves via Yang and Prentice model with piecewise exponential baseline distribution curves. Details about the model can be found in Demarqui and Mayrink (2019) <arXiv:1910.02406>. Model fitting carried out via likelihood-based and Bayesian approaches. The package also provides point and interval estimation for the crossing survival times.
License: GPL (>= 2)
URL: https://github.com/fndemarqui/YPPE
BugReports: https://github.com/fndemarqui/YPPE/issues
Encoding: UTF-8
LazyData: true
Biarch: true
Depends: R (>= 3.4.0), survival
Imports: methods, Formula, Rcpp (>= 0.12.0), rstan (>= 2.18.1), rstantools (>= 2.0.0)
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
Suggests: testthat
NeedsCompilation: yes
Packaged: 2019-10-08 12:27:58 UTC; fndemarqui
Author: Fabio Demarqui [aut, cre]
Maintainer: Fabio Demarqui <fndemarqui@est.ufmg.br>
Repository: CRAN
Date/Publication: 2019-10-09 15:20:05 UTC

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New package VARshrink with initial version 0.3.1
Package: VARshrink
Title: Shrinkage Estimation Methods for Vector Autoregressive Models
Version: 0.3.1
Authors@R: c( person("Namgil", "Lee", role = c("aut", "cre"), email = "namgil.lee@kangwon.ac.kr", comment = c(ORCID = "0000-0003-0593-9028")), person("Heon Young", "Yang", role = c("ctb"), email = "hyyang@kangwon.ac.kr"), person("Sung-Ho", "Kim", role = c("aut"), email = "sung-ho.kim@kaist.edu") )
Description: Vector autoregressive (VAR) model is a fundamental and effective approach for multivariate time series analysis. Shrinkage estimation methods can be applied to high-dimensional VAR models with dimensionality greater than the number of observations, contrary to the standard ordinary least squares method. This package is an integrative package delivering nonparametric, parametric, and semiparametric methods in a unified and consistent manner, such as the multivariate ridge regression in Golub, Heath, and Wahba (1979) <doi:10.2307/1268518>, a James-Stein type nonparametric shrinkage method in Opgen-Rhein and Strimmer (2007) <doi:10.1186/1471-2105-8-S2-S3>, and Bayesian estimation methods using noninformative and informative priors in Lee, Choi, and S.-H. Kim (2016) <doi:10.1016/j.csda.2016.03.007> and Ni and Sun (2005) <doi:10.1198/073500104000000622>.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: vars (>= 1.5.3), ars (>= 0.6), corpcor (>= 1.6.9), strucchange, stats, MASS, mvtnorm
Suggests: knitr, rmarkdown, rticles, kableExtra
URL: https://github.com/namgillee/VARshrink/
BugReports: https://github.com/namgillee/VARshrink/issues/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-07 13:31:17 UTC; namgi
Author: Namgil Lee [aut, cre] (<https://orcid.org/0000-0003-0593-9028>), Heon Young Yang [ctb], Sung-Ho Kim [aut]
Maintainer: Namgil Lee <namgil.lee@kangwon.ac.kr>
Repository: CRAN
Date/Publication: 2019-10-09 15:10:03 UTC

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New package rayrender with initial version 0.4.0
Package: rayrender
Type: Package
Title: Build and Raytrace 3D Scenes
Version: 0.4.0
Authors@R: c(person("Tyler", "Morgan-Wall", email = "tylermw@gmail.com", role = c("aut", "cph", "cre"), comment = c(ORCID = "0000-0002-3131-3814")), person("Syoyo", "Fujita", role=c("ctb", "cph")), person("Melissa", "O'Neill", email = "oneill@pcg-random.org", role = c("ctb", "cph")))
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>
Description: Render scenes using pathtracing. Build 3D scenes out of spheres, cubes, planes, disks, triangles, line segments, cylinders, ellipsoids, and 3D models in the 'Wavefront' OBJ file format. Supports several material types, textures, multicore rendering, and tone-mapping. Based on the "Ray Tracing in One Weekend" book series. Peter Shirley (2018) <https://raytracing.github.io>.
License: GPL-3
Copyright: file inst/COPYRIGHTS
Imports: Rcpp (>= 1.0.0), parallel, assertthat, tibble, magrittr, purrr, png, raster
LinkingTo: Rcpp, RcppThread, progress
URL: https://www.rayrender.net, https://github.com/tylermorganwall/rayrender
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-10-08 01:49:10 UTC; tyler
Author: Tyler Morgan-Wall [aut, cph, cre] (<https://orcid.org/0000-0002-3131-3814>), Syoyo Fujita [ctb, cph], Melissa O'Neill [ctb, cph]
Repository: CRAN
Date/Publication: 2019-10-09 15:30:02 UTC

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New package gwsem with initial version 0.1.2
Package: gwsem
Type: Package
Title: Genome-Wide Structural Equation Modeling
Version: 0.1.2
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)
Depends: R (>= 3.5), OpenMx (>= 2.14)
Imports: data.table, methods
Suggests: testthat (>= 2.1.0), MASS, covr, knitr, rmarkdown, qqman
RoxygenNote: 6.1.1
SystemRequirements: GNU make
URL: https://github.com/jpritikin/gwsem
BugReports: https://github.com/jpritikin/gwsem/issues
NeedsCompilation: yes
VignetteBuilder: knitr
Packaged: 2019-10-09 14:28:13 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: 2019-10-09 15:20:02 UTC

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New package forecastML with initial version 0.5.0
Package: forecastML
Type: Package
Title: Time Series Forecasting with Machine Learning Methods
Version: 0.5.0
Author: Nickalus Redell
Maintainer: Nickalus Redell <nickalusredell@gmail.com>
Description: The purpose of 'forecastML' is to simplify the process of multi-step-ahead direct forecasting with standard machine learning algorithms. 'forecastML' supports lagged, dynamic, static, and grouping features for modeling single and grouped time series. In addition, simple wrapper functions are used to support model-building with most R packages. This approach to forecasting is inspired by Bergmeir, Hyndman, and Koo's (2018) paper "A note on the validity of cross-validation for evaluating autoregressive time series prediction" <doi:10.1016/j.csda.2017.11.003>.
License: MIT + file LICENSE
URL: https://github.com/nredell/forecastML/
Encoding: UTF-8
LazyData: true
Imports: tidyr (>= 0.8.1), dplyr (>= 0.7.8), rlang (>= 0.4.0), magrittr (>= 1.5), stringr (>= 1.4.0), lubridate (>= 1.7.4), ggplot2 (>= 3.1.0), future.apply (>= 1.3.0), methods, purrr (>= 0.3.2)
RoxygenNote: 6.1.1
Collate: 'fill_gaps.R' 'create_windows.R' 'lagged_df.R' 'return_error.R' 'return_hyper.R' 'train_model.R' 'data_seatbelts.R' 'data_buoy.R' 'data_buoy_gaps.R'
Depends: R (>= 3.4.0)
Suggests: glmnet (>= 2.0.16), DT (>= 0.5), knitr (>= 1.22), rmarkdown (>= 1.12.6), xgboost (>= 0.82.1), randomForest (>= 4.6.14), testthat (>= 2.2.1), covr (>= 3.3.1)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-08 06:29:23 UTC; REDELLN
Repository: CRAN
Date/Publication: 2019-10-09 15:30:05 UTC

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New package ushr with initial version 0.1.0
Package: ushr
Type: Package
Title: Understanding Suppression of HIV
Version: 0.1.0
Date: 2019-09-26
Authors@R: c(person("Sinead E.", "Morris", role = c("aut", "cre"), email = "sinead.morris@columbia.edu", comment = c(ORCID = "0000-0001-8626-1698")), person("Luise", "Dziobek-Garrett", role = "ctb"), person("Andrew", "Yates", role = "ctb"))
Maintainer: Sinead E. Morris <sinead.morris@columbia.edu>
Description: Analyzes longitudinal data of HIV decline in patients on antiretroviral therapy using the canonical biphasic exponential decay model (pioneered, for example, by work in Perelson et al. (1997) <doi:10.1038/387188a0>; and Wu and Ding (1999) <doi:10.1111/j.0006-341X.1999.00410.x>). Model fitting and parameter estimation are performed, with additional options to calculate the time to viral suppression. Plotting and summary tools are also provided for fast assessment of model results.
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), stats
Suggests: knitr (>= 1.22), rmarkdown (>= 1.12), testthat (>= 2.2.0)
VignetteBuilder: knitr
URL: https://github.com/SineadMorris/ushr
NeedsCompilation: no
Packaged: 2019-10-08 01:42:18 UTC; sineadmorris
Author: Sinead E. Morris [aut, cre] (<https://orcid.org/0000-0001-8626-1698>), Luise Dziobek-Garrett [ctb], Andrew Yates [ctb]
Repository: CRAN
Date/Publication: 2019-10-09 15:00:02 UTC

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New package tfautograph with initial version 0.1.0
Package: tfautograph
Title: Autograph R for 'Tensorflow'
Version: 0.1.0
Authors@R: person("Tomasz", "Kalinowski", email = "kalinowskit@gmail.com", role = c("aut", "cre"))
Description: Translate R control flow expressions into 'Tensorflow' graphs.
SystemRequirements: TensorFlow (https://www.tensorflow.org/)
URL: https://t-kalinowski.github.io/tfautograph/
BugReports: https://github.com/t-kalinowski/tfautograph/issues
Depends: R (>= 3.5.0)
Imports: tensorflow, reticulate,
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: rlang, spelling, testthat (>= 2.1.0), knitr, tfdatasets, magrittr, rmarkdown, keras
Language: en-US
NeedsCompilation: no
Packaged: 2019-10-07 22:22:24 UTC; tomasz
Author: Tomasz Kalinowski [aut, cre]
Maintainer: Tomasz Kalinowski <kalinowskit@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-09 14:40:02 UTC

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New package simsl with initial version 0.1.0
Package: simsl
Type: Package
Title: Single-Index Models with a Surface-Link
Version: 0.1.0
Author: Park, H., Petkova, E., Tarpey, T., Ogden, R.T.
Maintainer: Hyung Park <parkh15@nyu.edu>
Description: An implementation of a single-index regression for optimizing individualized dose rules from an observational study. To model interaction effects between baseline covariates and a treatment variable defined on a continuum, we employ two-dimensional penalized spline regression on an index-treatment domain, where the index is defined as a linear combination of the covariates (a single-index). An unspecified main effect for the covariates is allowed. A unique contribution of this work is in the parsimonious single-index parametrization specifically defined for the interaction effect term. We refer to Park, Petkova, Tarpey, and Ogden (2020) <doi:10.1016/j.jspi.2019.05.008> (for the case of a discrete treatment) and Park, Petkova, Tarpey, and Ogden (2019) "A single-index model with a surface-link for optimizing individualized dose rules" (pre-print) for detail of the method. The main function of this package is simsl().
License: GPL-3
Imports: mgcv, stats
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-08 01:04:28 UTC; parkh15
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-10-09 14:50:06 UTC

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New package posterdown with initial version 1.0
Package: posterdown
Title: Generate PDF Conference Posters Using R Markdown
Version: 1.0
Authors@R: c(person(given = "Brent", family = "Thorne", role = c("aut", "cre"), email = "brent.thorne18@gmail.com", comment = c(ORCID = "0000-0002-1099-3857")), person(given = "Peter", family = "Higgins", role = "ctb"), person(given = "Shea", family = "Connell", role = "ctb"), person(given = "Luke", family = "Johnston", role = "ctb"))
Description: Use 'rmarkdown' and 'pagedown' to generate HTML and PDF conference posters.
License: MIT + file LICENSE
URL: https://github.com/brentthorne/posterdown
BugReports: https://github.com/brentthorne/posterdown/issues
Imports: pagedown, rmarkdown, yaml
Suggests: knitr
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-09 13:53:33 UTC; thornux
Author: Brent Thorne [aut, cre] (<https://orcid.org/0000-0002-1099-3857>), Peter Higgins [ctb], Shea Connell [ctb], Luke Johnston [ctb]
Maintainer: Brent Thorne <brent.thorne18@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-09 14:30:02 UTC

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New package mniw with initial version 1.0
Package: mniw
Type: Package
Title: The Matrix-Normal Inverse-Wishart Distribution
Version: 1.0
Date: 2019-10-06
Authors@R: c(person("Martin", "Lysy", role = c("aut", "cre"), email = "mlysy@uwaterloo.ca"), person("Bryan", "Yates", role = "aut"))
Description: Density evaluation and random number generation for the Matrix-Normal Inverse-Wishart (MNIW) distribution, as well as the the Matrix-Normal, Matrix-T, Wishart, and Inverse-Wishart distributions. Core calculations are implemented in a portable (header-only) C++ library, with matrix manipulations using the 'Eigen' library for linear algebra. Also provided is a Gibbs sampler for Bayesian inference on a random-effects model with multivariate normal observations.
URL: https://github.com/mlysy/mniw/
BugReports: https://github.com/mlysy/mniw/issues
License: GPL-3
Depends: R (>= 2.10)
Imports: Rcpp (>= 0.11.6)
LinkingTo: Rcpp, RcppEigen
LazyData: true
Suggests: testthat, knitr, rmarkdown
Encoding: UTF-8
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-10-09 13:43:27 UTC; mlysy
Author: Martin Lysy [aut, cre], Bryan Yates [aut]
Maintainer: Martin Lysy <mlysy@uwaterloo.ca>
Repository: CRAN
Date/Publication: 2019-10-09 14:20:02 UTC

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New package fpp3 with initial version 0.1
Package: fpp3
Title: Data for "Forecasting: Principles and Practice" (3rd Edition)
Version: 0.1
Authors@R: c(person(given = "Rob", family = "Hyndman", role = c("aut", "cre", "cph"), email = "Rob.Hyndman@monash.edu", comment = c(ORCID = "0000-0002-2140-5352")), person(given = "George", family = "Athanasopoulos", role = "ctb"), person(given = "Mitchell", family = "O'Hara-Wild", role = "ctb"), person(given = "RStudio", role = c("cph")))
Description: All data sets required for the examples and exercises in the book "Forecasting: principles and practice" by Rob J Hyndman and George Athanasopoulos <http://OTexts.org/fpp3/>. All packages required to run the examples are also loaded.
License: GPL-3
URL: https://github.com/robjhyndman/fpp3-package, https://OTexts.org/fpp3/
BugReports: https://github.com/robjhyndman/fpp3-package
Depends: R (>= 3.2)
Imports: cli (>= 1.0.0), crayon (>= 1.3.4), dplyr (>= 0.7.4), fable (>= 0.1.0), fabletools (>= 0.1.0), feasts (>= 0.0.0.9001), ggplot2 (>= 3.1.1), lubridate (>= 1.7.4), magrittr (>= 1.5), purrr (>= 0.2.4), rstudioapi (>= 0.7), tibble (>= 1.4.2), tidyr (>= 0.8.3), tsibble (>= 0.8.2), tsibbledata (>= 0.1.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-08 01:20:20 UTC; hyndman
Author: Rob Hyndman [aut, cre, cph] (<https://orcid.org/0000-0002-2140-5352>), George Athanasopoulos [ctb], Mitchell O'Hara-Wild [ctb], RStudio [cph]
Maintainer: Rob Hyndman <Rob.Hyndman@monash.edu>
Repository: CRAN
Date/Publication: 2019-10-09 15:00:05 UTC

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New package details with initial version 0.1.0
Package: details
Title: Create Details HTML Tag for Markdown and Package Documentation
Version: 0.1.0
Authors@R: person(given = "Jonathan", family = "Sidi", role = c("aut", "cre"), email = "yonicd@gmail.com")
Description: Create a details HTML tag around R objects to place in a Markdown, 'Rmarkdown' and 'roxygen2' documentation.
Depends: R (>= 3.2.0)
Imports: utils, clipr, magrittr, withr, xml2, httr, png
Suggests: sessioninfo, tibble, knitr, testthat, rmarkdown, covr
License: MIT + file LICENSE
URL: https://github.com/yonicd/details
BugReports: https://github.com/yonicd/details/issues
Encoding: UTF-8
LazyData: false
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-07 22:54:47 UTC; yonis
Author: Jonathan Sidi [aut, cre]
Maintainer: Jonathan Sidi <yonicd@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-09 14:50:13 UTC

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New package Ryacas0 with initial version 0.4.2
Package: Ryacas0
Version: 0.4.2
Title: Legacy 'Ryacas' (Interface to 'Yacas' Computer Algebra System)
Authors@R: c( person(given = "Mikkel Meyer", family = "Andersen", email = "mikl@math.aau.dk", role = c("aut", "cre", "cph")), person(given = "Rob", family = "Goedman", email = "goedman@mac.com", role = c("aut", "cph")), person(given = "Gabor", family = "Grothendieck", email = "ggrothendieck@gmail.com", role = c("aut", "cph")), person(given = "Søren", family = "Højsgaard", email = "sorenh@math.aau.dk", role = c("aut", "cph")), person(given = "Grzegorz", family = "Mazur", email = "teoretyk@gmail.com", role = c("aut", "cph")), person(given = "Ayal", family = "Pinkus", email = "apinkus@xs4all.nl", role = c("aut", "cph")), person(given = "Nemanja", family = "Trifunovic", role = c("cph"), comment = "UTF-8 part of yacas (src/yacas/include/yacas/utf8*)") )
Maintainer: Mikkel Meyer Andersen <mikl@math.aau.dk>
Encoding: UTF-8
Description: A legacy version of 'Ryacas', an interface to the 'yacas' computer algebra system (<http://www.yacas.org/>).
Depends: R (>= 3.3.0)
Imports: methods, Rcpp (>= 0.12.0), stats, settings, xml2
LinkingTo: Rcpp
Suggests: devtools, exams, knitr, Matrix, pkgload, rmarkdown, igraph, testthat
License: GPL-2
URL: https://github.com/mikldk/ryacas0, http://www.yacas.org
BugReports: https://github.com/mikldk/ryacas0/issues
RoxygenNote: 6.1.1.9000
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-10-07 20:06:49 UTC; mikl
Author: Mikkel Meyer Andersen [aut, cre, cph], Rob Goedman [aut, cph], Gabor Grothendieck [aut, cph], Søren Højsgaard [aut, cph], Grzegorz Mazur [aut, cph], Ayal Pinkus [aut, cph], Nemanja Trifunovic [cph] (UTF-8 part of yacas (src/yacas/include/yacas/utf8*))
Repository: CRAN
Date/Publication: 2019-10-09 13:40:02 UTC

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New package macs with initial version 1.0
Package: macs
Type: Package
Title: Recursive Partitioning Based Multivariate Adaptive Regression Models, Classification Trees, Survival Trees
Version: 1.0
Author: Heping Zhang, Yihao Lu, Haixu Ma, Mingliang Ma, Yidong Zhou, Qi Yu
Maintainer: Qi Yu <me@fredyu.net>
Description: Implements recursive partitioning based, nonparametric methods for high dimensional regression and classification. Depending on the aims of data analysis as well as the structures of the data, macs provides three major functions: multivariate adaptive regression models, classification trees and survival trees. A list of references for this package is, Zhang, H. (1997) <doi:10.1080/10618600.1997.10474728>, Zhang, H. et al. (1999) <ISBN:978-1-4757-3027-2>, Zhang, H. et al. (2014) <doi:10.1002/gepi.21843>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 0.12.17)
LinkingTo: Rcpp
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-10-07 19:49:45 UTC; Frederick Yu
Repository: CRAN
Date/Publication: 2019-10-09 13:30:03 UTC

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New package ltsspca with initial version 0.1.0
Package: ltsspca
Type: Package
Title: Sparse Principal Component Based on Least Trimmed Squares
Version: 0.1.0
Date: 2019-09-13
Authors@R: c( person(given="Yixin",family="Wang", role = c("aut","cre"), email="wangyixin07@outlook.com"), person(given="Stefan",family="Van Aelst", role = c("aut"), email="stefan.vanaelst@kuleuven.be"), person(given="Holger",family="Cevallos Valdiviezo",role=c("ctb"), comment = "Original R code for the LTS-PCA algorithm"), person(given="Tom",family="Reynkens",role=c("ctb"), comment = "Original R code for angle in the rospca package") )
Depends: R (>= 3.2.0)
Maintainer: Yixin Wang <wangyixin07@outlook.com>
Description: Implementation of robust and sparse PCA algorithm of Wang and Van Aelst (2019) <DOI:10.1080/00401706.2019.1671234>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: yes
VignetteBuilder: knitr
Suggests: robustbase, rrcov, stats, mvtnorm, graphics, knitr, rmarkdown, testthat
Imports: Rcpp (>= 1.0.1),pracma
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-10-07 19:44:19 UTC; wangy
Author: Yixin Wang [aut, cre], Stefan Van Aelst [aut], Holger Cevallos Valdiviezo [ctb] (Original R code for the LTS-PCA algorithm), Tom Reynkens [ctb] (Original R code for angle in the rospca package)
Repository: CRAN
Date/Publication: 2019-10-09 13:20:02 UTC

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New package miscIC with initial version 0.1.0
Package: miscIC
Type: Package
Title: Misclassified Interval Censored Time-to-Event Data
Version: 0.1.0
Authors@R: person("Andrew", "Titman", role=c("aut", "cre"), email = "a.titman@lancaster.ac.uk")
Description: Estimation of the survivor function for interval censored time-to-event data subject to misclassification using nonparametric maximum likelihood estimation, implementing the methods of Titman (2017) <doi:10.1007/s11222-016-9705-7>. Misclassification probabilities can either be specified as fixed or estimated. Models with time dependent misclassification may also be fitted.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: stats, nnls
NeedsCompilation: no
Packaged: 2019-10-07 16:57:20 UTC; andre
Author: Andrew Titman [aut, cre]
Maintainer: Andrew Titman <a.titman@lancaster.ac.uk>
Repository: CRAN
Date/Publication: 2019-10-09 13:00:02 UTC

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New package silicate with initial version 0.2.0
Package: silicate
Title: Common Forms for Complex Hierarchical and Relational Data Structures
Version: 0.2.0
Authors@R: c(person("Michael D.","Sumner", role = c("aut", "cre"), email = "mdsumner@gmail.com"), person("John", "Corbett", role = "ctb", comment = "the original inspiration"), person("Simon", "Wotherspoon", role = "ctb"), person("Kent", "Johnson", role = "dtc"), person("Mark", "Padgham", role = "aut") )
Description: Generate common data forms for complex data suitable for conversions and transmission by decomposition as paths or primitives. Paths are sequentially-linked records, primitives are basic atomic elements and both can model many forms and be grouped into hierarchical structures. The universal models 'SC0' (structural) and 'SC' (labelled, relational) are composed of edges and can represent any hierarchical form. Specialist models 'PATH', 'ARC' and 'TRI' provide the most common intermediate forms used for converting from one form to another. The methods are inspired by the simplicial complex <https://en.wikipedia.org/wiki/Simplicial_complex> and provide intermediate forms that relate spatial data structures to this mathematical construct.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: covr, knitr, rmarkdown, sp, testthat, trip, vdiffr
RoxygenNote: 6.1.1
Imports: dplyr, gibble (>= 0.2.0), methods, purrr, rlang, decido, tibble, unjoin (>= 0.0.3), geometry, tidyr (>= 1.0.0), grDevices, graphics, stats, magrittr, gridBase
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-07 14:27:46 UTC; mdsumner
Author: Michael D. Sumner [aut, cre], John Corbett [ctb] (the original inspiration), Simon Wotherspoon [ctb], Kent Johnson [dtc], Mark Padgham [aut]
Maintainer: Michael D. Sumner <mdsumner@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-09 11:30:02 UTC

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New package MUACz with initial version 1.0.0
Package: MUACz
Type: Package
Title: Generate MUAC z-Scores for School Children Aged 5-19 Years Old
Version: 1.0.0
Authors@R: c( person("Lazarus", "Mramba", email = "lmramba@gmail.com", role = c("aut", "cre")), person("James", "Berkley", email = "JBerkley@kemri-wellcome.org", role = "aut"))
Maintainer: Lazarus Mramba <lmramba@gmail.com>
Description: Generates mid upper arm circumference (MUAC) for age z-scores for children and adolescents aged 5 to 19 years that can be used to assess nutritional and health status and define risk of adverse health events. The standard growth reference constructed by Mramba et. al (2017) (<doi:10.1136/bmj.j3423>) smoothly join the WHO (2005) standards at age 5 years (<https://www.who.int/childgrowth/standards/Technical_report.pdf>) and has been validated against mortality risk among children and adolescents in Kenya, Uganda and Zimbabwe.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
Imports: epiDisplay, ggplot2, dplyr
SystemRequirements: GNU make
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-09 10:48:52 UTC; lmramba
Author: Lazarus Mramba [aut, cre], James Berkley [aut]
Repository: CRAN
Date/Publication: 2019-10-09 11:30:09 UTC

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New package lazyraster with initial version 0.5.0
Package: lazyraster
Version: 0.5.0
Title: Generate Raster Data Lazily from 'GDAL'
Description: Read raster data at a specified resolution on-demand via 'GDAL' (the Geospatial Data Abstraction Library <https://gdal.org/>). Augments the 'raster' package by never reading data from a raster source until necessary for generating an in-memory 'raster' object. A 'lazyraster' object may be cropped and converted to 'raster' object, and by default will only read a small amount of data sufficient for an overall summary. The amount of data read can be controlled by specifying the output dimensions.
Authors@R: person("Michael", "Sumner", email = "mdsumner@gmail.com", role = c("aut", "cre"))
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.1
Imports: graphics, raster, vapour (>= 0.4.0), methods, quadmesh (>= 0.4.0)
Suggests: palr, testthat (>= 2.1.0)
URL: https://github.com/hypertidy/lazyraster
BugReports: https://github.com/hypertidy/lazyraster/issues
NeedsCompilation: no
Packaged: 2019-10-07 11:57:45 UTC; mdsumner
Author: Michael Sumner [aut, cre]
Maintainer: Michael Sumner <mdsumner@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-09 11:10:02 UTC

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New package hypr with initial version 0.1.2
Package: hypr
Type: Package
Title: Hypothesis Matrix Translation
URL: https://maxrabe.com/hypr
BugReports: https://github.com/mmrabe/hypr/issues
Version: 0.1.2
Authors@R: c( person(given = "Maximilian M.", family = "Rabe", email = "maximilian.rabe@uni-potsdam.de", role = c("aut","cre")), person(given = "Shravan", family = "Vasishth", role = c("aut")), person(given = "Sven", family = "Hohenstein", role = c("aut")), person(given = "Reinhold", family = "Kliegl", email = "kliegl@uni-potsdam.de", role = c("aut")), person(given = "Daniel J.", family = "Schad", email = "schad@uni-potsdam.de", role = c("aut")))
Description: Translation between experimental null hypotheses, hypothesis matrices, and contrast matrices as used in linear regression models. The package is based on the method described in Schad, Vasishth, Hohenstein, and Kliegl (2019) <arXiv:1807.10451>.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: MASS, Matrix, pracma, methods, stats, rlang
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Collate: 'equations.R' 'hello.R' 'hypr.R'
NeedsCompilation: no
Packaged: 2019-10-07 13:32:52 UTC; max
Author: Maximilian M. Rabe [aut, cre], Shravan Vasishth [aut], Sven Hohenstein [aut], Reinhold Kliegl [aut], Daniel J. Schad [aut]
Maintainer: Maximilian M. Rabe <maximilian.rabe@uni-potsdam.de>
Repository: CRAN
Date/Publication: 2019-10-09 11:20:02 UTC

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New package ggVennDiagram with initial version 0.3
Package: ggVennDiagram
Type: Package
Title: A 'ggplot2' Implement of Venn Diagram
Version: 0.3
Authors@R: c( person("Chun-Hui","Gao",email="gaospecial@gmail.com",role=c("aut","cre"), comment=c(ORCID = "0000-0002-1445-7939")), person("Guangchuang", "Yu", email = "guangchuangyu@gmail.com", role = c("ctb"), comment = c(ORCID = "0000-0002-6485-8781")) )
Maintainer: Chun-Hui Gao <gaospecial@gmail.com>
Description: Easy-to-use functions to generate 2-4 sets Venn plot in publication quality. 'ggVennDiagram' is the first software that can automatically fill different colors to each part of a Venn diagram.
Depends: R (>= 3.5.0)
Imports: VennDiagram, sf, ggplot2, dplyr
URL: https://github.com/gaospecial/ggVennDiagram
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2019-10-07 01:34:38 UTC; gaosp
Author: Chun-Hui Gao [aut, cre] (<https://orcid.org/0000-0002-1445-7939>), Guangchuang Yu [ctb] (<https://orcid.org/0000-0002-6485-8781>)
Repository: CRAN
Date/Publication: 2019-10-09 11:40:02 UTC

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New package coil with initial version 1.0.0
Package: coil
Type: Package
Title: Contextualization and Evaluation of COI-5P Barcode Data
Version: 1.0.0
Author: Cameron M. Nugent
Maintainer: Cameron M. Nugent <nugentc@uoguelph.ca>
Description: Designed for the cleaning, contextualization and assessment of cytochrome c oxidase I DNA barcode data (COI-5P, or the five prime portion of COI). It contains functions for placing COI-5P barcode sequences into a common reading frame, translating DNA sequences to amino acids and for assessing the likelihood that a given barcode sequence includes an insertion or deletion error. The error assessment relies on the comparison of input sequences against nucleotide and amino acid profile hidden Markov models (for details see Durbin et al. 1998, ISBN: 9780521629713) trained on a taxonomically diverse set of reference sequences. The functions are provided as a complete pipeline and are also available individually for efficient and targeted analysis of barcode data.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R(>= 3.0.0)
Imports: ape, aphid, seqinr
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-07 12:58:25 UTC; cnuge
Repository: CRAN
Date/Publication: 2019-10-09 11:20:05 UTC

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New package PosteriorBootstrap with initial version 0.1.0
Package: PosteriorBootstrap
Title: Non-Parametric Sampling with Parallel Monte Carlo
Version: 0.1.0
Authors@R: c( person(given = "Simon", family = "Lyddon", role = c("aut"), email = "simon.lyddon@stats.ox.ac.uk"), person(given = "Miguel", family = "Morin", role = c("aut"), email = "info@turing.ac.uk"), person(given = "James", family = "Robinson", role = c("aut", "cre"), email = "james.em.robinson@gmail.com"), person("The Alan Turing Institute", role=c("cph"), email = "info@turing.ac.uk"))
Description: An implementation of a non-parametric statistical model using a parallelised Monte Carlo sampling scheme. The method implemented in this package allows non-parametric inference to be regularized for small sample sizes, while also being more accurate than approximations such as variational Bayes. The concentration parameter is an effective sample size parameter, determining the faith we have in the model versus the data. When the concentration is low, the samples are close to the exact Bayesian logistic regression method; when the concentration is high, the samples are close to the simplified variational Bayes logistic regression. The method is described in full in the paper Lyddon, Walker, and Holmes (2018), "Nonparametric learning from Bayesian models with randomized objective functions" <arXiv:1806.11544>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr (>= 0.7.4), e1071 (>= 1.7.1), ggplot2 (>= 3.1.1), gridExtra (>= 2.3), MASS (>= 7.3.51.1), Rcpp (>= 1.0.1), rstan (>= 2.18.2), utils (>= 3.4.3), StanHeaders (>= 2.18.1), tibble (>= 2.1.1)
Suggests: knitr (>= 1.21), lintr (>= 1.0.3), rmarkdown (>= 1.11), testthat (>= 2.0.1)
RoxygenNote: 6.1.1
VignetteBuilder: knitr
URL: https://github.com/alan-turing-institute/PosteriorBootstrap/
BugReports: https://github.com/alan-turing-institute/PosteriorBootstrap/issues
NeedsCompilation: no
Packaged: 2019-10-09 10:13:58 UTC; jrobinson
Author: Simon Lyddon [aut], Miguel Morin [aut], James Robinson [aut, cre], The Alan Turing Institute [cph]
Maintainer: James Robinson <james.em.robinson@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-09 11:00:02 UTC

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New package klassR with initial version 0.1.2
Package: klassR
Type: Package
Title: Classifications and Codelists for Statistics Norway
Version: 0.1.2
Author: Susie Jentoft, Lisa Li, Diana-Cristina Iancu
Maintainer: Susie Jentoft <susie.jentoft@ssb.no>
Description: Functions to search, retrieve and apply classifications and codelists using Statistics Norway's API <https://www.ssb.no/klass> from the system 'KLASS'. Retrieves classifications by date with options to choose language, hierarchical level and formatting.
Imports: tm, httr, jsonlite
BugReports: https://github.com/statisticsnorway/klassR/issues
License: Apache License 2.0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-01 12:37:59 UTC; coo
Repository: CRAN
Date/Publication: 2019-10-09 09:50:02 UTC

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New package CKAT with initial version 0.1.0
Package: CKAT
Type: Package
Title: Composite Kernel Association Test for Pharmacogenetics Studies
Version: 0.1.0
Author: Hong Zhang and Judong Shen
Maintainer: Hong Zhang <hzhang@wpi.edu>
Description: Composite Kernel Association Test (CKAT) is a flexible and robust kernel machine based approach to jointly test the genetic main effect and gene-treatment interaction effect for a set of single-nucleotide polymorphisms (SNPs) in pharmacogenetics (PGx) assessments embedded within randomized clinical trials.
License: GPL-2
Imports: stats, CompQuadForm
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-10-07 01:39:20 UTC; consi
Repository: CRAN
Date/Publication: 2019-10-09 09:20:02 UTC

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New package optimCheck with initial version 1.0
Package: optimCheck
Type: Package
Title: Graphical and Numerical Checks for Mode-Finding Routines
Version: 1.0
Date: 2019-10-06
Author: Martin Lysy
Maintainer: Martin Lysy <mlysy@uwaterloo.ca>
Description: Tools for checking that the output of an optimization algorithm is indeed at a local mode of the objective function. This is accomplished graphically by calculating all one-dimensional "projection plots" of the objective function, i.e., varying each input variable one at a time with all other elements of the potential solution being fixed. The numerical values in these plots can be readily extracted for the purpose of automated and systematic unit-testing of optimization routines.
URL: https://github.com/mlysy/optimCheck
BugReports: https://github.com/mlysy/optimCheck/issues
License: GPL-3
Imports: stats, graphics
RoxygenNote: 6.1.1
Encoding: UTF-8
Suggests: testthat, quantreg, mclust, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-06 18:18:06 UTC; mlysy
Repository: CRAN
Date/Publication: 2019-10-09 08:40:02 UTC

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New package nimbleEcology with initial version 0.1.0
Package: nimbleEcology
Type: Package
Title: Distributions for Ecological Models in 'nimble'
Version: 0.1.0
Maintainer: Benjamin R. Goldstein <ben.goldstein@berkeley.edu>
Authors@R: c(person("Benjamin R.", "Goldstein", role = c("aut", "cre"), email = "ben.goldstein@berkeley.edu"), person("Daniel", "Turek", role = "aut"), person("Lauren", "Ponisio", role = "aut"), person("Perry", "de Valpine", role = "aut"))
Date: 2019-09-24
Description: Common ecological distributions for 'nimble' models in the form of nimbleFunction objects. Includes Cormack-Jolly-Seber, occupancy, dynamic occupancy, hidden Markov, and dynamic hidden Markov models. (Jolly (1965) <doi:10.2307/2333826>, Seber (1965) <10.2307/2333827>, Turek et al. (2016) <doi:10.1007/s10651-016-0353-z>).
License: GPL-3
Copyright: Copyright (c) 2019, Perry de Valpine, Ben Goldstein, Daniel Turek, Lauren Ponisio
Depends: R (>= 3.4.0), nimble
Encoding: UTF-8
LazyData: true
URL: https://github.com/nimble-dev/nimbleEcology
Collate: dDynOcc.R dCJS.R dDHMM.R dHMM.R dOcc.R zzz.R
RoxygenNote: 6.1.1
Suggests: rmarkdown, testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2019-10-03 18:11:34 UTC; Ben
Author: Benjamin R. Goldstein [aut, cre], Daniel Turek [aut], Lauren Ponisio [aut], Perry de Valpine [aut]
Repository: CRAN
Date/Publication: 2019-10-09 08:40:07 UTC

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New package ipwCoxCSV with initial version 1.0
Package: ipwCoxCSV
Type: Package
Title: Inverse Probability Weighted Cox Model with Corrected Sandwich Variance
Version: 1.0
Date: 2019-09-16
Author: Di Shu <shudi1991@gmail.com>, Rui Wang <rwang@hsph.harvard.edu>
Maintainer: Di Shu <shudi1991@gmail.com>
Description: An implementation of corrected sandwich variance (CSV) estimation method for making inference of marginal hazard ratios (HR) in inverse probability weighted (IPW) Cox model without and with clustered data, proposed by Shu, Young, Toh, and Wang (2019) in their paper under revision for Biometrics. Both conventional inverse probability weights and stabilized weights are implemented. Logistic regression model is assumed for propensity score model.
License: GPL (>= 2)
Imports: survival, stats
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2019-10-06 18:39:09 UTC; dishu
Repository: CRAN
Date/Publication: 2019-10-09 08:50:03 UTC

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New package intdag with initial version 1.0.1
Package: intdag
Type: Package
Title: Reconstruction of a Directed Acyclic Graph with Interventions
Version: 1.0.1
Author: Si Peng, Xiaotong Shen, Wei Pan
Maintainer: Si Peng <pengx179@umn.edu>
Depends: R (>= 3.4.0)
Description: Provides intdag() for a constrained maximum likelihood estimate of a directed acyclic graph with intervention data. Also available is obsdag() for an estimate with observation data only, based on the method in the paper by Yuan, Shen and Pan (2018) <doi:10.1093/biomet/asy057>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-10-08 13:26:19 UTC; si
Repository: CRAN
Date/Publication: 2019-10-09 08:40:10 UTC

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New package gscaLCA with initial version 0.0.2
Package: gscaLCA
Type: Package
Title: Generalized Structure Component Analysis- Latent Class Analysis
Version: 0.0.2
Authors@R: c( person("Jihoon", "Ryoo", role = c("aut")), person("Seohee", "Park", email = "hee6904@gmail.com", role = c("aut", "cre")), person("Seoungeun", "Kim", role = c("aut")), person("heungsun", "Hwaung", role = c("aut")))
Description: Execute Latent Class Analysis (LCA) by using Generalized Structured Component Analysis (GSCA). This is explained in Ryoo, Park, and Kim (2009) <doi:10.1007/s41237-019-00084-6>. It estimates the parameters of latent class prevalence and item response probability in LCA with a single line comment. It also provide graphs of item response probabilities.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/hee6904/gscaLCA
Depends: R (>= 2.10)
Imports: gridExtra, ggplot2, stringr, progress, psych, fastDummies, fclust, MASS, devtools, foreach, doSNOW
Suggests: knitr, rmarkdown, R.rsp
RoxygenNote: 6.1.1.9000
NeedsCompilation: no
Packaged: 2019-10-06 21:38:27 UTC; Spenser
Author: Jihoon Ryoo [aut], Seohee Park [aut, cre], Seoungeun Kim [aut], heungsun Hwaung [aut]
Maintainer: Seohee Park <hee6904@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-09 09:00:02 UTC

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Tue, 08 Oct 2019

New package GMKMcharlie with initial version 1.0.3
Package: GMKMcharlie
Type: Package
Title: Unsupervised Gaussian Mixture and Minkowski K-Means
Version: 1.0.3
Author: Charlie Wusuo Liu
Maintainer: Charlie Wusuo Liu <liuwusuo@gmail.com>
Description: High performance trainers for parameterizing and clustering weighted data. The Gaussian mixture (GM) module includes the conventional EM (expectation maximization) trainer, the component-wise EM trainer, the minimum-message-length EM trainer by Figueiredo and Jain (2002) <doi:10.1109/34.990138>. These trainers accept additional constraints on mixture weights and covariance eigen ratios. The K-means (KM) module offers clustering with the options of (i) deterministic and stochastic K-means++ initializations, (ii) upper bounds on cluster weights (sizes), (iii) Minkowski distances, (iv) cosine dissimilarity, (v) dense and sparse representation of data input. The package improved the usual implementations of GM and KM training algorithms in various aspects. It is carefully crafted in multithreaded C++ for processing large data in industry use.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.0), RcppParallel
Suggests: MASS (>= 7.3.0), plot3D (>= 1.1.1)
LinkingTo: Rcpp, RcppParallel, RcppArmadillo
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2019-10-03 14:41:05 UTC; i56087
Repository: CRAN
Date/Publication: 2019-10-08 09:10:03 UTC

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Mon, 07 Oct 2019

New package egor with initial version 0.19.10
Package: egor
Type: Package
Title: Import and Analyse Ego-Centered Network Data
Version: 0.19.10
Date: 2019-10-06
Authors@R: c( person("Till", "Krenz", email = "egor@tillt.net", role = c("aut", "cre")), person("Pavel N.", "Krivitsky", email="pavel@uow.edu.au", role=c("aut")), person("Raffaele", "Vacca", email = "r.vacca@ufl.edu", role = c("aut")), person("Michal", "Bojanowski", email = "m.bojanowski at icm.edu.pl", role = c("aut")), person("Markus", "Gamper", email = "m.gamper@uni-koeln.de", role = c("ctb")), person("Andreas", "Herz", email = "herzand@uni-hildesheim.de", role = c("aut")), person("Christopher", "McCarty", email = "ufchris@ufl.edu", role = c("ctb")))
Description: Tools for importing, analyzing and visualizing ego-centered network data. Supports several data formats, including the export formats of 'EgoNet', 'EgoWeb 2.0' and 'openeddi'. An interactive (shiny) app for the intuitive visualization of ego-centered networks is provided. Also included are procedures for creating and visualizing Clustered Graphs (Lerner 2008 <DOI:10.1109/PACIFICVIS.2008.4475458>).
URL: https://github.com/tilltnet/egor, https://tilltnet.github.io/egor/
BugReports: https://github.com/tilltnet/egor/issues
License: AGPL-3
Depends: R (>= 2.10), dplyr, tibble
Imports: tidygraph, igraph, network, shiny, plyr, survey, tidyr, methods, utils, purrr, rlang
Suggests: knitr, testthat, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1.9000
LazyData: true
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-10-07 17:26:00 UTC; tillkrenz
Author: Till Krenz [aut, cre], Pavel N. Krivitsky [aut], Raffaele Vacca [aut], Michal Bojanowski [aut], Markus Gamper [ctb], Andreas Herz [aut], Christopher McCarty [ctb]
Maintainer: Till Krenz <egor@tillt.net>
Repository: CRAN
Date/Publication: 2019-10-07 22:10:06 UTC

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New package LHD with initial version 0.1.0
Package: LHD
Type: Package
Title: Latin Hypercube Designs (LHDs) Algorithms
Version: 0.1.0
Author: Hongzhi Wang, Qian Xiao, Abhyuday Mandal
Maintainer: Hongzhi Wang <hw34508@uga.edu>
Description: Contains functions for finding space-filling Latin Hypercube Designs (LHDs), e.g. maximin distance LHDs. Unlike other packages, our package is particularly useful in the area of Design and Analysis of Experiments (DAE). More specifically, it is very useful in design of computer experiments. One advantage of our package is its comprehensiveness. It contains a variety of heuristic algorithms (and their modifications) for searching maximin distance LHDs. In addition to that, it also contains other useful tools for developing and constructing maximin distance LHDs. In the future, algebraic construction methods will be added. Please refer to the function documentations for the detailed references of each function. Among all the references we used, one reference should be highlighted here, which is Ruichen Jin, Wei Chen, Agus Sudjianto (2005) <doi:10.1016/j.jspi.2004.02.014>. They provided a new form of phi_p criterion, which does not lose the space-filling property and simultaneously reduces the computational complexity when evaluating (or re-evaluating) an LHD. Their new phi_p criterion is a fundamental component of our many functions. Besides, the computation nature of the new phi_p criterion enables our functions to have less CPU time.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, devtools
Imports: stats
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-06 15:04:56 UTC; Hongzhi Wang
Repository: CRAN
Date/Publication: 2019-10-07 20:00:02 UTC

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New package unglue with initial version 0.0.1
Package: unglue
Title: Extract Matched Substrings Using a Pattern
Version: 0.0.1
Authors@R: person("Antoine", "Fabri", email = "antoine.fabri@gmail.com", role = c("aut", "cre"))
Description: Use syntax inspired by the package 'glue' to extract matched substrings in a more intuitive and compact way than by using standard regular expressions.
Depends: R (>= 3.1.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: glue, testthat (>= 2.1.0), rlang, covr, knitr, rmarkdown, magrittr
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-04 00:52:58 UTC; afabri
Author: Antoine Fabri [aut, cre]
Maintainer: Antoine Fabri <antoine.fabri@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-07 17:20:02 UTC

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New package traineR with initial version 1.0.0
Package: traineR
Type: Package
Title: Predictive Models Homologator
Version: 1.0.0
Authors@R: c( person("Oldemar", "Rodriguez R.", email = "oldemar.rodriguez@ucr.ac.cr", role = c("aut","cre")), person("Andres", "Navarro D.", role = c("ctb","prg")))
Depends: R (>= 3.5)
Imports: neuralnet (>= 1.44.2), rpart (>= 4.1-13), xgboost (>= 0.81.0.1), randomForest (>= 4.6-14), e1071 (>= 1.7-0.1), kknn (>= 1.3.1), dplyr (>= 0.8.0.1), ada (>= 2.0-5), nnet (>= 7.3-12), dummies (>= 1.5.6), stringr (>= 1.4.0)
Suggests: knitr, rmarkdown, rpart.plot
Description: Methods to unify the different ways of creating predictive models and their different predictive formats. It includes methods such as K-Nearest Neighbors, Decision Trees, ADA Boosting, Extreme Gradient Boosting, Random Forest, Neural Networks, Deep Learning, Support Vector Machines and Bayesian Methods.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
URL: http://www.promidat.com
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-04 19:44:01 UTC; promidat04
Author: Oldemar Rodriguez R. [aut, cre], Andres Navarro D. [ctb, prg]
Maintainer: Oldemar Rodriguez R. <oldemar.rodriguez@ucr.ac.cr>
Repository: CRAN
Date/Publication: 2019-10-07 17:20:05 UTC

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New package IPDFileCheck with initial version 0.3.0
Package: IPDFileCheck
Type: Package
Title: File Checking
Version: 0.3.0
Author: Sheeja Manchira Krishnan
Maintainer: Sheeja Manchira Krishnan <sheejamk@gmail.com>
Description: Checks files for existence, read access and checks individual columns for formats. Currently implemented for gender and age formats.
Imports: dplyr, testthat (>= 1.0.2), GlobalOptions (>= 0.1.0), lubridate, eeptools
License: CC0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-05 12:13:56 UTC; SheejaMK
Repository: CRAN
Date/Publication: 2019-10-07 17:30:02 UTC

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New package ggmsa with initial version 0.0.1
Package: ggmsa
Title: Plot Multiple Sequence Alignment using 'ggplot2'
Version: 0.0.1
Authors@R: c( person("Guangchuang", "Yu", email = "guangchuangyu@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-6485-8781")), person("Lang", "Zhou", email = "nyzhoulang@gmail.com", role = "aut"), person("Huina", "Huang", email = "1185796994@qq.com", role = "ctb"))
Description: Supports visualizing multiple sequence alignment of DNA and protein sequences using 'ggplot2'. It supports a number of colour schemes, including Chemistry, Clustal, Shapely, Taylor and Zappo. Multiple sequence alignment can easily be combined with other 'ggplot2' plots, such as aligning a phylogenetic tree produced by 'ggtree' with multiple sequence alignment.
Depends: R (>= 3.5.0)
Imports: ggplot2, ggseqlogo, magrittr, tidyr, treeio, utils
Suggests: Biostrings
License: Artistic-2.0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-06 02:40:20 UTC; ygc
Author: Guangchuang Yu [aut, cre] (<https://orcid.org/0000-0002-6485-8781>), Lang Zhou [aut], Huina Huang [ctb]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-07 17:50:02 UTC

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New package elfDistr with initial version 1.0.0
Package: elfDistr
Title: Kumaraswamy Complementary Weibull Geometric (Kw-CWG) Probability Distribution
Version: 1.0.0
Authors@R: c( person(given = "Matheus H. J.", family = "Saldanha", role = c("aut", "cre"), email = "mhjsaldanha@gmail.com"), person(given = "Adriano K.", family = "Suzuki", role = c("aut"), email = "suzuki@icmc.usp.br") )
Description: Density, distribution function, quantile function and random generation for the Kumaraswamy Complementary Weibull Geometric (Kw-CWG) lifetime probability distribution proposed in Afify, A.Z. et al (2017) <doi:10.1214/16-BJPS322>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/matheushjs/elfDistr
BugReports: https://github.com/matheushjs/elfDistr/issues
RoxygenNote: 6.1.1
Depends: R (>= 3.1.0)
LinkingTo: Rcpp
Imports: Rcpp
SystemRequirements: C++11
NeedsCompilation: yes
Suggests: testthat
Packaged: 2019-10-06 05:23:46 UTC; mathjs
Author: Matheus H. J. Saldanha [aut, cre], Adriano K. Suzuki [aut]
Maintainer: Matheus H. J. Saldanha <mhjsaldanha@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-07 18:00:02 UTC

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New package rrat with initial version 1.0.0
Package: rrat
Type: Package
Title: Robust Regression with Asymmetric Heavy-Tail Noise Distributions
Version: 1.0.0
Date: 2019-09-28
Author: Yi He and Yuelin Zhao
Maintainer: Yi He <yi.he@stats.oxon.org>
Description: Implementation of Robust Regression tailored to deal with Asymmetric noise Distribution, which was originally proposed by Takeuchi & Bengio & Kanamori (2002) <doi:10.1162/08997660260293300>. In addition, this implementation is extended as introducing potential feature regularization by LASSO etc.
Depends: R(>= 2.10), quantreg
License: GPL (>= 2)
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-04 00:43:13 UTC; Vincent
Repository: CRAN
Date/Publication: 2019-10-07 15:50:02 UTC

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New package SLEMI with initial version 1.0
Package: SLEMI
Title: Statistical Learning Based Estimation of Mutual Information
Version: 1.0
Date: 2019-09-19
Authors@R: c(person("Tomasz", "Jetka", email = "t.jetka@gmail.com", role = c("aut", "cre")), person("Karol", "Nienaltowski",role="ctb"),person("Michal", "Komorowski",role="ctb"))
Description: The implementation of the algorithm for estimation of mutual information and channel capacity from experimental data by classification procedures (logistic regression). Technically, it allows to estimate information-theoretic measures between finite-state input and multivariate, continuous output. Method described in Jetka et al. (2019) <doi:10.1371/journal.pcbi.1007132>.
Depends: R (>= 3.6.0)
License: LGPL (>= 2)
URL: https://github.com/sysbiosig/SLEMI
BugReports: https://github.com/sysbiosig/SLEMI/issues
Encoding: UTF-8
LazyData: true
Imports: e1071, ggplot2, ggthemes, gridExtra, nnet, Hmisc, reshape2, stringr, doParallel, caret, corrplot, foreach
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-04 11:14:11 UTC; ThinkPad_TJ
Author: Tomasz Jetka [aut, cre], Karol Nienaltowski [ctb], Michal Komorowski [ctb]
Maintainer: Tomasz Jetka <t.jetka@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-07 14:20:02 UTC

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New package rtmpt with initial version 0.1-15
Package: rtmpt
Version: 0.1-15
Title: Fitting RT-MPT Models
Authors@R: c(person("Raphael", "Hartmann", email = "raphael.hartmann@protonmail.com", role = c("aut", "cre")), person("Karl C.", "Klauer", email="christoph.klauer@psychologie.uni-freiburg.de", role=c("cph", "aut", "ctb", "ths")), person("Henrik", "Singmann", email="henrik.singmann@warwick.ac.uk", role=c("aut", "ctb", "cph")), person("Jean Marie", "Linhart", email="jlinhart@stata.com", role=c("cph")))
Author: Raphael Hartmann [aut, cre], Karl C. Klauer [cph, aut, ctb, ths], Henrik Singmann [aut, ctb, cph], Jean Marie Linhart [cph]
Maintainer: Raphael Hartmann <raphael.hartmann@protonmail.com>
Depends: R (>= 3.0.0)
Imports: coda, data.table, LaplacesDemon, loo, methods, stats, stringr, truncnorm, utils
Suggests: knitr
VignetteBuilder: knitr
NeedsCompilation: yes
SystemRequirements: GSL (>=2.3)
Description: Fit response-time extended multinomial processing tree (RT-MPT) models by Klauer and Kellen (2018) <doi:10.1016/j.jmp.2017.12.003>. The RT-MPT class not only incorporate frequencies like traditional multinomial processing tree (MPT) models, but also latencies. This enables it to estimate process completion times and encoding plus motor execution times next to the process probabilities of traditional MPTs. 'rtmpt' is a Bayesian framework and posterior samples are sampled using a Metropolis-Gibbs sampler like the one described in the Klauer and Kellen (2018), but with some modifications. Other than in the original C++ program we use the free and open source GNU Scientific Library (GSL). There is also the possibility to suppress single process completion times.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Packaged: 2019-10-04 18:34:39 UTC; hartmann2
Repository: CRAN
Date/Publication: 2019-10-07 14:50:02 UTC

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New package primer with initial version 1.1.1
Package: primer
Type: Package
Title: Functions and Data for the Book, A Primer of Ecology with R
Version: 1.1.1
Date: 2019-09-06
Author: M Henry H Stevens
Maintainer: Hank Stevens <hank.stevens@miamioh.edu>
Depends: deSolve, lattice
Suggests: bbmle, gdata, nlme, vegan
Description: Functions are primarily functions for systems of ordinary differential equations, difference equations, and eigenanalysis and projection of demographic matrices; data are for examples. Documentation of methods is provided in Stevens, MHH (2009, <https://www.springer.com/gp/book/9780387898810>).
License: GPL-2
LazyLoad: yes
NeedsCompilation: no
Packaged: 2019-09-06 10:11:07 UTC; hankstevens
Repository: CRAN
Date/Publication: 2019-10-07 14:30:03 UTC

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New package pkgfilecache with initial version 0.1.0
Package: pkgfilecache
Type: Package
Title: Download and Manage Optional Package Data
Version: 0.1.0
Author: Tim Schäfer
Maintainer: Tim Schäfer <ts+code@rcmd.org>
Description: Manage optional data for your package. The data can be hosted anywhere, and you have to give a Uniform Resource Locator (URL) for each file. File integrity checks are supported. This is useful for package authors who need to ship more than the 5 Megabyte of data currently allowed by the the Comprehensive R Archive Network (CRAN).
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/dfsp-spirit/pkgfilecache
BugReports: https://github.com/dfsp-spirit/pkgfilecache/issues
Suggests: knitr, rmarkdown, testthat (>= 2.1.0)
Imports: downloader, rappdirs
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-04 15:31:58 UTC; spirit
Repository: CRAN
Date/Publication: 2019-10-07 14:40:02 UTC

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New package oceanwaves with initial version 0.1.0
Package: oceanwaves
Title: Ocean Wave Statistics
Version: 0.1.0
Date: 2019-09-22
Authors@R: c(person(given = "Luke", family = "Miller", email= "contact@lukemiller.org", role = c("aut","cre"), comment = c(ORCID = "0000-0002-2009-6981")), person(given = "Urs", family = "Neumeier", email = "urs_neumeier@uqar.ca", role = "aut"), person(given = "Travis", family = "Mason", role = 'ctb'), person(given = 'Magali', family = 'Lecouturier', role = 'ctb'), person(given = 'George', family = 'Voulgaris', role = 'ctb'))
Description: Calculate ocean wave height summary statistics and process data from bottom-mounted pressure sensor data loggers. Derived primarily from MATLAB functions provided by U. Neumeier at <http://neumeier.perso.ch/matlab/waves.html>. Wave number calculation based on the algorithm in Hunt, J. N. (1979, ISSN:0148-9895) "Direct Solution of Wave Dispersion Equation", American Society of Civil Engineers Journal of the Waterway, Port, Coastal, and Ocean Division, Vol 105, pp 457-459.
URL: https://github.com/millerlp/oceanwaves, https://millerlp.github.io/oceanwaves/
BugReports: https://github.com/millerlp/oceanwaves/issues
Depends: R (>= 3.3.0), ggplot2
Imports: bspec, signal
Suggests: scales, oce, knitr, rmarkdown, testthat (>= 2.1.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-04 18:28:13 UTC; luke.miller
Author: Luke Miller [aut, cre] (<https://orcid.org/0000-0002-2009-6981>), Urs Neumeier [aut], Travis Mason [ctb], Magali Lecouturier [ctb], George Voulgaris [ctb]
Maintainer: Luke Miller <contact@lukemiller.org>
Repository: CRAN
Date/Publication: 2019-10-07 14:40:04 UTC

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New package meteorits with initial version 0.1.0
Type: Package
Package: meteorits
Title: Mixture-of-Experts Modeling for Complex Non-Normal Distributions
Version: 0.1.0
Authors@R: c(person("Faicel", "Chamroukhi", role = c("aut"), comment = c(ORCID = "0000-0002-5894-3103"), email = "faicel.chamroukhi@unicaen.fr"), person("Florian", "Lecocq", role = c("aut","trl","cre"), comment = "R port", email = "florian.lecocq@outlook.com"), person("Marius", "Bartcus", role = c("aut","trl"), comment = "R port", email = "marius.bartcus@gmail.com"))
Description: Provides a unified mixture-of-experts (ME) modeling and estimation framework with several original and flexible ME models to model, cluster and classify heterogeneous data in many complex situations where the data are distributed according to non-normal, possibly skewed distributions, and when they might be corrupted by atypical observations. Mixtures-of-Experts models for complex and non-normal distributions ('meteorits') are originally introduced and written in 'Matlab' by Faicel Chamroukhi. The references are mainly the following ones. The references are mainly the following ones. Chamroukhi F., Same A., Govaert, G. and Aknin P. (2009) <doi:10.1016/j.neunet.2009.06.040>. Chamroukhi F. (2010) <https://chamroukhi.com/FChamroukhi-PhD.pdf>. Chamroukhi F. (2015) <arXiv:1506.06707>. Chamroukhi F. (2015) <https://chamroukhi.com/FChamroukhi-HDR.pdf>. Chamroukhi F. (2016) <doi:10.1109/IJCNN.2016.7727580>. Chamroukhi F. (2016) <doi:10.1016/j.neunet.2016.03.002>. Chamroukhi F. (2017) <doi:10.1016/j.neucom.2017.05.044>.
URL: https://github.com/fchamroukhi/MEteorits
BugReports: https://github.com/fchamroukhi/MEteorits/issues
License: GPL (>= 3)
Depends: R (>= 2.10)
Imports: pracma, methods, stats, MASS, Rcpp
Suggests: knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
Collate: meteorits-package.R RcppExports.R logsumexp.R utils.R sampleUnivNMoE.R sampleUnivSNMoE.R sampleUnivStMoE.R sampleUnivTMoE.R ParamSNMoE.R ParamStMoE.R ParamTMoE.R ParamNMoE.R StatSNMoE.R StatStMoE.R StatTMoE.R StatNMoE.R ModelSNMoE.R ModelStMoE.R ModelTMoE.R ModelNMoE.R emSNMoE.R emStMoE.R emTMoE.R emNMoE.R data-tempanomalies.R
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-10-04 11:57:08 UTC; florianlecocq
Author: Faicel Chamroukhi [aut] (<https://orcid.org/0000-0002-5894-3103>), Florian Lecocq [aut, trl, cre] (R port), Marius Bartcus [aut, trl] (R port)
Maintainer: Florian Lecocq <florian.lecocq@outlook.com>
Repository: CRAN
Date/Publication: 2019-10-07 14:40:08 UTC

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New package LipidMSdata with initial version 1.0.0
Package: LipidMSdata
Type: Package
Title: 'LipidMS' Data
Version: 1.0.0
Author: M Isabel Alcoriza-Balaguer
Maintainer: M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
Description: Example data for 'LipidMS' package.
Depends: R (>= 3.1)
License: GPL (>= 2)
LazyData: TRUE
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-10-04 11:04:59 UTC; 73581298C
Repository: CRAN
Date/Publication: 2019-10-07 14:10:06 UTC

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New package HCTR with initial version 0.1.0
Package: HCTR
Title: Higher Criticism Tuned Regression
Version: 0.1.0
Authors@R: c(person("Tao", "Jiang", role = c("aut", "cre"), email = "tjiang8@ncsu.edu"))
Description: A novel searching scheme for tuning parameter in high-dimensional penalized regression. We propose a new estimate of the regularization parameter based on an estimated lower bound of the proportion of false null hypotheses (Meinshausen and Rice (2006) <doi:10.1214/009053605000000741>). The bound is estimated by applying the empirical null distribution of the higher criticism statistic, a second-level significance testing, which is constructed by dependent p-values from a multi-split regression and aggregation method (Jeng, Zhang and Tzeng (2019) <doi:10.1080/01621459.2018.1518236>). An estimate of tuning parameter in penalized regression is decided corresponding to the lower bound of the proportion of false null hypotheses. Different penalized regression methods are provided in the multi-split algorithm.
Depends: R (>= 3.4.0)
Imports: glmnet (>= 2.0-18), harmonicmeanp (>= 3.0), MASS, ncvreg (>= 3.11-1), Rdpack (>= 0.11-0), stats
RdMacros: Rdpack
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-04 16:48:49 UTC; tjiang8
Author: Tao Jiang [aut, cre]
Maintainer: Tao Jiang <tjiang8@ncsu.edu>
Repository: CRAN
Date/Publication: 2019-10-07 14:30:06 UTC

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New package cqcr with initial version 0.1.2
Package: cqcr
Title: Access 'Care Quality Commission' Data
Version: 0.1.2
Authors@R: person(given = "Evan", family = "Odell", role = c("aut", "cre"), email = "evanodell91@gmail.com", comment = c(ORCID = "0000-0003-1845-808X"))
Description: Access data from the 'Care Quality Commission', the health and adult social care regulator for England. The 'Care Quality Commission' operates an API <https://www.cqc.org.uk/about-us/transparency/using-cqc-data#api>, with data available under the Open Government License. Data includes information on service providers, locations such as hospitals, care homes and medical clinics, and ratings and inspection reports.
URL: https://github.com/evanodell/cqcr, https://docs.evanodell.com/cqcr
BugReports: https://github.com/evanodell/cqcr/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dplyr, httr, jsonlite, anytime, snakecase, rlang, purrr
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0), covr, tibble, knitr, rmarkdown, leaflet, scales, htmltools
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-04 10:52:59 UTC; EOdell
Author: Evan Odell [aut, cre] (<https://orcid.org/0000-0003-1845-808X>)
Maintainer: Evan Odell <evanodell91@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-07 14:10:02 UTC

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New package LongCART with initial version 1.0
Package: LongCART
Type: Package
Title: Recursive Partitioning for Longitudinal Profiles Using Baseline Covariates
Version: 1.0
Date: 2019-10-04
Author: Madan G Kundu
Maintainer: Madan G Kundu <madan_g.kundu@yahoo.com>
Depends: R (>= 3.4.0), nlme, rpart
Imports: Formula
Description: Constructs longitudinal tree (i.e., regression tree with heterogeneous longitudinal profile) for continuous longitudinal outcome using baseline covariates as partitioning variables according to the 'LongCART' algorithm as described in Kundu and Harezlak (2019) <doi:10.1080/24709360.2018.1557797>.
License: GPL (>= 2)
URL: https://www.r-project.org
BugReports: https://github.com/madanstat/LongCART/issues
NeedsCompilation: no
Packaged: 2019-10-04 07:58:40 UTC; mgkundu
Repository: CRAN
Date/Publication: 2019-10-07 13:50:02 UTC

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New package postDoubleR with initial version 1.4.12
Package: postDoubleR
Title: Post Double Selection with Double Machine Learning
Version: 1.4.12
Authors@R: person(given = "Juraj", family = "Szitás", role = c("aut", "cre"), email = "szitas.juraj13@gmail.com")
BugReports: https://github.com/JSzitas/postDoubleR/issues
Description: Implements post double selection using double machine learning, see Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, Newey, Robins (2017) <doi:10.1111/ectj.12097>, for various models, using several back ends. Allows the user flexibility in specifying their own methods for estimation.
License: GPL-3
Suggests: testthat (>= 2.1.0), knitr, rmarkdown
Encoding: UTF-8
LazyData: true
URL: https://github.com/JSzitas/postDoubleR
RoxygenNote: 6.1.1
Imports: glmnet, grf, neuralnet, progress, ggplot2, stats, parallel, doParallel
NeedsCompilation: no
Packaged: 2019-10-03 08:55:32 UTC; juraj
Author: Juraj Szitás [aut, cre]
Maintainer: Juraj Szitás <szitas.juraj13@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-07 10:40:03 UTC

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New package extremeIndex with initial version 0.0.1
Package: extremeIndex
Title: Forecast Verification for Extreme Events
Version: 0.0.1
Authors@R: person('Maxime','Taillardat',email='maxime.taillardat@meteo.fr',role=c('aut','cre'))
Description: An index measuring the amount of information brought by forecasts for extreme events, subject to calibration, is computed. This index is originally designed for weather or climate forecasts, but it may be used in other forecasting contexts. This is the implementation of the index in Taillardat et al. (2019) <arXiv:1905.04022>.
Depends: R (>= 3.2.3)
License: GPL-3
Encoding: UTF-8
LazyData: true
Maintainer: Maxime Taillardat <maxime.taillardat@meteo.fr>
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown
Imports: goftest, boot, evd, gmm, evir
NeedsCompilation: no
Packaged: 2019-10-03 09:12:35 UTC; maxime
Author: Maxime Taillardat [aut, cre]
Repository: CRAN
Date/Publication: 2019-10-07 11:00:02 UTC

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New package interpret with initial version 0.1.20
Package: interpret
Title: Fit Interpretable Models and Explain Blackbox Machine Learning
Version: 0.1.20
Date: 2019-10-07
Description: Machine Learning package for training interpretable models and explaining blackbox systems. Historically, the most intelligible models were not very accurate, and the most accurate models were not intelligible. Microsoft Research has developed an algorithm called the Explainable Boosting Machine (EBM) which has both high accuracy and intelligibility. EBM uses machine learning techniques like bagging and boosting to breathe new life into traditional GAMs (Generalized Additive Models). This makes them as accurate as random forests and gradient boosted trees, and also enhances their intelligibility and editability. Details on the EBM algorithm can be found in the paper by Rich Caruana, Yin Lou, Johannes Gehrke, Paul Koch, Marc Sturm, and Noemie Elhadad (2015, <doi:10.1145/2783258.2788613>).
URL: https://github.com/microsoft/interpret
BugReports: https://github.com/microsoft/interpret/issues
License: MIT + file LICENSE
Authors@R: c( person("Samuel", "Jenkins", role = c("aut")), person("Harsha", "Nori", role = c("aut")), person("Paul", "Koch", role = c("aut")), person("Rich", "Caruana", role = c("aut", "cre"), email = "interpretml@outlook.com"), person("Microsoft Corporation", role="cph") )
Depends: R (>= 3.0.0)
NeedsCompilation: yes
SystemRequirements: C++11
Packaged: 2019-10-07 08:03:24 UTC; admins
Author: Samuel Jenkins [aut], Harsha Nori [aut], Paul Koch [aut], Rich Caruana [aut, cre], Microsoft Corporation [cph]
Maintainer: Rich Caruana <interpretml@outlook.com>
Repository: CRAN
Date/Publication: 2019-10-07 09:20:02 UTC

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Sun, 06 Oct 2019

New package WR with initial version 0.1.0
Package: WR
Type: Package
Title: Win Ratio Analysis
Version: 0.1.0
Author: Lu Mao and Tuo Wang
Maintainer: Lu Mao <lmao@biostat.wisc.edu>
Description: Contains win-ratio analysis routines for prioritized composite time-to-event outcomes, e.g., death and non-fatal events. These routines include functions to fit the proportional win-fractions (PW) model and to compute and plot the standardized score process to assess the proportionality assumption.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10), survival
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-09-21 01:22:23 UTC; tuowang
Repository: CRAN
Date/Publication: 2019-10-06 13:00:05 UTC

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New package rscontract with initial version 0.1.0
Package: rscontract
Title: Generic implementation of the 'RStudio' connections contract
Version: 0.1.0
Authors@R: person("Edgar", "Ruiz", email = "edgar@rstudio.com", role = c("aut", "cre"))
Description: Provides a generic implementation of the 'RStudio' connection contract to make it easier for database connections, and other type of connections, opened via R packages integrate with the connections pane inside the 'RStudio' interactive development environment (IDE).
License: GPL-3
Suggests: testthat (>= 2.1.0), covr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/edgararuiz/rscontract
BugReports: https://github.com/edgararuiz/rscontract/issues
Language: en-US
NeedsCompilation: no
Packaged: 2019-10-02 12:59:19 UTC; edgar
Author: Edgar Ruiz [aut, cre]
Maintainer: Edgar Ruiz <edgar@rstudio.com>
Repository: CRAN
Date/Publication: 2019-10-06 12:40:03 UTC

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New package PCMBaseCpp with initial version 0.1.5
Package: PCMBaseCpp
Type: Package
Title: Fast Likelihood Calculation for Phylogenetic Comparative Models
Version: 0.1.5
Authors@R: c(person("Venelin", "Mitov", email = "vmitov@gmail.com", role = c("aut", "cre", "cph")))
Maintainer: Venelin Mitov <vmitov@gmail.com>
Description: Provides a C++ backend for multivariate phylogenetic comparative models implemented in the R-package 'PCMBase'. Can be used in combination with 'PCMBase' to enable fast and parallel likelihood calculation. Implements the pruning likelihood calculation algorithm described in Mitov et al. (2018) <arXiv:1809.09014>. Uses the 'SPLITT' C++ library for parallel tree traversal described in Mitov and Stadler (2018) <doi:10.1111/2041-210X.13136>.
Encoding: UTF-8
License: GPL (>= 3.0)
LazyData: true
Depends: R (>= 3.1.0), Rcpp, methods
Imports: PCMBase, data.table, abind
Suggests: testthat, knitr, rmarkdown, covr
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
ByteCompile: yes
NeedsCompilation: yes
URL: https://github.com/venelin/PCMBaseCpp, https://venelin.github.io/PCMBase/
BugReports: https://github.com/venelin/PCMBaseCpp/issues
Repository: CRAN
Packaged: 2019-10-02 09:42:59 UTC; vmitov
Author: Venelin Mitov [aut, cre, cph]
Date/Publication: 2019-10-06 12:30:02 UTC

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New package ohenery with initial version 0.1.0
Package: ohenery
Maintainer: Steven E. Pav <shabbychef@gmail.com>
Authors@R: c(person(c("Steven", "E."), "Pav", role=c("aut","cre"), email="shabbychef@gmail.com", comment = c(ORCID = "0000-0002-4197-6195")))
Version: 0.1.0
Date: 2019-10-01
License: LGPL-3
Title: Modeling of Ordinal Random Variables via Softmax Regression
BugReports: https://github.com/shabbychef/ohenery/issues
Description: Supports the modeling of ordinal random variables, like the outcomes of races, via Softmax regression, under the Harville <doi:10.1080/01621459.1973.10482425> and Henery <doi:10.1111/j.2517-6161.1981.tb01153.x> models.
Depends: R (>= 3.0.2)
Imports: Rcpp (>= 0.12.3), maxLik, magrittr, methods, dplyr
LinkingTo: Rcpp
Suggests: rlang, tidyr, forcats, microbenchmark, testthat, numDeriv, ggplot2, scales, knitr
Encoding: UTF-8
URL: https://github.com/shabbychef/ohenery
Collate: 'data.r' 'harsm.r' 'hensm.r' 'linodds.r' 'ohenery.r' 'RcppExports.R' 'rsm.r' 'utils.r'
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-10-02 04:43:35 UTC; spav
Author: Steven E. Pav [aut, cre] (<https://orcid.org/0000-0002-4197-6195>)
Repository: CRAN
Date/Publication: 2019-10-06 12:10:02 UTC

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New package NMVANOVA with initial version 1.1.0
Package: NMVANOVA
Type: Package
Title: Novice Model Variation ANOVA
Version: 1.1.0
Author: Joseph V. Lipoff, Will Pauls, Kaylin C. Dobbs, Jordan L. Jensen, Kevin Woods, Evan T. Johnson, Benjamin F. Timson, Scott D. Zimmerman,and Paul Plummer
Maintainer: Joseph Lipoff <josephlipoff@msn.com>
Description: Due to 'Rstudio's' status as open source software, we believe it will be utilized frequently for future data analysis by users whom lack formal training or experience with 'R'. The 'NMVANOVA' (Novice Model Variation ANOVA) a streamlined variation of experimental design functions that allows novice 'Rstudio' users to perform different model variations one-way analysis of variance without downloading multiple libraries or packages. Users can easily manipulate the data block, and needed inputs so that users only have to plugin the four designed variables/values.
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-10-01 14:59:38 UTC; wrpauls21
Repository: CRAN
Date/Publication: 2019-10-06 12:10:06 UTC

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New package MPBoost with initial version 0.1-3
Package: MPBoost
Type: Package
Title: Treatment Allocation in Clinical Trials by the Maximal Procedure
Version: 0.1-3
Date: 2019-10-02
Author: Ignacio López-de-Ullibarri [aut, cre]
Maintainer: Ignacio López-de-Ullibarri <ignacio.lopezdeullibarri@udc.es>
Description: Performs treatment allocation in two-arm clinical trials by the maximal procedure described by Berger et al. (2003) <doi:10.1002/sim.1538>. To that end, the algorithm provided by Salama et al. (2008) <doi:10.1002/sim.3014> is implemented.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.1)
LinkingTo: Rcpp, BH
Depends: R (>= 3.6.0)
Suggests: knitr, pinp, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2019-10-02 10:54:22 UTC; ilu
Repository: CRAN
Date/Publication: 2019-10-06 12:50:08 UTC

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New package glmtree with initial version 0.1
Package: glmtree
Type: Package
Title: Logistic Regression Trees
Version: 0.1
Date: 2019-09-26
Authors@R: c(person("Adrien", "Ehrhardt", email = "adrien.ehrhardt@centraliens-lille.org", role = c("aut", "cre")))
Maintainer: Adrien Ehrhardt <adrien.ehrhardt@centraliens-lille.org>
Description: A logistic regression tree is a decision tree with logistic regressions at its leaves. A particular stochastic expectation maximization algorithm is used to draw a few good trees, that are then assessed via the user's criterion of choice among BIC / AIC / test set Gini. The formal development is given in a PhD chapter, see Ehrhardt (2019) <https://github.com/adimajo/manuscrit_these/releases/>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: partykit, magrittr, methods, dplyr, caret
Suggests: FactoMineR, knitr, testthat, covr, rmarkdown
URL: https://adimajo.github.io
BugReports: https://github.com/adimajo/glmtree/issues
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-02 15:53:37 UTC; adrien
Author: Adrien Ehrhardt [aut, cre]
Repository: CRAN
Date/Publication: 2019-10-06 12:50:02 UTC

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New package eqn2svg with initial version 0.1.0
Package: eqn2svg
Title: Create an SVG-Based Mathematical Formula
Version: 0.1.0
Authors@R: person("Richard", "Iannone", , "riannone@me.com", c("aut", "cre"), comment = c(ORCID = "0000-0003-3925-190X"))
Description: If you have a mathematical formula and the need to have that formula in the form of scalable vector graphics (SVG), you'll be delighted by what 'eqn2svg' will let you do. The incoming LaTeX math formula will be nicely converted to SVG tags. And you can use that code wherever SVGs are accepted.
License: MIT + file LICENSE
URL: https://github.com/rich-iannone/eqn2svg
BugReports: https://github.com/rich-iannone/eqn2svg/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.2.0)
Imports: htmltools (>= 0.3.6), magrittr
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2019-10-02 15:43:42 UTC; rich
Author: Richard Iannone [aut, cre] (<https://orcid.org/0000-0003-3925-190X>)
Maintainer: Richard Iannone <riannone@me.com>
Repository: CRAN
Date/Publication: 2019-10-06 12:50:05 UTC

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New package donut with initial version 1.0.0
Package: donut
Title: Nearest Neighbour Search with Variables on a Torus
Version: 1.0.0
Date: 2019-10-03
Authors@R: person(c("Paul", "J."), "Northrop", email = "p.northrop@ucl.ac.uk", role = c("aut", "cre", "cph"))
Description: Finds the k nearest neighbours in a dataset of specified points, adding the option to wrap certain variables on a torus. The user chooses the algorithm to use to find the nearest neighbours. Three such algorithms, provided by the packages 'RANN' <https://cran.r-project.org/package=RANN>, 'RANN.L1' <https://cran.r-project.org/package=RANN.L1>, and 'nabor' <https://cran.r-project.org/package=nabor>, are suggested.
Imports: graphics, methods
License: GPL (>= 2)
LazyData: TRUE
Encoding: UTF-8
Depends: R (>= 3.3.0)
RoxygenNote: 6.1.1
Suggests: knitr, nabor, RANN, RANN.L1, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
URL: http://github.com/paulnorthrop/donut
BugReports: http://github.com/paulnorthrop/donut/issues
NeedsCompilation: no
Packaged: 2019-10-02 23:20:27 UTC; paul
Author: Paul J. Northrop [aut, cre, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>
Repository: CRAN
Date/Publication: 2019-10-06 13:00:02 UTC

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New package diyar with initial version 0.0.1
Package: diyar
Type: Package
Title: Multistage Record Linkage and Case Definition for Epidemiological Analysis
Date: 2019-10-01
Version: 0.0.1
URL: https://github.com/OlisaNsonwu/diyar
BugReports: https://github.com/OlisaNsonwu/diyar/issues
Author: Olisa Nsonwu
Maintainer: Olisa Nsonwu <olisa.nsonwu@gmail.com>
Description: Perform multistage deterministic linkages, apply case definitions to datasets, and deduplicate records. Records (rows) from datasets are linked by different matching criteria and sub-criteria (columns) in a specified order of certainty. The linkage process handles missing data and conflicting matches based on this same order of certainty. For episode grouping, rows of dated events (e.g. sample collection) or interval of events (e.g. hospital admission) are grouped into chronological episodes beginning with a "case". The process permits several options such as episode lengths and recurrence periods which are used to build custom preferences for case assignment (definition). The record linkage and episode grouping processes assign unique group IDs to matching records or those grouped into episodes. This then allows for record deduplication or sub-analysis within these groups.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: methods, utils, rlang, dplyr (>= 0.7.5), lubridate (>= 1.7.4), stringr, tidyr (>= 0.8.2)
RoxygenNote: 6.1.1
Suggests: ggplot2, janitor, knitr, rmarkdown, testthat, covr
VignetteBuilder: knitr
Language: en-GB
NeedsCompilation: no
Packaged: 2019-10-02 06:14:35 UTC; St. Loki
Repository: CRAN
Date/Publication: 2019-10-06 12:20:02 UTC

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New package aliases2entrez with initial version 0.0.6
Package: aliases2entrez
Title: Converts Human gene symbols to entrez IDs
Version: 0.0.6
Authors@R: c(person(given = "Raphael", family = "Bonnet", role = c("aut", "cre"), email = "raphael.bonnet@univ-cotedazur.fr", comment="Université Côte d’Azur"), person(given = "Jean-François", family = "Peyron", role = c("aut"), comment="Inserm") )
Description: Queries multiple resources authors HGNC (2019) <https://www.genenames.org>, authors limma (2015) <doi:10.1093/nar/gkv007> to find the correspondence between evolving nomenclature of human gene symbols, aliases, previous symbols or synonyms with stable, curated gene entrezID from NCBI database. This allows fast, accurate and up-to-date correspondence between human gene expression datasets from various date and platform (e.g: gene symbol: BRCA1 - ID: 672).
BugReports: https://github.com/peyronlab/aliases2entrez/issues
Imports: doParallel, limma, utils, org.Hs.eg.db, AnnotationDbi, parallel, foreach, readr, RCurl
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: spelling
Language: en-US
NeedsCompilation: no
Packaged: 2019-10-02 07:49:39 UTC; raphael
Author: Raphael Bonnet [aut, cre] (Université Côte d’Azur), Jean-François Peyron [aut] (Inserm)
Maintainer: Raphael Bonnet <raphael.bonnet@univ-cotedazur.fr>
Repository: CRAN
Date/Publication: 2019-10-06 12:20:06 UTC

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New package prismatic with initial version 0.1.0
Package: prismatic
Title: Color Manipulation Tools
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: Manipulate and visualize colors in a intuitive, low-dependency and functional way.
License: MIT + file LICENSE
URL: https://github.com/EmilHvitfeldt/prismatic
BugReports: https://github.com/EmilHvitfeldt/prismatic/issues
Depends: R (>= 3.2)
Imports: farver (>= 1.1.0)
Suggests: covr, crayon, testthat (>= 2.1.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-01 20:43:06 UTC; emilhvitfeldthansen
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-06 11:30:02 UTC

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New package interpret with initial version 0.1.18
Package: interpret
Title: Fit Interpretable Models and Explain Blackbox Machine Learning
Version: 0.1.18
Date: 2019-10-01
Description: Machine Learning package for training interpretable models and explaining blackbox systems. Historically, the most intelligible models were not very accurate, and the most accurate models were not intelligible. Microsoft Research has developed an algorithm called the Explainable Boosting Machine (EBM) which has both high accuracy and intelligibility. EBM uses modern machine learning techniques like bagging and boosting to breathe new life into traditional GAMs (Generalized Additive Models). This makes them as accurate as random forests and gradient boosted trees, and also enhances their intelligibility and editability. Details on the EBM algorithm can be found in the paper by Rich Caruana, Yin Lou, Johannes Gehrke, Paul Koch, Marc Sturm, and Noemie Elhadad (2015, <doi:10.1145/2783258.2788613>).
URL: https://github.com/microsoft/interpret
BugReports: https://github.com/microsoft/interpret/issues
License: MIT + file LICENSE
Authors@R: c( person("Samuel", "Jenkins", role = c("aut")), person("Harsha", "Nori", role = c("aut")), person("Paul", "Koch", role = c("aut")), person("Rich", "Caruana", role = c("aut", "cre"), email = "interpretml@outlook.com"), person("Microsoft Corporation", role="cph") )
Depends: R (>= 3.0.0)
NeedsCompilation: yes
SystemRequirements: C++11
Packaged: 2019-10-01 17:28:16 UTC; admins
Author: Samuel Jenkins [aut], Harsha Nori [aut], Paul Koch [aut], Rich Caruana [aut, cre], Microsoft Corporation [cph]
Maintainer: Rich Caruana <interpretml@outlook.com>
Repository: CRAN
Date/Publication: 2019-10-06 11:30:05 UTC

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New package foodingraph with initial version 0.1.0
Package: foodingraph
Type: Package
Title: Food Network Inference and Visualization
Version: 0.1.0
Authors@R: c( person("Victor", "Gasque", , "victor.gasque@protonmail.com", c("cre", "aut")), person("Boris", "Hejblum", , "boris.hejblum@u-bordeaux.fr", "aut"), person("Cecilia", "Samieri", , "cecilia.samieri@u-bordeaux.fr", "aut"))
Maintainer: Victor Gasque <victor.gasque@protonmail.com>
Description: Displays a weighted undirected food graph from an adjacency matrix. Can perform confidence-interval bootstrap inference with mutual information or maximal information coefficient. Based on my Master 1 internship at the Bordeaux Population Health center. References : Reshef et al. (2011) <doi:10.1126/science.1205438>, Meyer et al. (2008) <doi:10.1186/1471-2105-9-461>, Liu et al. (2016) <doi:10.1371/journal.pone.0158247>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dplyr, ggplot2, cowplot, magrittr, stringr, tibble, tidyr, viridis, igraph, ggraph, minerva, rlang, labeling, grid
Suggests: knitr, infotheo, minet,
VignetteBuilder: knitr
URL: https://github.com/vgasque/foodingraph/
BugReports: https://github.com/vgasque/foodingraph/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-01 19:08:18 UTC; Victor
Author: Victor Gasque [cre, aut], Boris Hejblum [aut], Cecilia Samieri [aut]
Repository: CRAN
Date/Publication: 2019-10-06 11:30:08 UTC

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New package mlr3pipelines with initial version 0.1.0
Package: mlr3pipelines
Title: Preprocessing Operators and Pipelines for 'mlr3'
Version: 0.1.0
Authors@R: c(person(given = "Martin", family = "Binder", role = c("aut", "cre"), email = "mlr.developer@mb706.com"), person(given = "Florian", family = "Pfisterer", role = "aut", email = "pfistererf@googlemail.com", comment = c(ORCID = "0000-0001-8867-762X")), person(given = "Bernd", family = "Bischl", role = "aut", email = "bernd_bischl@gmx.net", comment = c(ORCID = "0000-0001-6002-6980")), person(given = "Michel", family = "Lang", role = "aut", email = "michellang@gmail.com", comment = c(ORCID = "0000-0001-9754-0393")), person(given = "Susanne", family = "Dandl", role = "aut", email = "dandl.susanne@googlemail.com"))
Description: Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.
License: LGPL-3
URL: https://mlr3pipelines.mlr-org.com, https://github.com/mlr-org/mlr3pipelines
BugReports: https://github.com/mlr-org/mlr3pipelines/issues
Depends: R (>= 3.1.0)
Imports: backports, checkmate, data.table, digest, mlr3 (>= 0.1.3), mlr3misc (>= 0.1.4), paradox, R6, withr
Suggests: ggplot2, glmnet, igraph, knitr, lgr, lme4, mlbench, mlr3filters, mlr3learners, nloptr, rmarkdown, rpart, testthat, visNetwork, bestNormalize, fastICA, kernlab, smotefamily
VignetteBuilder: knitr
ByteCompile: true
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
RoxygenNote: 6.1.1
Collate: 'Graph.R' 'GraphLearner.R' 'mlr_pipeops.R' 'utils.R' 'PipeOp.R' 'PipeOpEnsemble.R' 'LearnerAvg.R' 'NO_OP.R' 'PipeOpTaskPreproc.R' 'PipeOpBoxCox.R' 'PipeOpBranch.R' 'PipeOpChunk.R' 'PipeOpClassBalancing.R' 'PipeOpClassifAvg.R' 'PipeOpColApply.R' 'PipeOpCollapseFactors.R' 'PipeOpCopy.R' 'PipeOpEncode.R' 'PipeOpEncodeLmer.R' 'PipeOpFeatureUnion.R' 'PipeOpFilter.R' 'PipeOpFixFactors.R' 'PipeOpHistBin.R' 'PipeOpICA.R' 'PipeOpImpute.R' 'PipeOpImputeHist.R' 'PipeOpImputeMean.R' 'PipeOpImputeMedian.R' 'PipeOpImputeNewlvl.R' 'PipeOpImputeSample.R' 'PipeOpKernelPCA.R' 'PipeOpLearner.R' 'PipeOpLearnerCV.R' 'PipeOpMissingIndicators.R' 'PipeOpModelMatrix.R' 'PipeOpMutate.R' 'PipeOpNOP.R' 'PipeOpPCA.R' 'PipeOpQuantileBin.R' 'PipeOpRegrAvg.R' 'PipeOpRemoveConstants.R' 'PipeOpScale.R' 'PipeOpScaleMaxAbs.R' 'PipeOpScaleRange.R' 'PipeOpSelect.R' 'PipeOpSmote.R' 'PipeOpSpatialSign.R' 'PipeOpSubsample.R' 'PipeOpUnbranch.R' 'PipeOpYeoJohnson.R' 'Selector.R' 'assert_graph.R' 'greplicate.R' 'gunion.R' 'operators.R' 'po.R' 'reexports.R' 'typecheck.R' 'zzz.R'
Packaged: 2019-10-01 16:14:45 UTC; user
Author: Martin Binder [aut, cre], Florian Pfisterer [aut] (<https://orcid.org/0000-0001-8867-762X>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Susanne Dandl [aut]
Maintainer: Martin Binder <mlr.developer@mb706.com>
Repository: CRAN
Date/Publication: 2019-10-06 10:40:02 UTC

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New package HTLR with initial version 0.4
Package: HTLR
Version: 0.4
Title: Bayesian Logistic Regression with Heavy-Tailed Priors
Authors@R: c(person(given = "Longhai", family = "Li", role = c("aut", "cre"), email = "longhai@math.usask.ca", comment=c(ORCID="0000-0002-3074-8584")), person(given = "Steven", family = "Liu", role = c("aut"), email = "xil865@usask.ca"))
Description: Efficient Bayesian multinomial logistic regression based on heavy-tailed (hyper-LASSO, non-convex) priors. The posterior of coefficients and hyper-parameters is sampled with restricted Gibbs sampling for leveraging the high-dimensionality and Hamiltonian Monte Carlo for handling the high-correlation among coefficients. A detailed description of the method: Li and Yao (2018), JSCS, 88:14, 2827-2851, <arXiv:1405.3319>.
License: GPL-2
URL: https://github.com/longhaiSK/HTLR
BugReports: https://github.com/longhaiSK/HTLR/issues
Depends: R (>= 3.1.0)
Suggests: rda, ggplot2, corrplot, testthat (>= 2.0.0), bayesplot, knitr, rmarkdown
Imports: Rcpp (>= 0.12.0), BCBCSF, glmnet, magrittr
LinkingTo: Rcpp (>= 0.12.0), RcppArmadillo
NeedsCompilation: yes
SystemRequirements: C++11
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Packaged: 2019-09-30 22:45:06 UTC; xil
Author: Longhai Li [aut, cre] (<https://orcid.org/0000-0002-3074-8584>), Steven Liu [aut]
Maintainer: Longhai Li <longhai@math.usask.ca>
Repository: CRAN
Date/Publication: 2019-10-06 10:10:03 UTC

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New package BHAI with initial version 0.99.2
Package: BHAI
Title: Estimate the Burden of Healthcare-Associated Infections
Version: 0.99.2
Authors@R: person("Benedikt", "Zacher", email = "ZacherB@rki.de", role = c("aut", "cre"))
Author: Benedikt Zacher [aut, cre]
Maintainer: Benedikt Zacher <ZacherB@rki.de>
Description: Provides an approach which is based on the methodology of the Burden of Communicable Diseases in Europe (BCoDE) and can be used for large and small samples such as individual countries. The Burden of Healthcare-Associated Infections (BHAI) is estimated in disability-adjusted life years, number of infections as well as number of deaths per year. Results can be visualized with various plotting functions and exported into tables.
Depends: R (>= 3.6.0)
License: GPL-3
LazyData: true
RoxygenNote: 6.1.1
Imports: prevtoinc, MCMCpack, plotrix, graphics, grDevices, stats, methods
NeedsCompilation: no
Packaged: 2019-10-01 13:58:13 UTC; zacherb
Repository: CRAN
Date/Publication: 2019-10-06 10:20:02 UTC

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Sat, 05 Oct 2019

New package TouRnament with initial version 0.2.5
Package: TouRnament
Type: Package
Title: Tools for Sports Competitions
Version: 0.2.5
Authors@R: person("Tobias", "Wolfanger", email = "tobias.wolfanger@gmx.de", role = c("aut","cre"))
Description: Contains two functions related to sports competitions. One to create league tables and one to create a match schedule.
BugReports: https://github.com/captaincaracho/TouRnament/issues
Suggests: engsoccerdata
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-09-30 20:14:32 UTC; User
Author: Tobias Wolfanger [aut, cre]
Maintainer: Tobias Wolfanger <tobias.wolfanger@gmx.de>
Repository: CRAN
Date/Publication: 2019-10-05 09:00:02 UTC

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Fri, 04 Oct 2019

New package nationwider with initial version 1.0.0
Package: nationwider
Title: Download House Price Data From Nationwide
Version: 1.0.0
Authors@R: person(given = "Kostas", family = "Vasilopoulos", role = c("aut", "cre"), email = "k.vasilopoulo@gmail.com",, comment = c(ORCID = "0000-0002-9769-6395"))
Description: Web scraping the <https://www.nationwide.co.uk> for up-to-date data on house price indices. Download data in tidy format.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: httr (>= 1.4.1), rvest (>= 0.3.4), xml2 (>= 1.2.2), magrittr (>= 1.5), dplyr (>= 0.8.3), tidyr (>= 0.8.3), readxl (>= 1.3.1), lubridate (>= 1.7.4), zoo (>= 1.8.6), stringr (>= 1.4.0)
RoxygenNote: 6.1.1
URL: https://github.com/kvasilopoulos/nationwider
BugReports: https://github.com/kvasilopoulos/nationwider/issues
Suggests: testthat (>= 2.1.0), covr (>= 3.3.0), spelling (>= 2.1), ggplot2 (>= 3.2.1)
Language: en-US
NeedsCompilation: no
Packaged: 2019-09-30 21:53:21 UTC; T460p
Author: Kostas Vasilopoulos [aut, cre] (<https://orcid.org/0000-0002-9769-6395>)
Maintainer: Kostas Vasilopoulos <k.vasilopoulo@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-04 10:50:02 UTC

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New package geospark with initial version 0.2.1
Package: geospark
Type: Package
Title: Bring Local Sf to Spark
Version: 0.2.1
Authors@R: c( person("Harry", "Zhu", email = "7harryprince@gmail.com", role = c("aut", "cre")), person("Javier", "Luraschi", email = "javier@rstudio.com", role = c("ctb")) )
Maintainer: Harry Zhu <7harryprince@gmail.com>
BugReports: https://github.com/harryprince/geospark/issues
Description: R binds 'GeoSpark' <http://geospark.datasyslab.org/> extending 'sparklyr' <https://spark.rstudio.com/> R package to make distributed 'geocomputing' easier. Sf is a package that provides [simple features] <https://en.wikipedia.org/wiki/Simple_Features> access for R and which is a leading 'geospatial' data processing tool. 'Geospark' R package bring the same simple features access like sf but running on Spark distributed system.
License: Apache License (>= 2.0)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.2)
Imports: sparklyr (>= 1.0.0), dplyr (>= 0.8.3), dbplyr (>= 1.3.0)
RoxygenNote: 6.1.1
Suggests: testthat, knitr, utils
NeedsCompilation: no
Packaged: 2019-09-30 22:31:07 UTC; harryzhu
Author: Harry Zhu [aut, cre], Javier Luraschi [ctb]
Repository: CRAN
Date/Publication: 2019-10-04 11:00:02 UTC

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Thu, 03 Oct 2019

New package panelWranglR with initial version 1.2.13
Package: panelWranglR
Title: Panel Data Wrangling Tools
Version: 1.2.13
Authors@R: person(given = "Juraj", family = "Szitás", role = c("aut", "cre"), email = "szitas.juraj13@gmail.com")
BugReports: https://github.com/JSzitas/panelWranglR/issues
Description: Leading/lagging a panel, creating dummy variables, taking panel differences, looking for panel autocorrelations, and more. Implemented via a 'data.table' back end.
License: GPL-3
Depends: R (>= 3.2.0)
Suggests: testthat (>= 2.1.0)
Encoding: UTF-8
LazyData: true
URL: https://github.com/JSzitas/panelWranglR
RoxygenNote: 6.1.1
Imports: data.table, Hmisc, caret
NeedsCompilation: no
Packaged: 2019-09-28 18:02:59 UTC; juraj
Author: Juraj Szitás [aut, cre]
Maintainer: Juraj Szitás <szitas.juraj13@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-03 08:30:02 UTC

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New package healthforum with initial version 0.1.0
Package: healthforum
Type: Package
Title: Scrape Patient Forum Data
Version: 0.1.0
Authors@R: c( person("Lingshu", "Hu", , email = "lingshu.hu@hotmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0304-882X")), person("Michael W.", "Kearney", , email = "kearneymw@missouri.edu", role = c("ctb"), comment = c(ORCID = "0000-0002-0730-4694")))
Description: Scrape data from Patient Forum <https://patient.info/forums> by entering urls. It will return a data frame containing text, user names, like counts, reply counts, etc.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: rvest, magrittr, xml2, purrr, tokenizers, stringr
Depends: R (>= 3.5.0)
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2019-09-28 16:12:03 UTC; lingshuhu
Author: Lingshu Hu [aut, cre] (<https://orcid.org/0000-0003-0304-882X>), Michael W. Kearney [ctb] (<https://orcid.org/0000-0002-0730-4694>)
Maintainer: Lingshu Hu <lingshu.hu@hotmail.com>
Repository: CRAN
Date/Publication: 2019-10-03 08:20:02 UTC

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New package varsExplore with initial version 0.1.0
Package: varsExplore
Type: Package
Title: Searchable Variable Explorer with Labelled Variables
Version: 0.1.0
Author: Vlad Tarko
Maintainer: Vlad Tarko <vladtarko@gmail.com>
Description: Creates a summary dataframe that can be used in 'RStudio' similar to the variable explorer in 'Stata', but which also includes the summary statistics. By default the result is shown in the 'RStudio' Viewer Pane as a searchable data table. This is useful particularly if you have a large dataset with a very large number of labelled variables with hard to remember names. Can also be used to generate a table of summary statistics.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, magrittr, purrr, tidyr, stringr, glue, DT, rstudioapi, rio
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-09-28 05:28:40 UTC; vladtarko
Repository: CRAN
Date/Publication: 2019-10-03 07:40:02 UTC

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New package rmangal with initial version 2.0.0
Package: rmangal
Type: Package
Title: 'Mangal' Client
Version: 2.0.0
Authors@R: c( person(given = "Steve", family = "Vissault", comment = c(ORCID = "0000-0002-0866-4376"), email = "steve.vissault@usherbrooke.ca", role = c("aut", "cre")), person(given = "Kevin", family = "Cazelles", comment = c(ORCID = "0000-0001-6619-9874"), email = "kcazelle@uoguelph.ca", role = c("aut","ctb")), person(given = "Gabriel", family = "Bergeron", email = "gabriel.bergeron3@usherbrooke.ca", role = c("aut","ctb")), person(given = "Benjamin", family = "Mercier", email = "Benjamin.B.Mercier@usherbrooke.ca", role = c("aut","ctb")), person(given = "Clément", family = "Violet", email = "Clement.Violet@etudiant.univ-brest.fr", role = c("aut","ctb")), person(given = "Dominique", family = "Gravel", email = "dominique.gravel@usherbrooke.ca", role = c("aut")), person(given = "Timothée", family = "Poisot", email = "timothee.poisot@umontreal.ca", role = c("aut")), person(given = "Thomas Lin", family = "Pedersen", role = "rev", comment = c(ORCID = "0000-0002-5147-4711")), person(given = "Anna Willoughby", role = "rev", comment = c(ORCID = "0000-0002-0504-0605")) )
Description: An interface to the 'Mangal' database - a collection of ecological networks. This package includes functions to work with the 'Mangal RESTful API' methods (<https://mangal.io/doc/api>).
URL: https://mangal.io, https://github.com/ropensci/rmangal
BugReports: https://github.com/ropensci/rmangal/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: httr (>= 1.3.1), igraph, jsonlite (>= 1.5), memoise, purrr
RoxygenNote: 6.1.1
Suggests: ggraph (>= 2.0.0), knitr, magrittr, mapview, rmarkdown, sf, spelling, taxize, tidygraph, testthat, tibble, USAboundaries,
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-09-28 14:26:54 UTC; steve
Author: Steve Vissault [aut, cre] (<https://orcid.org/0000-0002-0866-4376>), Kevin Cazelles [aut, ctb] (<https://orcid.org/0000-0001-6619-9874>), Gabriel Bergeron [aut, ctb], Benjamin Mercier [aut, ctb], Clément Violet [aut, ctb], Dominique Gravel [aut], Timothée Poisot [aut], Thomas Lin Pedersen [rev] (<https://orcid.org/0000-0002-5147-4711>), Anna Willoughby [rev] (<https://orcid.org/0000-0002-0504-0605>)
Maintainer: Steve Vissault <steve.vissault@usherbrooke.ca>
Repository: CRAN
Date/Publication: 2019-10-03 08:00:03 UTC

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New package microhaplot with initial version 1.0.1
Package: microhaplot
Type: Package
Title: Microhaplotype Constructor and Visualizer
Version: 1.0.1
Authors@R: person("Thomas", "Ng", email = "tngthomasng@gmail.com", role = c("aut", "cre"))
Description: A downstream bioinformatics tool to construct and assist curation of microhaplotypes from short read sequences.
Depends: R (>= 3.1.2)
Encoding: UTF-8
License: GPL-3
LazyData: TRUE
Imports: DT (>= 0.1), dplyr (>= 0.4.3), ggplot2 (>= 2.1.0), grid (>= 3.1.2), gtools (>= 3.5.0), magrittr (>= 1.5), scales (>= 0.4.0), shiny (>= 0.13.2), shinyBS (>= 0.61), tidyr (>= 0.4.1), shinyWidgets (>= 0.4.3), ggiraph (>= 0.6.0)
URL: https://github.com/ngthomas/microhaplot
BugReports: https://github.com/ngthomas/microhaplot/issues
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-09-28 00:53:53 UTC; thomasn
Author: Thomas Ng [aut, cre]
Maintainer: Thomas Ng <tngthomasng@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-03 07:40:05 UTC

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New package sfheaders with initial version 0.0.1
Package: sfheaders
Type: Package
Title: Constructs Simple Feature Objects
Version: 0.0.1
Authors@R: c( person("David", "Cooley", ,"david.cooley.au@gmail.com", role = c("aut", "cre")) )
Description: Converts R and 'Rcpp' objects to Simple Features 'sf', without depending on the Simple Feature library. Conversion functions are available at both the R level, and through 'Rcpp'.
License: GPL-3
URL: https://dcooley.github.io/sfheaders/
BugReports: https://github.com/dcooley/sfheaders/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
SystemRequirements: C++11
LinkingTo: Rcpp
Imports: Rcpp
Suggests: testthat, covr
NeedsCompilation: yes
Packaged: 2019-09-27 11:11:43 UTC; dave
Author: David Cooley [aut, cre]
Maintainer: David Cooley <david.cooley.au@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-03 06:50:02 UTC

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New package intsurvbin with initial version 0.0.4
Package: intsurvbin
Title: Survival and Binary Data Integration
Version: 0.0.4
Authors@R: c(person("Arnab", "Maity", email = "arnab.maity@pfizer.com", role = c("aut", "cre")), person("Antik", "Chakraborty", email = "antik.chakraborty@duke.edu", role = "aut"), person("Anirban", "Bhattacharya", email = "anirbanb@stat.tamu.edu", role = "aut"), person("Raymond", "Carroll", email = "carroll@stat.tamu.edu", role = "aut"), person("Bani", "K. Mallick", email = "bmallick@stat.tamu.edu", role = "aut"))
Description: Function to implement the horseshoe shrinkage prior in integrated survival and binary regression as developed in Maity et. al. (2019) <doi:10.1111/rssc.12377>.
Depends: R (>= 2.1.1)
Imports: msm, stats, tmvtnorm, mvtnorm, MHadaptive, mgcv
Suggests: smoothmest
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-27 14:04:34 UTC; MAITYA02
Author: Arnab Maity [aut, cre], Antik Chakraborty [aut], Anirban Bhattacharya [aut], Raymond Carroll [aut], Bani K. Mallick [aut]
Maintainer: Arnab Maity <arnab.maity@pfizer.com>
Repository: CRAN
Date/Publication: 2019-10-03 06:50:09 UTC

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New package drumr with initial version 0.1.0
Package: drumr
Title: Turn R into a Drum Machine
Version: 0.1.0
Authors@R: person("James", "Martherus", email = "james@martherus.com", role = c("aut", "cre"))
Description: Includes various functions for playing drum sounds. beat() plays a drum sound from one of the six included drum kits. tempo() sets spacing between calls to beat() in bpm. Together the two functions can be used to create many different drum patterns.
Depends: R (>= 3.1.0)
License: GPL-3
LazyData: true
Imports: audio, stringr
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-09-27 14:12:36 UTC; jamesmartherus
Author: James Martherus [aut, cre]
Maintainer: James Martherus <james@martherus.com>
Repository: CRAN
Date/Publication: 2019-10-03 06:50:12 UTC

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Wed, 02 Oct 2019

New package dodgr with initial version 0.2.4
Package: dodgr
Title: Distances on Directed Graphs
Version: 0.2.4
Authors@R: c( person("Mark", "Padgham", email="mark.padgham@email.com", role=c("aut", "cre")), person("Andreas", "Petutschnig", role="aut"), person("Robin", "Lovelace", role="ctb"), person("Andrew", "Smith", role="ctb"), person("Malcolm", "Morgan", role="ctb"), person("Shane", "Saunders", role="cph", comment="Original author of included code for priority heaps"))
Description: Distances on dual-weighted directed graphs using priority-queue shortest paths (Padgham (2019) <doi:10.32866/6945>). Weighted directed graphs have weights from A to B which may differ from those from B to A. Dual-weighted directed graphs have two sets of such weights. A canonical example is a street network to be used for routing in which routes are calculated by weighting distances according to the type of way and mode of transport, yet lengths of routes must be calculated from direct distances.
Depends: R (>= 3.5.0)
License: GPL-3
Imports: callr, digest, igraph, magrittr, methods, osmdata, Rcpp (>= 0.12.6), RcppParallel
Suggests: dplyr, geodist, ggplot2, igraphdata, jsonlite, knitr, purrr, rbenchmark, RColorBrewer, rmarkdown, roxygen2, scales, sf, testthat, tidygraph
LinkingTo: Rcpp, RcppParallel
SystemRequirements: C++11, GNU make
VignetteBuilder: knitr
NeedsCompilation: yes
Encoding: UTF-8
LazyData: true
URL: https://github.com/ATFutures/dodgr
BugReports: https://github.com/ATFutures/dodgr/issues
RoxygenNote: 6.1.1
Packaged: 2019-10-02 10:20:17 UTC; markus
Author: Mark Padgham [aut, cre], Andreas Petutschnig [aut], Robin Lovelace [ctb], Andrew Smith [ctb], Malcolm Morgan [ctb], Shane Saunders [cph] (Original author of included code for priority heaps)
Maintainer: Mark Padgham <mark.padgham@email.com>
Repository: CRAN
Date/Publication: 2019-10-02 15:00:02 UTC

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New package povcalnetR with initial version 0.1.0
Package: povcalnetR
Title: Client for the 'Povcalnet' API
Version: 0.1.0
Authors@R: c( person(given = "Tony", family = "Fujs", role = c("aut", "cre"), email = "tonyfujs@gmail.com"), person(given = "Ratnadeep", family = "Mitra", role = c("aut")), person(given = "Andres", family = "Castaneda", role = c("ctb")), person(given = "Espen", family = "Prydz", role = c("ctb")), person(given = "Christoph", family = "Lakner", role = c("ctb")), person(given = "World Bank", role = c("cph")) )
Description: Provides an interface to compute poverty and inequality indicators for more than 160 countries and regions from the World Bank's database of household surveys. It has the same functionality as the 'Povcalnet' website (<http://iresearch.worldbank.org/PovcalNet/>). 'Povcalnet' is a computational tool that allows users to estimate poverty rates for regions, sets of countries or individual countries, over time and at any poverty line. 'Povcalnet' is managed jointly by the data and research group in the World Bank's development economics division. It draws heavily upon a strong collaboration with the poverty and equity global practice, which is responsible for the gathering and harmonization of the underlying survey data.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.2.0)
Imports: purrr, stringr, httr, jsonlite, readr, tibble, dplyr, js, tidyr, memoise, naniar, ggthemes, ggplot2
Suggests: testthat (>= 2.1.0), assertthat, knitr, rmarkdown, forcats, scales
VignetteBuilder: knitr
URL: https://github.com/worldbank/povcalnetR
BugReports: https://github.com/worldbank/povcalnetR/issues
NeedsCompilation: no
Packaged: 2019-09-27 09:11:27 UTC; WB499754
Author: Tony Fujs [aut, cre], Ratnadeep Mitra [aut], Andres Castaneda [ctb], Espen Prydz [ctb], Christoph Lakner [ctb], World Bank [cph]
Maintainer: Tony Fujs <tonyfujs@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-02 10:20:02 UTC

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New package BayesBP with initial version 1.0
Package: BayesBP
Type: Package
Title: Bayesian Estimation using Bernstein Polynomial Fits Rate Matrix
Version: 1.0
Author: Li-Syuan Hong [aut, cre]
Maintainer: Li-Syuan Hong <lisyuan@nhri.org.tw>
Description: Smoothed lexis diagrams with Bayesian method specifically tailored to cancer incidence data. Providing to calculating slope and constructing credible interval. LC Chien et al. (2015) <doi:10.1080/01621459.2015.1042106>. LH Chien et al. (2017) <doi:10.1002/cam4.1102>.
License: GPL (>= 2)
Encoding: UTF-8
Date: 2019-09-02
LazyLoad: yes
LazyData: yes
Depends: R (>= 3.5.0),parallel,iterators,utils,stats,openxlsx
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2019-09-27 01:22:53 UTC; admin
Repository: CRAN
Date/Publication: 2019-10-02 10:20:05 UTC

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New package tabit with initial version 0.1.1
Package: tabit
Type: Package
Title: Simple Tabulation Made Simple
Version: 0.1.1
Date: 2019-09-19
Authors@R: person( given = "Peter", family = "Meissner", email = "retep.meissner@gmail.com", role = c("aut", "cre") )
Maintainer: Peter Meissner <retep.meissner@gmail.com>
Description: Simple tabulation should be dead simple. This package is an opinionated approach to easy tabulations while also providing exact numbers and allowing for re-usability. This is achieved by providing tabulations as data.frames with columns for values, optional variable names, frequency counts including and excluding NAs and percentages for counts including and excluding NAs. Also values are automatically sorted by in decreasing order of frequency counts to allow for fast skimming of the most important information.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-26 20:29:29 UTC; peter
Author: Peter Meissner [aut, cre]
Repository: CRAN
Date/Publication: 2019-10-02 10:00:02 UTC

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New package PRIMAL with initial version 1.0.0
Package: PRIMAL
Type: Package
Title: Parametric Simplex Method for Sparse Learning
Version: 1.0.0
Date: 2019-09-18
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: 2019-09-26 17:15:23 UTC; lizichong
RoxygenNote: 6.1.1
Repository: CRAN
Date/Publication: 2019-10-02 10:00:08 UTC

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New package mSTEM with initial version 1.0-1
Package: mSTEM
Type: Package
Title: Multiple Testing of Local Extrema for Detection of Change Points
Version: 1.0-1
Date: 2019-09-1
Author: Zhibing He and Dan Cheng
Maintainer: Zhibing He <zhibingh@asu.edu>
Description: A new approach to detect change points based on smoothing and multiple testing, which is for long data sequence modeled as piecewise constant functions plus stationary Gaussian noise, see Dan Cheng and Armin Schwartzman (2015) <arXiv:1504.06384>.
Depends: R (>= 3.1.0)
Imports: parallel, foreach, doParallel, latex2exp
URL: https://arxiv.org/abs/1504.06384
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-26 19:40:58 UTC; hzb
Repository: CRAN
Date/Publication: 2019-10-02 10:00:05 UTC

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New package GPvecchia with initial version 0.1.0
Package: GPvecchia
Type: Package
Title: Scalable Gaussian-Process Approximations
Version: 0.1.0
Date: 2019-09-25
Author: Matthias Katzfuss, Marcin Jurek, Daniel Zilber, Wenlong Gong, Joe Guinness, Jingjie Zhang
Maintainer: Matthias Katzfuss <katzfuss@gmail.com>
Description: Fast scalable Gaussian process approximations, particularly well suited to spatial (aerial, remote-sensed) and environmental data, described in more detail in Katzfuss and Guinness (2017) <arXiv:1708.06302>. Package also contains a fast implementation of the incomplete Cholesky decomposition (IC0), based on Schaefer et al. (2019) <arXiv:1706.02205> and MaxMin ordering proposed in Guinness (2018) <arXiv:1609.05372>.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.16), methods, stats, sparseinv, fields, Matrix(>= 1.2.14), parallel, GpGp, FNN
LinkingTo: Rcpp, RcppArmadillo, BH
RoxygenNote: 6.1.1
Suggests: mvtnorm, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-09-26 14:46:20 UTC; marcin
Repository: CRAN
Date/Publication: 2019-10-02 09:50:02 UTC

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New package ymlthis with initial version 0.1.0
Package: ymlthis
Title: Write 'YAML' for 'R Markdown', 'bookdown', 'blogdown', and More
Version: 0.1.0
Authors@R: c(person(given = "Malcolm", family = "Barrett", role = c("aut", "cre"), email = "malcolmbarrett@gmail.com", comment = c(ORCID = "0000-0003-0299-5825")), person(given = "Richard", family = "Iannone", role = "aut", email = "rich@rstudio.com", comment = c(ORCID = "0000-0003-3925-190X")), person(given = "RStudio", role = c("cph", "fnd")))
Description: Write 'YAML' front matter for R Markdown and related documents. yml_*() functions write 'YAML' and use_*() functions let you write the resulting 'YAML' to your clipboard or to .yml files related to your project.
License: MIT + file LICENSE
URL: https://ymlthis.r-lib.org, https://github.com/r-lib/ymlthis
BugReports: https://github.com/r-lib/ymlthis/issues
Depends: R (>= 3.2)
Imports: crayon, fs, glue, magrittr, miniUI, purrr (>= 0.3.2), rlang, rmarkdown, rstudioapi, shiny, shinyBS, stringr, usethis (>= 1.5.0), whoami, withr, yaml
Suggests: blogdown, bookdown, covr, knitr, pkgdown, prettydoc, roxygen2, spelling, testthat, xaringan
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-23 19:13:57 UTC; malcolmbarrett
Author: Malcolm Barrett [aut, cre] (<https://orcid.org/0000-0003-0299-5825>), Richard Iannone [aut] (<https://orcid.org/0000-0003-3925-190X>), RStudio [cph, fnd]
Maintainer: Malcolm Barrett <malcolmbarrett@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-02 08:50:02 UTC

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New package MLRShiny2 with initial version 0.1.0
Package: MLRShiny2
Type: Package
Title: Interactive Application for Working with Multiple Linear Regression
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive application for working with multiple linear regression technique. The application has a template for solving problems on multiple linear regression. Runtime examples are provided at <https://kartikeyastat.shinyapps.io/MLR_WEB_K/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,shinyAce,dplyr,psych,QuantPsyc,forecast,corrgram
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-23 15:58:36 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-10-02 08:40:02 UTC

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New package DPQ with initial version 0.3-3
Package: DPQ
Title: Density, Probability, Quantile ('DPQ') Computations
Version: 0.3-3
Date: 2019-09-24
Authors@R: c(person("Martin","Maechler", role=c("aut","cre"), email="maechler@stat.math.ethz.ch", comment = c(ORCID = "0000-0002-8685-9910")) , person("Morten", "Welinder", role = "ctb", comment = "pgamma C code, see PR#7307, Jan. 2005") , person("Wolfgang", "Viechtbauer", role = "ctb", comment = "dtWV(), 2002") , person("Ross", "Ihaka", role = "ctb", comment = "src/qchisq_appr.c") , person("R-core", email = "R-core@R-project.org", role = "ctb", comment = "src/{dpq.h, algdiv.c, pnchisq.c}") )
Description: Computations for approximations and alternatives for the 'DPQ' (Density (pdf), Probability (cdf) and Quantile) functions for probability distributions in R. Primary focus is on (central and non-central) beta, gamma and related distributions such as the chi-squared, F, and t. -- This is for the use of researchers in these numerical approximation implementations, notably for my own use in order to improve R`s own pbeta(), qgamma(), ..., etc: {'"dpq"'-functions}. -- We plan to complement with 'DPQmpfr' to be suggested later.
Depends: R (>= 3.5.0)
Imports: stats, graphics, methods, utils, sfsmisc
Suggests: Rmpfr, Matrix, mgcv, scatterplot3d, akima
SuggestsNote: Matrix only for its "test-tools-1.R"; mgcv,scatt..,akima: some tests/
License: GPL (>= 2)
Encoding: UTF-8
Author: Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>), Morten Welinder [ctb] (pgamma C code, see PR#7307, Jan. 2005), Wolfgang Viechtbauer [ctb] (dtWV(), 2002), Ross Ihaka [ctb] (src/qchisq_appr.c), R-core [ctb] (src/{dpq.h, algdiv.c, pnchisq.c})
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>
Repository: CRAN
Repository/R-Forge/Project: specfun
Repository/R-Forge/Revision: 111
Repository/R-Forge/DateTimeStamp: 2019-09-24 13:38:29
Date/Publication: 2019-10-02 09:00:02 UTC
NeedsCompilation: yes
Packaged: 2019-09-24 13:50:27 UTC; rforge

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Tue, 01 Oct 2019

New package KTensorGraphs with initial version 0.2
Package: KTensorGraphs
Type: Package
Title: Co-Tucker3 Analysis of Two Sequences of Matrices
Version: 0.2
Date: 2019-10-01
Author: Miguel Rodriguez-Rosa <miguel_rosa90@usal.es> [aut, cre]
Maintainer: Miguel Rodriguez-Rosa <miguel_rosa90@usal.es>
Description: Provides a function called COTUCKER3() (Co-Inertia Analysis + Tucker3 method) which performs a Co-Tucker3 analysis of two sequences of matrices, as well as other functions called PCA() (Principal Component Analysis) and BGA() (Between-Groups Analysis), which perform analysis of one matrix, COIA() (Co-Inertia Analysis), which performs analysis of two matrices, PTA() (Partial Triadic Analysis) and TUCKER3(), which perform analysis of a sequence of matrices, and BGCOIA() (Between-Groups Co-Inertia Analysis), STATICO() (STATIS method + Co-Inertia Analysis), COSTATIS() (Co-Inertia Analysis + STATIS method), which also perform analysis of two sequences of matrices.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2019-10-01 07:23:50 UTC; Magnet
Repository: CRAN
Date/Publication: 2019-10-01 18:40:09 UTC

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New package baycn with initial version 1.0.0
Package: baycn
Type: Package
Title: Bayesian Inference for Causal Networks
Version: 1.0.0
Author: Evan A Martin [aut, cre], Audrey Qiuyan Fu [aut]
Maintainer: Evan A Martin <evanamartin@gmail.com>
Description: A Bayesian hybrid approach for inferring Directed Acyclic Graphs (DAGs) for continuous, discrete, and mixed data. The algorithm can use the graph inferred by another more efficient graph inference method as input; the input graph may contain false edges or undirected edges but can help reduce the search space to a more manageable size. A Bayesian Markov chain Monte Carlo algorithm is then used to infer the probability of direction and absence for the edges in the network. References: Martin and Fu (2019) <arXiv:1909.10678>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: egg, ggplot2, MASS, methods
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-09-25 17:33:01 UTC; Evatar
Repository: CRAN
Date/Publication: 2019-10-01 15:30:02 UTC

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New package KbMvtSkew with initial version 1.0.1
Package: KbMvtSkew
Type: Package
Title: Khattree-Bahuguna's Univariate and Multivariate Skewness
Version: 1.0.1
Authors@R: c( person("Zhixin", "Lun", email = "zlun@oakland.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8980-1554")), person("Ravindra", "Khattree", email = "khattree@oakland.edu", role = "aut", comment = c(ORCID = "0000-0002-9305-2365")))
Maintainer: Zhixin Lun <zlun@oakland.edu>
Description: Computes Khattree-Bahuguna's univariate and multivariate skewness, principal-component-based Khattree-Bahuguna's multivariate skewness. It also provides several measures of univariate or multivariate skewnesses including, Pearson’s coefficient of skewness, Bowley’s univariate skewness and Mardia's multivariate skewness. See Khattree, R. and Bahuguna, M. (2019) <doi: 10.1007/s41060-018-0106-1>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: stats
Depends: R (>= 3.5.0)
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-24 21:35:46 UTC; Zhixin Lun
Author: Zhixin Lun [aut, cre] (<https://orcid.org/0000-0002-8980-1554>), Ravindra Khattree [aut] (<https://orcid.org/0000-0002-9305-2365>)
Repository: CRAN
Date/Publication: 2019-10-01 14:40:08 UTC

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New package hilldiv with initial version 1.5.1
Package: hilldiv
Title: Integral Analysis of Diversity Based on Hill Numbers
Version: 1.5.1
Author: Antton Alberdi [aut, cre]
Maintainer: Antton Alberdi <antton.alberdi@bio.ku.dk>
Description: Tools for analysing, comparing, visualising and partitioning diversity based on Hill numbers. 'hilldiv' is an R package that provides a set of functions to assist analysis of diversity for diet reconstruction, microbial community profiling or more general ecosystem characterisation analyses based on Hill numbers, using OTU/ASV tables and associated phylogenetic trees as inputs. The package includes functions for (phylo)diversity measurement, (phylo)diversity profile plotting, (phylo)diversity comparison between samples and groups, (phylo)diversity partitioning and (dis)similarity measurement. All of these grounded in abundance-based and incidence-based Hill numbers. The statistical framework developed around Hill numbers encompasses many of the most broadly employed diversity (e.g. richness, Shannon index, Simpson index), phylogenetic diversity (e.g. Faith's PD, Allen's H, Rao's quadratic entropy) and dissimilarity (e.g. Sorensen index, Unifrac distances) metrics. This enables the most common analyses of diversity to be performed while grounded in a single statistical framework. The methods are described in Jost et al. (2007) <DOI:10.1890/06-1736.1>, Chao et al. (2010) <DOI:10.1098/rstb.2010.0272> and Chiu et al. (2014) <DOI:10.1890/12-0960.1>; and reviewed in the framework of molecularly characterised biological systems in Alberdi & Gilbert (2019) <DOI:10.1111/1755-0998.13014>.
License: GPL-3
LazyData: true
URL: https://github.com/anttonalberdi/hilldiv
BugReports: https://github.com/anttonalberdi/hilldiv/issues
Depends: R (>= 3.1.0)
Suggests:
Imports: stats, ggplot2, scales, ggpubr, RColorBrewer, data.table, ape, vegan, geiger, qgraph, FSA
Encoding: UTF-8
RoxygenNote: 6.1.1
Collate: 'index_div.R' 'hill_div.R' 'div_profile.R' 'div_profile_plot.R' 'div_test.R' 'div_test_plot.R' 'depth_cov.R' 'div_part.R' 'alpha_div.R' 'gamma_div.R' 'beta_dis.R' 'pair_dis.R' 'pair_dis_plot.R' 'UqN.R' 'CqN.R' 'VqN.R' 'SqN.R' 'match_data.R' 'depth_filt.R' 'copy_filt.R' 'to.incidence.R' 'tss.R' 'is.nested.R' 'tree_depth.R' 'data.R'
NeedsCompilation: no
Packaged: 2019-10-01 13:32:38 UTC; jpl786
Repository: CRAN
Date/Publication: 2019-10-01 14:40:02 UTC

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New package factorEx with initial version 1.0.0
Package: factorEx
Type: Package
Title: Design and Analysis for Factorial Experiments
Version: 1.0.0
Author: Naoki Egami, Brandon de la Cuesta, Kosuke Imai
Maintainer: Naoki Egami <naoki.egami5@gmail.com>
Description: Provides design-based and model-based estimators for the population average marginal component effects in general factorial experiments, including conjoint analysis. The package also implements a series of recommendations offered in de la Cuesta, Egami, and Imai (2019+), and Egami and Imai (2019) <doi:10.1080/01621459.2018.1476246>.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.5.0), arm, genlasso
Imports: prodlim, sandwich, igraph, pbmcapply, pbapply, mvtnorm, stringr, doParallel, foreach, estimatr
URL: https://github.com/naoki-egami/factorEx
BugReports: https://github.com/naoki-egami/factorEx/issues
NeedsCompilation: no
Packaged: 2019-10-01 13:03:08 UTC; negami
Repository: CRAN
Date/Publication: 2019-10-01 14:40:05 UTC

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New package amber with initial version 0.1.5
Package: amber
Type: Package
Title: Automated Model Benchmarking Package for the Canadian Land Surface Scheme
Version: 0.1.5
Author: Christian Seiler [cre, aut]
Maintainer: Christian Seiler <christian.seiler@canada.ca>
Description: Functions that quantify how well the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) reproduces land surface processes when compared against reference data. To summarize model performance across different statistical metrics, this package employs a skill score system that was originally developed by Collier et. al., (2018) <doi:10.1029/2018MS001354> .
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Imports: classInt, doParallel, foreach, latex2exp, ncdf4, parallel, raster, rgeos, scico, sp, spatial.tools, stats, utils, viridis, xtable
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-24 15:14:32 UTC; acrpcsr
Repository: CRAN
Date/Publication: 2019-10-01 14:20:02 UTC

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New package signs with initial version 0.1.0
Package: signs
Title: Insert Proper Minus Signs
Version: 0.1.0
Authors@R: person(given = c("Benjamin", "E."), family = "Wolfe", role = c("aut", "cre"), email = "benjamin.e.wolfe@gmail.com", comment = c(ORCID = "0000-0002-4339-9328"))
Description: Provides convenience functions to replace hyphen-minuses (ASCII 45) with proper minus signs (Unicode character 2212). The minus sign is wider and slightly nicer for display than the hyphen-minus we use for computation.
URL: https://benjaminwolfe.github.io/signs
BugReports: https://github.com/BenjaminWolfe/signs/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: scales, rlang (>= 0.4.0)
RoxygenNote: 6.1.1
Suggests: ggplot2, dplyr, ggrepel, testthat (>= 2.1.0), knitr, rmarkdown, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-09-24 04:57:02 UTC; Karin
Author: Benjamin E. Wolfe [aut, cre] (<https://orcid.org/0000-0002-4339-9328>)
Maintainer: Benjamin E. Wolfe <benjamin.e.wolfe@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-01 12:40:02 UTC

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New package Rquefts with initial version 1.0-5
Package: Rquefts
Type: Package
Title: Quantitative Evaluation of the Native Fertility of Tropical Soils
Version: 1.0-5
Date: 2019-09-30
LinkingTo: Rcpp
SystemRequirements: C++11
Imports: meteor, methods, Rcpp (>= 0.12.4)
Authors@R: c( person("Robert J.", "Hijmans", role = c("cre", "aut"), email = "r.hijmans@gmail.com"), person("Joost", "Wolff", role = "ctb"))
Description: An implementation of the QUEFTS (Quantitative Evaluation of the Native Fertility of Tropical Soils) model. The model estimates nutrient requirements for crops to achieve a target yield given native soil fertility, as estimated from a few soil chemical properties. See Janssen et al. (1990) <doi:10.1016/0016-7061(90)90021-Z> for the technical details and Sattari et al. (2014) <doi:10.1016/j.fcr.2013.12.005> for a recent evaluation.
License: GPL (>= 3)
BugReports: https://github.com/cropmodels/Rquefts/issues
URL: https://github.com/cropmodels/Rquefts/
NeedsCompilation: yes
Packaged: 2019-10-01 02:55:13 UTC; rhijm
Author: Robert J. Hijmans [cre, aut], Joost Wolff [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-01 12:00:14 UTC

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New package pedmut with initial version 0.1.0
Package: pedmut
Title: Mutation Models for Pedigree Likelihood Computations
Version: 0.1.0
Authors@R: person("Magnus Dehli", "Vigeland", email = "m.d.vigeland@medisin.uio.no", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9134-4962"))
Description: A collection of functions for modeling mutations in pedigrees with marker data, as used e.g. in likelihood computations with microsatellite data. Implemented models include proportional and stepwise models, as well as random models for experimental work, and custom models allowing the user to apply any valid mutation matrix. Allele lumping is done following the lumpability criteria of Kemeny and Snell (1976), ISBN:0387901922.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-09-30 18:06:12 UTC; magnusdv
Author: Magnus Dehli Vigeland [aut, cre] (<https://orcid.org/0000-0002-9134-4962>)
Maintainer: Magnus Dehli Vigeland <m.d.vigeland@medisin.uio.no>
Repository: CRAN
Date/Publication: 2019-10-01 12:00:02 UTC

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New package kubik with initial version 0.1.1
Package: kubik
Title: Cubic Hermite Splines
Version: 0.1.1
Date: 2019-10-01
License: GPL (>= 2)
Maintainer: Abby Spurdle <spurdle.a@gmail.com>
Author: Abby Spurdle
URL: https://sites.google.com/site/spurdlea/r
Description: Computes (constructs, plots and evaluates) constrained cubic Hermite splines, which can be used to construct monotonic splines. Computes their first derivatives, indefinite integrals and smooth approximations of their first, second and higher derivatives. Also, computes their roots, including their argmins, argmaxs and inflection points.
Imports: intoo
Suggests: zeallot
NeedsCompilation: no
Packaged: 2019-10-01 01:38:36 UTC; Student9
Repository: CRAN
Date/Publication: 2019-10-01 12:00:05 UTC

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New package goffda with initial version 0.0.5
Package: goffda
Type: Package
Title: Goodness-of-Fit Tests for Functional Data
Version: 0.0.5
Date: 2019-09-30
Authors@R: c( person(given = "Eduardo", family = "García-Portugués", role = c("aut", "cre"), email = "edgarcia@est-econ.uc3m.es"), person("Javier", "Álvarez-Liébana", role = "aut", email = "alvarezljavier@uniovi.es"), person("Gonzalo", "Álvarez-Pérez", role = "ctb", email = "gonzaloalvarez@uniovi.es"), person("Manuel", "Febrero-Bande", role = "ctb", email = "manuel.febrero@usc.es") )
Description: Implementation of several goodness-of-fit tests for functional data. Currently, mostly related with the functional linear model with functional/scalar response and functional/scalar predictor. The package allows for the replication of the data applications considered in García-Portugués, Álvarez-Liébana, Álvarez-Pérez and González-Manteiga (2019) <arXiv:1909.07686>.
License: GPL-3
LazyData: true
Depends: R (>= 3.5.0), Rcpp
Imports: fda.usc, glmnet, ks
Suggests: microbenchmark, knitr, viridisLite, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
URL: https://github.com/egarpor/goffda
BugReports: https://github.com/egarpor/goffda
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-10-01 07:18:49 UTC; Eduardo
Author: Eduardo García-Portugués [aut, cre], Javier Álvarez-Liébana [aut], Gonzalo Álvarez-Pérez [ctb], Manuel Febrero-Bande [ctb]
Maintainer: Eduardo García-Portugués <edgarcia@est-econ.uc3m.es>
Repository: CRAN
Date/Publication: 2019-10-01 12:00:08 UTC

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New package gemma2 with initial version 0.1.1
Package: gemma2
Title: GEMMA Multivariate Linear Mixed Model
Version: 0.1.1
Authors@R: c( person(given = "Frederick", family = "Boehm", email = "frederick.boehm@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1644-5931") ) )
Description: Fits a multivariate linear mixed effects model that uses a polygenic term, after Zhou & Stephens (2014) (<https://www.nature.com/articles/nmeth.2848>). Of particular interest is the estimation of variance components with restricted maximum likelihood (REML) methods. Genome-wide efficient mixed-model association (GEMMA), as implemented in the package 'gemma2', uses an expectation-maximization algorithm for variance components inference for use in quantitative trait locus studies.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/fboehm/gemma2
BugReports: https://github.com/fboehm/gemma2/issues
Suggests: covr, testthat, knitr, rmarkdown
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Imports: readr, Matrix
Language: en-US
NeedsCompilation: no
Packaged: 2019-09-30 15:47:45 UTC; fred
Author: Frederick Boehm [aut, cre] (<https://orcid.org/0000-0002-1644-5931>)
Maintainer: Frederick Boehm <frederick.boehm@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-01 12:00:11 UTC

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Mon, 30 Sep 2019

New package ModStatR with initial version 1.3.0
Package: ModStatR
Type: Package
Title: Statistical Modelling in Action with R
Version: 1.3.0
Date: 2019-09-23
Depends: R (>= 3.5.0)
Imports: stats, boot, ggplot2, BioStatR, jmuOutlier, ellipse, hypergeo, gsl
Authors@R: c( person(given = "Frederic", family= "Bertrand", role = c("cre", "aut"), email = "frederic.bertrand@math.unistra.fr", comment = c(ORCID = "0000-0002-0837-8281")), person(given = "Emmanuelle", family= "Claeys", role = c("aut"), email = "emmanuelle.claeys@unistra.fr"), person(given = "Myriam", family= "Maumy-Bertrand", role = c("aut"), email = "myriam.maumy-bertrand@math.unistra.fr", comment = c(ORCID = "0000-0002-4615-1512")))
Author: Frederic Bertrand [cre, aut] (<https://orcid.org/0000-0002-0837-8281>), Emmanuelle Claeys [aut], Myriam Maumy-Bertrand [aut] (<https://orcid.org/0000-0002-4615-1512>)
Maintainer: Frederic Bertrand <frederic.bertrand@math.unistra.fr>
Description: Datasets and functions for the book "Modélisation statistique par la pratique avec R", F. Bertrand, E. Claeys and M. Maumy-Bertrand (2019, ISBN:9782100793525, Dunod, Paris). The first chapter of the book is dedicated to an introduction to the R statistical software. The second chapter deals with correlation analysis: Pearson, Spearman and Kendall simple, multiple and partial correlation coefficients. New wrapper functions for permutation tests or bootstrap of matrices of correlation are provided with the package. The third chapter is dedicated to data exploration with factorial analyses (PCA, CA, MCA, MDA) and clustering. The fourth chapter is dedicated to regression analysis: fitting and model diagnostics are detailed. The exercises focus on covariance analysis, logistic regression, Poisson regression, two-way analysis of variance for fixed or random factors. Various example datasets are shipped with the package: for instance on pokemon, world of warcraft, house tasks or food nutrition analyses.
LazyLoad: yes
LazyData: yes
License: GPL-3
Encoding: UTF-8
Classification/MSC:
URL: http://www-irma.u-strasbg.fr/~fbertran/, https://github.com/fbertran/ModStatR
BugReports: https://github.com/fbertran/ModStatR/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-24 00:29:41 UTC; fbertran
Repository: CRAN
Date/Publication: 2019-09-30 16:20:02 UTC

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New package Mapinguari with initial version 1.0.0
Package: Mapinguari
Type: Package
Title: Process-Based Biogeographical Analysis
Version: 1.0.0
Authors@R: c(person("Gabriel", "Caetano", email = "gabrielhoc@gmail.com", role = c("aut", "cre")), person("Juan", "Santos", email = "infraguttatus@gmail.com", role = c("aut")), person("Barry", "Sinervo", email = "lizardrps@gmail.com", role = c("aut")))
Description: Facilitates the incorporation of biological processes in biogeographical analyses. It offers conveniences in fitting, comparing and extrapolating models of biological processes such as physiology and phenology. These spatial extrapolations can be informative by themselves, but also complement traditional correlative species distribution models, by mixing environmental and process-based predictors.
Depends: R (>= 3.5)
License: GPL-2
Encoding: UTF-8
LazyData: true
URL: http://github.com/gabrielhoc/Mapinguari
BugReports: http://github.com/gabrielhoc/Mapinguari/issues
Suggests: EcoHydRology, geosphere, mgcv
Imports: dplyr, magrittr, parallel, raster, rgdal, rlang, stringr, testthat
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-23 19:43:39 UTC; gabrielhenriquedeoliveiracaetano
Author: Gabriel Caetano [aut, cre], Juan Santos [aut], Barry Sinervo [aut]
Maintainer: Gabriel Caetano <gabrielhoc@gmail.com>
Repository: CRAN
Date/Publication: 2019-09-30 16:40:02 UTC

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New package gg.gap with initial version 1.3
Package: gg.gap
Type: Package
Title: Define Segments in y-Axis for 'ggplot2'
Version: 1.3
Authors@R: c( person("Jiacheng", "Lou", email = "loujiacheng1986@foxmail.com", role = c("aut", "cre")), person("Jing", "Zhang", role = "aut"), person("Yizhu", "Lvy", role = "aut"), person("Zhi", "Jin", role = "aut") )
Description: It is not very easy to define segments for y-axis in a 'ggplot2' plot. gg.gap() function in this package can carry it out.
Imports: ggplot2, cowplot, grid
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/ChrisLou-bioinfo/gg.gap
BugReports: https://github.com/ChrisLou-bioinfo/gg.gap/issues
NeedsCompilation: no
Packaged: 2019-09-23 15:12:20 UTC; asus
Author: Jiacheng Lou [aut, cre], Jing Zhang [aut], Yizhu Lvy [aut], Zhi Jin [aut]
Maintainer: Jiacheng Lou <loujiacheng1986@foxmail.com>
Repository: CRAN
Date/Publication: 2019-09-30 16:10:02 UTC

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New package mlr3tuning with initial version 0.1.0
Package: mlr3tuning
Title: Tuning for 'mlr3'
Version: 0.1.0
Authors@R: c(person(given = "Michel", family = "Lang", role = c("cre", "aut"), email = "michellang@gmail.com", comment = c(ORCID = "0000-0001-9754-0393")), person(given = "Jakob", family = "Richter", role = "aut", email = "jakob1richter@gmail.com", comment = c(ORCID = "0000-0003-4481-5554")), person(given = "Bernd", family = "Bischl", role = "aut", email = "bernd_bischl@gmx.net", comment = c(ORCID = "0000-0001-6002-6980")), person(given = "Daniel", family = "Schalk", role = "aut", email = "daniel.schalk@stat.uni-muenchen.de", comment = c(ORCID = "0000-0003-0950-1947")))
Description: Implements methods for hyperparameter tuning with 'mlr3', e.g. Grid Search, Random Search, or Simulated Annealing. Various termination criteria can be set and combined. The class 'AutoTuner' provides a convenient way to perform nested resampling in combination with 'mlr3'.
License: LGPL-3
URL: https://mlr3tuning.mlr-org.com, https://github.com/mlr-org/mlr3tuning
BugReports: https://github.com/mlr-org/mlr3tuning/issues
Depends: R (>= 3.1.0)
Imports: checkmate (>= 1.9.4), data.table, lgr, mlr3, mlr3misc, paradox, R6
Suggests: GenSA, rpart, testthat
Encoding: UTF-8
NeedsCompilation: no
RoxygenNote: 6.1.1
Collate: 'AutoTuner.R' 'mlr_terminators.R' 'Terminator.R' 'TerminatorClockTime.R' 'TerminatorCombo.R' 'TerminatorEvals.R' 'TerminatorModelTime.R' 'TerminatorNone.R' 'TerminatorPerfReached.R' 'TerminatorStagnation.R' 'mlr_tuners.R' 'Tuner.R' 'TunerDesignPoints.R' 'TunerGenSA.R' 'TunerGridSearch.R' 'TunerRandomSearch.R' 'TuningInstance.R' 'assertions.R' 'helper.R' 'sugar.R' 'zzz.R'
Packaged: 2019-09-22 19:00:14 UTC; michel
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Daniel Schalk [aut] (<https://orcid.org/0000-0003-0950-1947>)
Maintainer: Michel Lang <michellang@gmail.com>
Repository: CRAN
Date/Publication: 2019-09-30 15:20:02 UTC

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New package rasterpdf with initial version 0.1.0
Package: rasterpdf
Title: Plot Raster Graphics in PDF Files
Version: 0.1.0
Authors@R: person(given = "Ilari", family = "Scheinin", role = c("aut", "cre"), email = "ilari.scheinin+rasterpdf@gmail.com", comment = c(ORCID = "0000-0002-4696-9066"))
Description: The ability to plot raster graphics in PDF files can be useful when one needs multi-page documents, but the plots contain so many individual elements that (the usual) use of vector graphics results in inconveniently large file sizes. Internally, the package plots each individual page as a PNG, and then combines them in one PDF file.
License: MIT + file LICENSE
Imports: methods, png
Suggests: covr, lintr, pkgdown, ragg, testthat
URL: https://ilarischeinin.github.io/rasterpdf, https://github.com/ilarischeinin/rasterpdf
BugReports: https://github.com/ilarischeinin/rasterpdf/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-22 13:53:57 UTC; ischeini
Author: Ilari Scheinin [aut, cre] (<https://orcid.org/0000-0002-4696-9066>)
Maintainer: Ilari Scheinin <ilari.scheinin+rasterpdf@gmail.com>
Repository: CRAN
Date/Publication: 2019-09-30 15:00:02 UTC

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New package support.BWS3 with initial version 0.1-1
Package: support.BWS3
Type: Package
Title: Basic Functions for Supporting Case 3 Best-Worst Scaling
Version: 0.1-1
Date: 2019-09-21
Author: Hideo Aizaki
Maintainer: Hideo Aizaki <azk-r@spa.nifty.com>
Description: Provides basic functions that support an implementation of Case 3 (multi-profile case) best-worst scaling (BWS). Case 3 BWS is a question-based survey method to elicit people's preferences for attribute levels. Case 3 BWS constructs various combinations of attribute levels (profiles) and then asks respondents to select the best and worst profiles in each choice set. A main function creates a dataset for Case 3 BWS analysis from the choice sets and the responses to the questions. For details on Case 3 BWS, see Louviere et al. (2015) <doi:10.1017/CBO9781107337855>.
License: GPL (>= 2)
Suggests: support.CEs, survival
NeedsCompilation: no
Packaged: 2019-09-21 07:17:58 UTC; user
Repository: CRAN
Date/Publication: 2019-09-30 12:10:02 UTC

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New package gnn with initial version 0.0-1
Package: gnn
Version: 0.0-1
Title: Generative Neural Networks
Description: Tools to set up, train, store, load, investigate and analyze generative neural networks. In particular, functionality for generative moment matching networks is provided. See Hofert, Prasad, Zhu (2018) <arXiv:abs/1811.00683> for more details.
Authors@R: c(person(given = "Marius", family = "Hofert", role = c("aut", "cre"), email = "marius.hofert@uwaterloo.ca", comment = c(ORCID = "0000-0001-8009-4665")), person(given = "Avinash", family = "Prasad", role = "aut", email = "a2prasad@uwaterloo.ca"))
Maintainer: Marius Hofert <marius.hofert@uwaterloo.ca>
Depends: R (>= 3.5.0)
Imports: keras, tensorflow, qrng, methods, tools
Suggests: copula, qrmtools, qrmdata, latticeExtra, RnavGraphImageData
Enhances:
License: GPL (>= 3)
SystemRequirements: TensorFlow (https://www.tensorflow.org/)
NeedsCompilation: no
Repository: CRAN
Encoding: UTF-8
Date/Publication: 2019-09-30 11:30:02 UTC
Packaged: 2019-09-20 07:45:40 UTC; mhofert
Author: Marius Hofert [aut, cre] (<https://orcid.org/0000-0001-8009-4665>), Avinash Prasad [aut]

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New package ggmr with initial version 0.1.1
Package: ggmr
Type: Package
Title: Generalized Gauss Markov Regression
Version: 0.1.1
Date: 2019-09-20
Author: Hugo Gasca-Aragon
Maintainer: Hugo Gasca-Aragon <hugo_gasca_aragon@hotmail.com>
Description: Implements the generalized Gauss Markov regression, this is useful when both predictor and response have uncertainty attached to them and also when covariance within the predictor, within the response and between the predictor and the response is present. Base on the results published in guide ISO/TS 28037 (2010) <https://www.iso.org/standard/44473.html>.
Depends: stats (>= 3.4.0), MASS (>= 7.3), R (>= 3.4.0)
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-09-21 02:30:13 UTC; hugo_
Repository: CRAN
Date/Publication: 2019-09-30 11:50:02 UTC

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New package biclustermd with initial version 0.1.0
Package: biclustermd
Type: Package
Title: Biclustering with Missing Data
Version: 0.1.0
Authors@R: c( person("John", "Reisner", email = "johntreisner@gmail.com", role = c("cre", "aut", "cph")), person("Hieu", "Pham", email = "phieu93@gmail.com", role = c("ctb", "cph")), person("Jing", "Li", email = "jingli2014cymail@gmail.com", role = c("ctb", "cph")))
Maintainer: John Reisner <johntreisner@gmail.com>
Description: Biclustering is a statistical learning technique that simultaneously partitions and clusters rows and columns of a data matrix. Since the solution space of biclustering is in infeasible to completely search with current computational mechanisms, this package uses a greedy heuristic. The algorithm featured in this package is, to the best our knowledge, the first biclustering algorithm to work on data with missing values. Li, J., Reisner, J., Pham, H., Olafsson, S., and Vardeman, S. (2019) Biclustering for Missing Data. Information Sciences, Submitted.
URL: http://github.com/jreisner/biclustermd
BugReports: http://github.com/jreisner/biclustermd/issues
Depends: ggplot2 (>= 3.0.0), R (>= 3.5.0), tidyr (>= 0.8.1)
Imports: biclust (>= 2.0.1), clues (>= 0.5.9), doParallel (>= 1.0.14), dplyr (>= 0.7.6), foreach (>= 1.4.4), magrittr (>= 1.5), nycflights13 (>= 1.0.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-09-21 01:22:48 UTC; johnreisner
Author: John Reisner [cre, aut, cph], Hieu Pham [ctb, cph], Jing Li [ctb, cph]
Repository: CRAN
Date/Publication: 2019-09-30 11:40:06 UTC

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New package bama with initial version 0.9.1
Package: bama
Title: High Dimensional Bayesian Mediation Analysis
Version: 0.9.1
URL: https://github.com/umich-cphds/bama
BugReports: https://github.com/umich-cphds/bama/issues
Authors@R: c(person(given = "Alexander", family = "Rix", role = c("aut", "cre"), email = "alexrix@umich.edu"), person(given = "Yanyi", family = "Song", role = c("aut"), email = "yanys@umich.edu"))
Description: Perform mediation analysis in the presence of high-dimensional mediators based on the potential outcome framework. Bayesian Mediation Analysis (BAMA), developed by Song et al (2018) <doi:10.1101/467399>, relies on two Bayesian sparse linear mixed models to simultaneously analyze a relatively large number of mediators for a continuous exposure and outcome assuming a small number of mediators are truly active. This sparsity assumption also allows the extension of univariate mediator analysis by casting the identification of active mediators as a variable selection problem and applying Bayesian methods with continuous shrinkage priors on the effects.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-09-19 13:31:02 UTC; alexrix
Author: Alexander Rix [aut, cre], Yanyi Song [aut]
Maintainer: Alexander Rix <alexrix@umich.edu>
Repository: CRAN
Date/Publication: 2019-09-30 11:30:05 UTC

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Fri, 27 Sep 2019

New package TAG with initial version 0.1.0
Package: TAG
Type: Package
Title: Transformed Additive Gaussian Processes
Version: 0.1.0
Author: Li-Hsiang Lin and V. Roshan Joseph
Maintainer: Li-Hsiang Lin <llin79@gatech.edu>
Description: Implement the transformed additive Gaussian (TAG) process and the transformed approximately additive Gaussian (TAAG) process proposed in Lin and Joseph (2019+) <DOI:10.1080/00401706.2019.1665592>. These functions can be used to model deterministic computer experiments, obtain predictions at new inputs, and quantify the uncertainty of the predictions.
License: GPL-2
Depends: R (>= 3.5.0)
Imports: Rcpp, DiceKriging, Matrix, mgcv, FastGP, mlegp, randtoolbox, doParallel
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-09-20 19:45:23 UTC; llin79
Repository: CRAN
Date/Publication: 2019-09-27 11:10:02 UTC

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New package SimDissolution with initial version 0.1.0
Package: SimDissolution
Type: Package
Title: Modeling and Assessing Similarity of Drug Dissolutions Profiles
Version: 0.1.0
Author: Kathrin Moellenhoff
Maintainer: Kathrin Moellenhoff <kathrin.moellenhoff@rub.de>
Description: Implementation of a model-based bootstrap approach for testing whether two formulations are similar. The package provides a function for fitting a pharmacokinetic model to time-concentration data and comparing the results for all five candidate models regarding the Residual Sum of Squares (RSS). The candidate set contains a First order, Hixson-Crowell, Higuchi, Weibull and a logistic model. The assessment of similarity implemented in this package is performed regarding the maximum deviation of the profiles. See Moellenhoff et al. (2018) <doi:10.1002/sim.7689> for details.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: dplyr, alabama, mvtnorm, graphics
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-20 06:48:20 UTC; Kathrin
Repository: CRAN
Date/Publication: 2019-09-27 10:20:11 UTC

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New package nlpred with initial version 1.0.0
Package: nlpred
Title: Estimators of Non-Linear Cross-Validated Risks Optimized for Small Samples
Version: 1.0.0
Authors@R: person("David", "Benkeser", email = "benkeser@emory.edu", role = c("aut", "cre"))
Description: Methods for obtaining improved estimates of non-linear cross-validated risks are obtained using targeted minimum loss-based estimation, estimating equations, and one-step estimation. Cross-validated area under the receiver operating characteristics curve (LeDell, Petersen, van der Laan (2015), <doi:10.1214/15-EJS1035>) and other metrics are included.
Depends: R (>= 3.2.0), data.table
Imports: stats, utils, SuperLearner, cvAUC, ROCR, Rdpack, bde, np, assertthat
Suggests: knitr, rmarkdown, testthat, prettydoc, randomForest, ranger, xgboost, glmnet,
License: MIT + file LICENSE
Encoding: UTF-8
VignetteBuilder: knitr, rmarkdown
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-20 13:58:21 UTC; dbenkes
Author: David Benkeser [aut, cre]
Maintainer: David Benkeser <benkeser@emory.edu>
Repository: CRAN
Date/Publication: 2019-09-27 11:00:02 UTC

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New package LPBkg with initial version 1.1.4
Package: LPBkg
Type: Package
Title: Detecting New Signals under Background Mismodelling
Version: 1.1.4
Author: Sara Algeri <salgeri@umn.edu>, Haoran Liu<liu00728@umn.edu>
Maintainer: Sara Algeri <salgeri@umn.edu>
Description: Given a postulated model and a set of data, the comparison density is estimated and the deviance test is implemented in order to assess if the data distribution deviates significantly from the postulated model. Finally, the results are summarized in a CD-plot as described in Algeri S. (2019) <arXiv:1906.06615>.
Depends: R (>= 2.0.1), polynom
Imports: orthopolynom,Hmisc,grDevices,graphics,stats
Encoding: UTF-8
License: GPL-3
LazyData: true
NeedsCompilation: no
Packaged: 2019-09-20 14:52:15 UTC; salgeri
Repository: CRAN
Date/Publication: 2019-09-27 10:50:08 UTC

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New package immuneSIM with initial version 0.8.7
Package: immuneSIM
Type: Package
Title: Tunable Simulation of B- And T-Cell Receptor Repertoires
Version: 0.8.7
Authors@R: c( person("Cédric R.", "Weber", email = "cedric.weber@bsse.ethz.ch",role = c("aut", "cre")), person("Victor", "Greiff", email = "victor.greiff@medisin.uio.no",role = "aut"))
Author: Cédric R. Weber [aut, cre], Victor Greiff [aut]
Maintainer: Cédric R. Weber <cedric.weber@bsse.ethz.ch>
Description: Simulate full B-cell and T-cell receptor repertoires using an in silico recombination process that includes a wide variety of tunable parameters to introduce noise and biases. Additional post-simulation modification functions allow the user to implant motifs or codon biases as well as remodeling sequence similarity architecture. The output repertoires contain records of all relevant repertoire dimensions and can be analyzed using provided repertoire analysis functions. Preprint is available at bioRxiv (Weber et al., 2019 <doi:10.1101/759795>).
Depends: R (>= 3.4.0)
Imports: poweRlaw, stringdist, Biostrings, igraph, stringr, data.table, plyr, reshape2, ggplot2, grid, ggthemes, RColorBrewer, Metrics, repmis
License: GPL-3
URL: https://immuneSIM.readthedocs.io
BugReports: https://github.com/GreiffLab/immuneSIM/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-20 08:43:33 UTC; ceweber
Repository: CRAN
Date/Publication: 2019-09-27 10:30:06 UTC

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New package hans with initial version 0.1
Package: hans
Type: Package
Title: Haversines are not Slow
Version: 0.1
Date: 2019-08-29
Authors@R: person("Alex", "Hallam", email = "alexhallam6.28@tutanota.com", role = c("aut", "cre"))
Encoding: UTF-8
Description: The haversine is a function used to calculate the distance between a pair of latitude and longitude points while accounting for the assumption that the points are on a spherical globe. This package provides a fast, dataframe compatible, haversine function. For the first publication on the haversine calculation see Joseph de Mendoza y Ríos (1795) <https://books.google.cat/books?id=030t0OqlX2AC> (In Spanish).
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.1)
LinkingTo: Rcpp
Suggests: testthat (>= 2.1.0)
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-09-03 13:20:37 UTC; ahallam
Author: Alex Hallam [aut, cre]
Maintainer: Alex Hallam <alexhallam6.28@tutanota.com>
Repository: CRAN
Date/Publication: 2019-09-27 10:20:06 UTC

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New package glmpca with initial version 0.1.0
Package: glmpca
Title: Dimension Reduction of Non-Normally Distributed Data
Version: 0.1.0
Description: Implements a generalized version of principal components analysis (GLM-PCA) for dimension reduction of non-normally distributed data such as counts or binary matrices. Townes FW, Hicks SC, Aryee MJ, Irizarry RA (2019) <doi:10.1101/574574>. Townes FW (2019) <arXiv:1907.02647>.
Authors@R: c(person("F. William", "Townes", email = "will.townes@gmail.com", role = c("aut", "cre", "cph")), person("Kelly", "Street", email = "street.kelly@gmail.com", role="aut"), person("Jake", "Yeung", email = "jakeyeung@gmail.com", role="ctb"))
License: Artistic-2.0
Depends: R (>= 3.6), stats
Imports:
Suggests: knitr, MASS, testthat, covr, ggplot2
URL: https://github.com/willtownes/glmpca
BugReports: https://github.com/willtownes/glmpca/issues
VignetteBuilder: knitr
LazyData: false
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-09-13 22:06:37 UTC; townesf
Author: F. William Townes [aut, cre, cph], Kelly Street [aut], Jake Yeung [ctb]
Maintainer: F. William Townes <will.townes@gmail.com>
Repository: CRAN
Date/Publication: 2019-09-27 10:50:05 UTC

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New package CamelUp with initial version 0.1.0
Package: CamelUp
Title: CamelUp Board Game as a Teaching Aid for Introductory Statistics
Version: 0.1.0
Authors@R: c(person("Michael", "Czekanski", email = "middleburystatspackages@gmail.com", role = c("aut", "cre")), person("Alex", "Lyford", role = "aut"), person("Tom", "Rahr", role = "aut"), person("Tina", "Chen", role = "aut"))
Description: Implements the board game CamelUp for use in introductory statistics classes using a Shiny app.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: data.table, ggthemes, parallel, R6, shiny, shinyalert, tidyverse
NeedsCompilation: no
Packaged: 2019-09-19 17:32:44 UTC; michael
Author: Michael Czekanski [aut, cre], Alex Lyford [aut], Tom Rahr [aut], Tina Chen [aut]
Maintainer: Michael Czekanski <middleburystatspackages@gmail.com>
Repository: CRAN
Date/Publication: 2019-09-27 10:10:02 UTC

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New package lmds with initial version 0.1.0
Package: lmds
Type: Package
Title: Landmark Multi-Dimensional Scaling
Version: 0.1.0
Authors@R: c( person( "Robrecht", "Cannoodt", email = "rcannood@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3641-729X", github = "rcannood") ), person( "Wouter", "Saelens", email = "wouter.saelens@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0002-7114-6248", github = "zouter") ) )
Description: A fast dimensionality reduction method scaleable to large numbers of samples. Landmark Multi-Dimensional Scaling (LMDS) is an extension of classical Torgerson MDS, but rather than calculating a complete distance matrix between all pairs of samples, only the distances between a set of landmarks and the samples are calculated.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: assertthat, dynutils (>= 1.0.3), irlba, Matrix
Suggests: testthat
RoxygenNote: 6.1.1
URL: http://github.com/dynverse/lmds
BugReports: https://github.com/dynverse/lmds/issues
Collate: 'cmdscale_landmarks.R' 'select_landmarks.R' 'lmds.R' 'package.R'
NeedsCompilation: no
Packaged: 2019-09-19 12:12:04 UTC; rcannood
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [aut] (<https://orcid.org/0000-0002-7114-6248>, zouter)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>
Repository: CRAN
Date/Publication: 2019-09-27 09:10:02 UTC

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New package imagefluency with initial version 0.2.1
Package: imagefluency
Type: Package
Title: Image Statistics Based on Processing Fluency
Version: 0.2.1
Date: 2019-09-19
Authors@R: person(given = "Stefan", family = "Mayer", email = "stefan@mayer-de.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0034-7090"))
Description: Get image statistics based on processing fluency theory. The functions provide scores for several basic aesthetic principles that facilitate fluent cognitive processing of images: contrast, complexity / simplicity, self-similarity, symmetry, and typicality. See Mayer & Landwehr (2018) <doi:10.1037/aca0000187> and Mayer & Landwehr (2018) <doi:10.31219/osf.io/gtbhw> for the theoretical background of the methods.
License: GPL-3
Encoding: UTF-8
URL: https://stm.github.io/imagefluency
BugReports: https://github.com/stm/imagefluency/issues
Depends: R (>= 3.2.3)
Imports: R.utils, readbitmap, pracma, quadprog, magick, OpenImageR
Suggests: grid, ggplot2, scales, shiny, testthat, knitr, rmarkdown
RoxygenNote: 6.1.1
Collate: 'utils.R' 'complexity.R' 'contrast.R' 'imagefluency-package.R' 'imagefluencyApp.R' 'self-similarity.R' 'simplicity.R' 'symmetry.R' 'typicality.R'
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-09-19 13:50:22 UTC; stemayer
Author: Stefan Mayer [aut, cre] (<https://orcid.org/0000-0003-0034-7090>)
Maintainer: Stefan Mayer <stefan@mayer-de.com>
Repository: CRAN
Date/Publication: 2019-09-27 09:50:02 UTC

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