Thu, 22 Aug 2019

New package rscielo with initial version 1.0.0
Package: rscielo
Type: Package
Title: A Scraper for Scientific Journals Hosted on Scielo
Version: 1.0.0
Authors@R: c( person("Fernando", "Meireles", , "fernando.meireles@iesp.uerj.br", c("aut", "cre"), c(ORCID = "0000-0002-7027-2058")), person("Denisson", "Silva", , "silvadenisson@ufmg.br", c("aut"), c(ORCID = "0000-0003-2771-8146")), person("Rogerio", "Barbosa", , "antrologos@gmail.com", c("aut"), c(ORCID = "0000-0002-7027-2058")) )
Description: Scrapes data from scientific articles hosted on the Scientific Electronic Library Online Platform <http://www.scielo.br/>. The data information includes author's names, articles' metadata and contents, among others. The package also provides additional functions to easily summarize the scraped data.
License: GPL-3
Depends: R (>= 3.1)
Imports: graphics, magrittr, stats, xml2, httr (>= 0.5), rvest, stringr, tibble, purrr, dplyr
LazyData: TRUE
URL: https://github.com/meirelesff/rscielo
BugReports: https://github.com/meirelesff/rscielo/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-21 15:44:21 UTC; meire
Author: Fernando Meireles [aut, cre] (<https://orcid.org/0000-0002-7027-2058>), Denisson Silva [aut] (<https://orcid.org/0000-0003-2771-8146>), Rogerio Barbosa [aut] (<https://orcid.org/0000-0002-7027-2058>)
Maintainer: Fernando Meireles <fernando.meireles@iesp.uerj.br>
Repository: CRAN
Date/Publication: 2019-08-22 12:10:02 UTC

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New package gretel with initial version 0.0.1
Package: gretel
Title: Generalized Path Analysis for Social Networks
Version: 0.0.1
Date: 2019-08-09
Authors@R: person("David", "Buch", email = "davidbuch42@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4574-0075"))
Description: The social network literature features numerous methods for assigning value to paths as a function of their ties. 'gretel' systemizes these approaches, casting them as instances of a generalized path value function indexed by a penalty parameter. The package also calculates probabilistic path value and identifies optimal paths in either value framework. Finally, proximity matrices can be generated in these frameworks that capture high-order connections overlooked in primitive adjacency sociomatrices. Novel methods are described in Buch (2019) <https://davidbuch.github.io/analyzing-networks-with-gretel.html>. More traditional methods are also implemented, as described in Yang, Knoke (2001) <doi:10.1016/S0378-8733(01)00043-0>.
Maintainer: David Buch <davidbuch42@gmail.com>
URL: https://github.com/davidbuch/gretel
BugReports: https://github.com/davidbuch/gretel/issues
License: GPL-3
Depends: R (>= 3.0)
Imports: Rcpp (>= 1.0.0), ResistorArray (>= 1.0-32)
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-08-21 11:38:45 UTC; Buch
Author: David Buch [aut, cre] (<https://orcid.org/0000-0002-4574-0075>)
Repository: CRAN
Date/Publication: 2019-08-22 12:00:02 UTC

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New package simGWAS with initial version 0.2.0-2
Package: simGWAS
Type: Package
Title: Fast Simulation of Large Case-Control GWAS Summary Statistics
Version: 0.2.0-2
Date: 2019-08-19
Authors@R: c(person("Mary", "Fortune", role=c("aut"), email = "mdf34@cam.ac.uk"), person("Chris","Wallace", role=c("aut","cre"), email="cew54@cam.ac.uk"), person("Marcus", "Klarqvist", role=c("ctb")))
Author: Mary Fortune [aut], Chris Wallace [aut, cre], Marcus Klarqvist [ctb]
Maintainer: Chris Wallace <cew54@cam.ac.uk>
Description: Simulating output from a case-control genome wide association study (GWAS) with a given causal model. Fortune and Wallace (2019) <doi:10.1093/bioinformatics/bty898>.
License: GPL
LazyLoad: yes
OS_type: unix
Collate: 'simGWAS.R' 'compute_gamma0.R' 'vbeta.R' 'zscore.R' 'extractsnps.R' 'make_dataset.R' 'make_GenoProbList.R' 'RcppExports.R'
LinkingTo: Rcpp
Imports: Rcpp, dplyr, combinat, corpcor, mvtnorm
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
URL: https://github.com/chr1swallace/simGWAS
BugReports: https://github.com/chr1swallace/simGWAS/issues
NeedsCompilation: yes
Packaged: 2019-08-20 21:01:25 UTC; chris
Repository: CRAN
Date/Publication: 2019-08-22 08:20:02 UTC

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New package cursory with initial version 1.0.0
Package: cursory
Type: Package
Title: A Cursory Look at Variables
Version: 1.0.0
Authors@R: person("Andrew", "Redd", role = c("aut", "cre") , email = "Andrew.Redd@hsc.utah.edu" , comment = c(ORCID = "https://orcid.org/000-0002-6149-2438") )
Maintainer: Andrew Redd <Andrew.Redd@hsc.utah.edu>
Description: Provides functions for quickly looking at summary statistics for variables in a data set.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Language: en-US
RoxygenNote: 6.1.1
Imports: dplyr, methods, pkgcond, purrr, rlang, tibble, tidymargins, tidyr, tidyselect
Suggests: covr, forcats, datasets, dbplyr, testthat, testextra, DBI, RSQLite
URL: https://github.com/halpo/cursory
BugReports: https://github.com/halpo/cursory/issues
NeedsCompilation: no
Packaged: 2019-08-20 21:26:04 UTC; u0092104
Author: Andrew Redd [aut, cre] (<https://orcid.org/000-0002-6149-2438>)
Repository: CRAN
Date/Publication: 2019-08-22 08:40:02 UTC

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New package Rirt with initial version 0.0.1
Package: Rirt
Type: Package
Title: Item Response Theory Models
Version: 0.0.1
Date: 2019-08-05
Authors@R: c(person("Xiao", "Luo", role=c("aut","cre"), email="xluo1986@gmail.com"))
Author: Xiao Luo [aut, cre]
Maintainer: Xiao Luo <xluo1986@gmail.com>
Description: Parameter estimation, computation of probability, information, and (log-)likelihood, and visualization of item/test characteristic curves and item/test information functions for three uni-dimensional item response theory models: the 3-parameter-logistic model, generalized partial credit model, and graded response model. The full documentation and tutorials are at <https://github.com/xluo11/Rirt>.
License: GPL (>= 3)
Depends: R (>= 3.6.0)
URL: https://github.com/xluo11/Rirt
BugReports: https://github.com/xluo11/Rirt/issues
LinkingTo: Rcpp
Imports: ggplot2, Rcpp, reshape2, stats
Suggests: testthat
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-08-20 18:14:03 UTC; Luo.Xiao
Repository: CRAN
Date/Publication: 2019-08-22 07:50:05 UTC

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New package QuantileNPCI with initial version 0.2.95
Package: QuantileNPCI
Type: Package
Title: Nonparametric Confidence Intervals for Quantiles
Version: 0.2.95
Authors@R: c( person("Nicholas", "Hutson", role = "aut"), person("Li", "Yan", role=c("aut", "cre"), email = "li.yan@roswellpark.org") )
Maintainer: Li Yan <li.yan@roswellpark.org>
Description: Based on Alan D. Hutson (1999) <doi:10.1080/02664769922458>, "Calculating nonparametric confidence intervals for quantiles using fractional order statistics", Journal of Applied Statistics, 26:3, 343-353.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports:
Suggests: dplyr, kableExtra, knitr, rmarkdown, testthat (>= 2.1.0)
Depends: R (>= 2.10)
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-20 19:30:03 UTC; liyan
Author: Nicholas Hutson [aut], Li Yan [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-22 07:20:02 UTC

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New package mRpostman with initial version 0.2.0
Package: mRpostman
Type: Package
Title: IMAP Tools in a Tidy Way
Version: 0.2.0
Date: 2019-08-18
Authors@R: c( person(given="Allan", family="Quadros", email = "allanvcq@gmail.com", role = c("aut", "cre")))
Description: Multiple IMAP (Internet Message Access Protocol) commands based on the RFC 3501 manual (Crispin, 2003, <doi:10.17487/RFC3501>), its updates, and other related documents. Besides other features, 'mRpostman' provides functions for listing, selecting and renaming mailboxes, as well as moving, fetching, and searching for messages using several criteria.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: curl, stringr, magrittr, assertthat, base64enc
Depends: R (>= 3.1.0)
BugReports: https://github.com/allanvc/mRpostman/issues
SystemRequirements: libcurl: libcurl-devel (rpm) or libcurl4-openssl-dev (deb)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-20 19:12:26 UTC; allan
Author: Allan Quadros [aut, cre]
Maintainer: Allan Quadros <allanvcq@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-22 07:30:02 UTC

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New package DoE.multi.response with initial version 0.1.0
Package: DoE.multi.response
Title: Construct Multi-Response Experimental Designs
Version: 0.1.0
Authors@R: person("Wilmina", "Marget", email = "margetw@augsburg.edu", role = c("aut", "cre"))
Description: Construct multi-response experimental designs, such as a Unique Factor Central Composite Design (UF-CCD), given information (from screening or expert knowledge) about which factors are related to each response variable (Wilmina M. Marget & Max D. Morris, 2019 <doi:10.1080/00401706.2018.1549102>).
Depends: R (>= 3.6), DoE.wrapper (>= 0.10)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-08-21 15:01:29 UTC; margetw
Author: Wilmina Marget [aut, cre]
Maintainer: Wilmina Marget <margetw@augsburg.edu>
Repository: CRAN
Date/Publication: 2019-08-22 07:10:02 UTC

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New package bigutilsr with initial version 0.1.1
Package: bigutilsr
Title: Utility Functions for Large-scale Data
Version: 0.1.1
Date: 2019-08-20
Authors@R: person("Florian", "Privé", email = "florian.prive.21@gmail.com", role = c("aut", "cre"))
Description: Utility functions for large-scale data. For now, package 'bigutilsr' mainly includes functions for outlier detection.
License: GPL-3
Encoding: UTF-8
Language: en-US
LazyData: TRUE
ByteCompile: TRUE
RoxygenNote: 6.1.0
URL: https://github.com/privefl/bigutilsr
BugReports: https://github.com/privefl/bigutilsr/issues
LinkingTo: Rcpp
Imports: hdpca, nabor, Rcpp, robustbase, robust, stats
Suggests: covr, spelling, testthat
NeedsCompilation: yes
Packaged: 2019-08-20 20:32:14 UTC; privef
Author: Florian Privé [aut, cre]
Maintainer: Florian Privé <florian.prive.21@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-22 07:50:02 UTC

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Wed, 21 Aug 2019

New package xgxr with initial version 1.0.2
Package: xgxr
Title: Exploratory Graphics for Pharmacometrics
Version: 1.0.2
Authors@R: c(person(given = "Andrew", family = "Stein", role = c("aut", "cre"), email = "andy.stein@gmail.com"), person(given = "Alison", family = "Margolskee", role = "aut", email = "alison.margolskee@gmail.com"), person(given = "Fariba", family = "Khanshan", role = "aut", email = "faribashan@gmail.com"), person(given = "Konstantin", family = "Krismer", role = "aut", email = "krismer@mit.edu", comment = c(ORCID = "0000-0001-8994-3416")), person(given = "Matthew", family = "Fidler", role = "ctb", email = "matthew.fidler@gmail.com", comment = c(ORCID = "0000-0001-8538-6691")), person("Novartis Pharma AG", role = c("cph","fnd")))
Description: Supports a structured approach for exploring PKPD data <https://opensource.nibr.com/xgx>. It also contains helper functions for enabling the modeler to follow best R practices (by appending the program name, figure name location, and draft status to each plot). In addition, it enables the modeler to follow best graphical practices (by providing a theme that reduces chart ink, and by providing time-scale, log-scale, and reverse-log-transform-scale functions for more readable axes). Finally, it provides some data checking and summarizing functions for rapidly exploring pharmacokinetics and pharmacodynamics (PKPD) datasets.
License: MIT + file LICENSE
URL: https://opensource.nibr.com/xgx
Depends: R (>= 3.4.0)
Imports: assertthat, binom, dplyr, ggplot2, graphics, grDevices, labeling, magrittr, pander, png, scales, stats, tibble, utils
Suggests: caTools, gridExtra, knitr, rmarkdown, RxODE, stringr, testthat, tidyr
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-21 18:13:04 UTC; steinanf
Author: Andrew Stein [aut, cre], Alison Margolskee [aut], Fariba Khanshan [aut], Konstantin Krismer [aut] (<https://orcid.org/0000-0001-8994-3416>), Matthew Fidler [ctb] (<https://orcid.org/0000-0001-8538-6691>), Novartis Pharma AG [cph, fnd]
Maintainer: Andrew Stein <andy.stein@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-21 21:50:02 UTC

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New package SWMPrExtension with initial version 1.1.1
Package: SWMPrExtension
Type: Package
Title: Functions for Analyzing and Plotting Estuary Monitoring Data
Version: 1.1.1
Maintainer: Dave Eslinger <dave.eslinger@noaa.gov>
Description: Tools for performing routine analysis and plotting tasks with environmental data from the System Wide Monitoring Program of the National Estuarine Research Reserve System <http://cdmo.baruch.sc.edu/>. This package builds on the functionality of the SWMPr package <https://cran.r-project.org/web/packages/SWMPr/index.html>, which is used to retrieve and organize the data. The combined set of tools address common challenges associated with continuous time series data for environmental decision making, and are intended for use in annual reporting activities. References: Beck, Marcus W. (2016) <ISSN 2073-4859><https://journal.r-project.org/archive/2016-1/beck.pdf> Rudis, Bob (2014) <https://rud.is/b/2014/11/16/moving-the-earth-well-alaska-hawaii-with-r/>. United States Environmental Protection Agency (2015) <https://cfpub.epa.gov/si/si_public_record_Report.cfm?dirEntryId=327030>. United States Environmental Protection Agency (2012) <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.646.1973&rep=rep1&type=pdf>.
BugReports: https://github.com/NOAA-OCM/SWMPrExtension/issues
License: CC0
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2.0), SWMPr
Imports: broom, dplyr, EnvStats, flextable, ggplot2, ggthemes, grDevices, leaflet, lubridate, magrittr, maptools, methods, officer, tidyr, scales, RColorBrewer, rgdal, rgeos, rlang, sp
Authors@R: c( person(given = "Julie", family = "Padilla", role = c("aut", "ctb"), email = "jpadilla@limno.com"), person(given = "Marcus", family = "Beck", role = c("ctb"), email = "marcus@sccwrp.org"), person(given = "Kimberly", family = "Cressman", role = c("ctb"), email = "kimberly.cressman@dmr.ms.gov"), person(given = "Dave", family = "Eslinger", role = c("cre", "ctb"), email = "dave.eslinger@noaa.gov"), person(given = "Bob", family = "Rudis", role = c("ctb"), email = "bob@rud.is") )
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-19 15:37:44 UTC; Dave.Eslinger
Author: Julie Padilla [aut, ctb], Marcus Beck [ctb], Kimberly Cressman [ctb], Dave Eslinger [cre, ctb], Bob Rudis [ctb]
Repository: CRAN
Date/Publication: 2019-08-21 21:50:09 UTC

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New package KernSmoothIRT with initial version 6.2
Package: KernSmoothIRT
Type: Package
Title: Nonparametric Item Response Theory
Version: 6.2
Date: 2019-08-08
Author: Angelo Mazza, Antonio Punzo, Brian McGuire
Maintainer: Brian McGuire <mcguirebc@gmail.com>
Description: Fits nonparametric item and option characteristic curves using kernel smoothing. It allows for optimal selection of the smoothing bandwidth using cross-validation and a variety of exploratory plotting tools. The kernel smoothing is based on methods described in Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.
License: GPL-2
LazyLoad: yes
Imports: Rcpp, plotrix, rgl
LinkingTo: Rcpp
Packaged: 2019-08-21 17:18:47 UTC; BrianMcGuire
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2019-08-21 21:50:13 UTC

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New package geohashTools with initial version 0.2.2
Package: geohashTools
Version: 0.2.2
Title: Tools for Working with Geohashes
Author: Michael Chirico, Hiroaki Kawai
Maintainer: Michael Chirico <MichaelChirico4@gmail.com>
Depends: R (>= 3.0.0)
Description: Tools for working with Gustavo Niemeyer's geohash coordinate system, ported to R from Hiroaki Kawai's 'Python' implementation and embellished to sit naturally in the R ecosystem.
URL: https://github.com/MichaelChirico/geohashTools
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.0)
Suggests: rgdal, sf, sp, testthat, mockery
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2019-08-21 12:18:15 UTC; michael.chirico
Repository: CRAN
Date/Publication: 2019-08-21 14:20:04 UTC

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New package SECFISH with initial version 0.1.5
Package: SECFISH
Type: Package
Title: Disaggregate Variable Costs
Version: 0.1.5
Author: Isabella Bitetto (COISPA), Loretta Malvarosa (NISEA), Maria Teresa Spedicato (COISPA), Ralf Doering (THUENEN), Joerg Berkenhagen (THUENEN)
Maintainer: Isabella Bitetto <bitetto@coispa.it>
Description: These functions were developed within SECFISH project (Strengthening regional cooperation in the area of fisheries data collection-Socio-economic data collection for fisheries, aquaculture and the processing industry at EU level). They are aimed at identifying correlations between costs and transversal variables by metier using individual vessel data and for disaggregating variable costs from fleet segment to metier level.
License: GPL-2
Depends: R (>= 3.5)
Imports: ggplot2, Hmisc, optimization
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-08-21 08:42:10 UTC; Bitetto Isabella
Repository: CRAN
Date/Publication: 2019-08-21 11:20:09 UTC

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New package vici with initial version 0.5.2
Package: vici
Title: Vaccine Induced Cellular Immunogenicity with Bivariate Modeling
Version: 0.5.2
Date: 2019-08-20
Authors@R: person('Boris', 'Hejblum', email = 'boris.hejblum@u-bordeaux.fr', role = c('cre', 'aut'))
Description: A shiny app for accurate estimation of vaccine induced immunogenicity with bivariate linear modeling. Method is detailed in: Lhomme E, Hejblum BP, Lacabaratz C, Wiedemann A, Lelièvre J-D, Levy Y, Thiebaut R & Richert L (2019). Submitted.
BugReports: https://github.com/borishejblum/vici/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: cowplot, DT, ggplot2, grDevices, ggpubr, nlme, shiny, stats, tidyr, utils
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-20 14:04:39 UTC; borishejblum
Author: Boris Hejblum [cre, aut]
Maintainer: Boris Hejblum <boris.hejblum@u-bordeaux.fr>
Repository: CRAN
Date/Publication: 2019-08-21 09:20:02 UTC

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New package samc with initial version 1.0.3
Package: samc
Type: Package
Title: Spatial Absorbing Markov Chains
Version: 1.0.3
Date: 2019-08-20
Authors@R: c( person("Andrew", "Marx", , "andrewjmarx@ufl.edu", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-7456-1631") ), person("Robert", "Fletcher", , , role = c("ctb"), comment = c(ORCID = "0000-0003-1717-5707") ), person("Miguel", "Acevedo", , , role = c("ctb"), comment = c(ORCID = "0000-0002-8289-1497") ), person("Jorge", "Sefair", , , role = c("ctb"), comment = c() ), person("Chao", "Wang", , , role = c("ctb"), comment = c() ) )
Description: An implementation of the framework described in "Toward a unified framework for connectivity that disentangles movement and mortality in space and time" by Fletcher et al. (2019) <doi:10.1111/ele.13333>. Incorporates both resistance and absorption with spatial absorbing Markov chains (SAMC) to provide several short-term and long-term predictions for metrics related to connectivity in landscapes.
License: GPL (>= 3)
URL: https://andrewmarx.github.io/samc
BugReports: https://github.com/andrewmarx/samc/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3.0)
Imports: methods, gdistance, Matrix, raster
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat, ggplot2, png, viridis, gifski, gganimate
VignetteBuilder: knitr
Collate: 'RcppExports.R' 'samc-class.R' 'check.R' 'data.R' 'visitation.R' 'dispersal.R' 'distribution.R' 'map.R' 'mortality.R' 'samc.R' 'survival.R'
LinkingTo: Rcpp (>= 1.0.1), RcppEigen (>= 0.3.3.5.0)
NeedsCompilation: yes
Packaged: 2019-08-20 14:42:48 UTC; andrewjmarx
Author: Andrew Marx [aut, cre, cph] (<https://orcid.org/0000-0002-7456-1631>), Robert Fletcher [ctb] (<https://orcid.org/0000-0003-1717-5707>), Miguel Acevedo [ctb] (<https://orcid.org/0000-0002-8289-1497>), Jorge Sefair [ctb], Chao Wang [ctb]
Maintainer: Andrew Marx <andrewjmarx@ufl.edu>
Repository: CRAN
Date/Publication: 2019-08-21 09:40:02 UTC

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New package ipfr with initial version 1.0.0
Package: ipfr
Title: List Balancing for Reweighting and Population Synthesis
Version: 1.0.0
Authors@R: c( person( "Kyle", "Ward", email = "kyleward084@gmail.com", role = c("aut", "cre", "cph") ), person("Greg", "Macfarlane", email = "gregmacfarlane@byu.edu", role = c("ctb")))
Description: Performs iterative proportional updating given a seed table and an arbitrary number of marginal distributions. This is commonly used in population synthesis, survey raking, matrix rebalancing, and other applications. For example, a household survey may be weighted to match the known distribution of households by size from the census. An origin/ destination trip matrix might be balanced to match traffic counts. The approach used by this package is based on a paper from Arizona State University (Ye, Xin, et. al. (2009) <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.537.723&rep=rep1&type=pdf>). Some enhancements have been made to their work including primary and secondary target balance/importance, general marginal agreement, and weight restriction.
License: Apache License (== 2.0)
URL: https://github.com/dkyleward/ipfr
BugReports: https://github.com/dkyleward/ipfr/issues
Depends: R (>= 3.2.0)
Imports: dplyr (>= 0.7.3), ggplot2 (>= 2.2.1), magrittr (>= 1.5), tidyr (>= 0.5.1), mlr (>= 2.11)
LazyData: true
Suggests: knitr, rmarkdown, testthat (>= 2.1.0), covr
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-20 14:15:20 UTC; kyle
Author: Kyle Ward [aut, cre, cph], Greg Macfarlane [ctb]
Maintainer: Kyle Ward <kyleward084@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-21 09:30:03 UTC

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New package genodds with initial version 1.0.0
Package: genodds
Type: Package
Title: Generalized Odds Ratios
Version: 1.0.0
Date: 2019-08-14
Encoding: UTF-8
Authors@R: person("Hannah","Johns", role=c("aut","cre"),email="htjohns@gmail.com",comment=c(ORCID="0000-0003-2135-0504"))
Maintainer: Hannah Johns <htjohns@gmail.com>
Description: Calculates Agresti's (1980) <https://www.jstor.org/stable/2530495> generalized odds ratios. For a randomly selected pair of observations from two groups, calculates the odds that the second group will have a higher scoring outcome than that of the first group. Package provides hypothesis testing for if this odds ratio is significantly different to 1 (equal chance).
License: GPL (>= 2)
LazyData: TRUE
Depends: R (>= 2.10)
Imports: Rcpp (>= 0.12.3)
LinkingTo: Rcpp
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0)
NeedsCompilation: yes
Packaged: 2019-08-20 14:30:17 UTC; hannah
Author: Hannah Johns [aut, cre] (<https://orcid.org/0000-0003-2135-0504>)
Repository: CRAN
Date/Publication: 2019-08-21 09:30:06 UTC

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New package Biopeak with initial version 1.0
Package: Biopeak
Type: Package
Title: Identification of Impulse-Like Gene Expression Changes in Short Genomic Series Data
Version: 1.0
Author: David Lauenstein
Maintainer: David Lauenstein <david.lauenstein@gmail.com>
Description: Enables the user to systematically identify and visualize impulse-like gene expression changes within short genomic series experiments. In order to detect such activation peaks, the gene expression is treated as a signal that propagates along an experimental axis (time, temperature or other series conditions). Peaks are selected by exhaustive identification of local maximums and subsequent filtering based on a range of controllable parameters. Moreover, the 'Biopeak' package provides a series of data exploration tools including: expression profile plots, correlation heat maps and clustering functionalities.
License: GPL (>= 2)
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Imports: cluster, dbscan, factoextra, gplots, RColorBrewer, stats, graphics
LazyData: True
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-08-09 09:40:11 UTC; David
Repository: CRAN
Date/Publication: 2019-08-21 09:40:06 UTC

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New package viromeBrowser with initial version 1.0.0
Package: viromeBrowser
Type: Package
Title: Virome Sequencing Analysis Result Browser
Version: 1.0.0
Authors@R: person("David", "Nieuwenhuijse", email = "d.nieuwenhuijse@erasmusmc.nl", role = c("aut", "cre"))
Description: Experiments in which highly complex virome sequencing data is generated are difficult to visualize and unpack for a person without programming experience. After processing of the raw sequencing data by a next generation sequencing (NGS) processing pipeline the usual output consists of contiguous sequences (contigs) in fasta format and an annotation file linking the contigs to a reference sequence. The virome analysis browser app imports an annotation file and a corresponding fasta file containing the annotated contigs. It facilitates browsing of annotations in multiple files and allows users to select and export specific annotated sequences from the associated fasta files. Various annotation quality thresholds can be set to filter contigs from the annotation files. Further inspection of selected contigs can be done in the form of automatic open reading frame (ORF) detection. Separate contigs and/or separate ORFs can be downloaded in nucleotide or amino acid format for further analysis.
Depends: R (>= 3.4)
Imports: shiny (>= 1.3.2), shinyWidgets, plyr, ggplot2, shinydashboard, DT, reshape, rbokeh, Biostrings, Rsamtools, data.table, markdown, stringr, shinycssloaders
License: AGPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-20 12:02:54 UTC; david
Author: David Nieuwenhuijse [aut, cre]
Maintainer: David Nieuwenhuijse <d.nieuwenhuijse@erasmusmc.nl>
Repository: CRAN
Date/Publication: 2019-08-21 08:10:02 UTC

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New package scorepeak with initial version 0.1.2
Package: scorepeak
Type: Package
Title: Peak Functions for Peak Detection in Univariate Time Series
Version: 0.1.2
Authors@R: c( person("Shota", "Ochi", email = "shotaochi1990@gmail.com", role = c("aut", "cre", "cph")))
Maintainer: Shota Ochi <shotaochi1990@gmail.com>
Description: Provides peak functions, which enable us to detect peaks in time series. The methods implemented in this package are based on Girish Keshav Palshikar (2009) <https://www.researchgate.net/publication/228853276_Simple_Algorithms_for_Peak_Detection_in_Time-Series>.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: checkmate (>= 1.9.1), Rcpp (>= 1.0.0)
Suggests: knitr, rmarkdown, testthat (>= 2.0.0), cluster
URL: https://github.com/ShotaOchi/scorepeak
BugReports: https://github.com/ShotaOchi/scorepeak/issues
NeedsCompilation: yes
LinkingTo: Rcpp
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Encoding: UTF-8
Packaged: 2019-08-20 12:16:24 UTC; shota
Author: Shota Ochi [aut, cre, cph]
Repository: CRAN
Date/Publication: 2019-08-21 08:20:02 UTC

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New package partitionBEFsp with initial version 1.0
Package: partitionBEFsp
Title: Methods for Calculating the Loreau & Hector 2001 BEF Partition
Version: 1.0
Author: Adam Clark
Maintainer: Adam Clark <adam.tclark@gmail.com>
Description: A collection of functions that can be used to estimate selection and complementarity effects, sensu Loreau & Hector (2001) <doi:10.1038/35083573>, even in cases where data are only available for a random subset of species (i.e. incomplete sample-level data). A full derivation and explanation of the statistical corrections used here is available in Clark et al. (2019) <doi:10.1111/2041-210X.13285>.
Depends: R (>= 3.4)
Imports: graphics, stats
License: GPL-3
LazyData: true
NeedsCompilation: no
Packaged: 2019-08-20 12:36:15 UTC; atclark
Repository: CRAN
Date/Publication: 2019-08-21 08:20:05 UTC

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New package factory with initial version 0.1.0
Package: factory
Type: Package
Title: Build Function Factories
Version: 0.1.0
Authors@R: c(person(given = "Jon", family = "Harmon", role = c("aut", "cre"), email = "jonthegeek@gmail.com") )
Description: Function factories are functions that make functions. They can be confusing to construct. Straightforward techniques can produce functions that are fragile or hard to understand. While more robust techniques exist to construct function factories, those techniques can be confusing. This package is designed to make it easier to construct function factories.
URL: https://github.com/jonthegeek/factory
BugReports: https://github.com/jonthegeek/factory/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: purrr (>= 0.3.2), rlang (>= 0.4.0)
Suggests: testthat (>= 2.1.0), covr, roxygen2, knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-20 13:44:54 UTC; Jon.Harmon
Author: Jon Harmon [aut, cre]
Maintainer: Jon Harmon <jonthegeek@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-21 09:00:07 UTC

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New package DRAYL with initial version 1.0
Package: DRAYL
Version: 1.0
Title: Computation of Rayleigh Densities of Arbitrary Dimension
Author: Martin Wiegand
Maintainer: Martin Wiegand <Martin.Wiegand@manchester.ac.uk>
Depends: R (>= 3.0.1)
Description: We offer an implementation of the series representation put forth in "A series representation for multidimensional Rayleigh distributions" by Wiegand and Nadarajah <DOI: 10.1002/dac.3510>. Furthermore we have implemented an integration approach proposed by Beaulieu et al. for 3 and 4-dimensional Rayleigh densities (Beaulieu, Zhang, "New simplest exact forms for the 3D and 4D multivariate Rayleigh PDFs with applications to antenna array geometrics", <DOI: 10.1109/TCOMM.2017.2709307>).
License: GPL-2
Imports: stats,pracma,RConics,rmutil,cubature
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-08-20 12:56:17 UTC; mbbxwmw4
Repository: CRAN
Date/Publication: 2019-08-21 08:20:07 UTC

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Tue, 20 Aug 2019

New package lactcurves with initial version 1.0.0
Package: lactcurves
Type: Package
Title: Lactation Curve Parameter Estimation
Version: 1.0.0
Author: Eva M. Strucken
Maintainer: Eva M. Strucken <estrucke@une.edu.au>
Description: AllCurves() runs multiple lactation curve models and extracts selection criteria for each model. This package summarises the most common lactation curve models from the last century and provides a tool for researchers to quickly decide on which model fits their data best to proceed with their analysis. Start parameters were optimized based on a dataset with 1.7 million Holstein-Friesian cows. If convergence fails, the start parameters need to be manually adjusted. The models included in the package are taken from: (1) Michaelis-Menten: Michaelis, L. and M.L. Menten (1913). <www.plantphys.info/plant_physiology/copyright/MichaelisMentenTranslation2.pdf> (1a) Michaelis-Menten (Rook): Rook, A.J., J. France, and M.S. Dhanoa (1993). <doi:10.1017/S002185960007684X> (1b) Michaelis-Menten + exponential (Rook): Rook, A.J., J. France, and M.S. Dhanoa (1993). <doi:10.1017/S002185960007684X> (2) Brody (1923): Brody, S., A.C. Ragsdale, and C.W. Turner (1923). <doi:10.1085/jgp.5.6.777> (3) Brody (1924): Brody, S., C.W. Tuner, and A.C. Ragsdale (1924). <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2140670/> (4) Schumacher: Schumacher, F.X. (1939) in Thornley, J.H.M. and J. France (2007). <https://books.google.com.au/books/about/Mathematical_Models_in_Agriculture.html?id=rlwBCRSHobcC&redir_esc=y> (4a) Schumacher (Lopez et al. 2015): Lopez, S. J. France, N.E. Odongo, R.A. McBride, E. Kebreab, O. AlZahal, B.W. McBride, and J. Dijkstra (2015). <doi:10.3168/jds.2014-8132> (5) Parabolic exponential (Adediran): Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (6) Wood: Wood, P.D.P. (1967). <doi:10.1038/216164a0> (6a) Wood reparameterized (Dhanoa): Dhanoa, M.S. (1981). <doi:10.1017/S0003356100027276> (6b) Wood non-linear (Cappio-Borlino): Cappio-Borlino, A., G. Pulina, and G. Rossi (1995). <doi:10.1016/0921-4488(95)00713-U> (7) Quadratic Polynomial (Dave): Dave, B.K. (1971) in Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (8) Cobby and Le Du (Vargas): Vargas, B., W.J. Koops, M. Herrero, and J.A.M Van Arendonk (2000). <doi:10.3168/jds.S0022-0302(00)75005-3> (9) Papajcsik and Bodero 1: Papajcsik, I.A. and J. Bodero (1988). <doi:10.1017/S0003356100003275> (10) Papajcsik and Bodero 2: Papajcsik, I.A. and J. Bodero (1988). <doi:10.1017/S0003356100003275> (11) Papajcsik and Bodero 3: Papajcsik, I.A. and J. Bodero (1988). <doi:10.1017/S0003356100003275> (12) Papajcsik and Bodero 4: Papajcsik, I.A. and J. Bodero (1988). <doi:10.1017/S0003356100003275> (13) Papajcsik and Bodero 6: Papajcsik, I.A. and J. Bodero (1988). <doi:10.1017/S0003356100003275> (14) Mixed log model 1 (Guo and Swalve): Guo, Z. and H.H. Swalve (1995). <https://journal.interbull.org/index.php/ib/issue/view/11> (15) Mixed log model 3 (Guo and Swalve): Guo, Z. and H.H. Swalve (1995). <https://journal.interbull.org/index.php/ib/issue/view/11> (16) Log-quadratic (Adediran et al. 2012): Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (17) Wilmink: J.B.M. Wilmink (1987). <doi:10.1016/0301-6226(87)90003-0> (17a) modified Wilmink (Jakobsen): Jakobsen J.H., P. Madsen, J. Jensen, J. Pedersen, L.G. Christensen, and D.A. Sorensen (2002). <doi:10.3168/jds.S0022-0302(02)74231-8> (17b) modified Wilmink (Laurenson & Strucken): in preparation (2019). (18) Bicompartemental (Ferguson and Boston 1993): Ferguson, J.D., and R. Boston (1993) in Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (19) Dijkstra: Dijkstra, J., J. France, M.S. Dhanoa, J.A. Maas, M.D. Hanigan, A.J. Rook, and D.E. Beever (1997). <doi10.3168/jds.S0022-0302(97)76185-X> (20) Morant and Gnanasakthy (Pollott et al 2000): Pollott, G.E. and E. Gootwine (2000). <doi10.1017/S1357729800055028> (21) Morant and Gnanasakthy (Vargas et al 2000): Vargas, B., W.J. Koops, M. Herrero, and J.A.M Van Arendonk (2000). <doi:10.3168/jds.S0022-0302(00)75005-3> (22) Morant and Gnanasakthy (Adediran et al. 2012): Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (23) Khandekar (Guo and Swalve): Guo, Z. and H.H. Swalve (1995). <https://journal.interbull.org/index.php/ib/issue/view/11> (24) Ali and Schaeffer: Ali, T.E. and L.R. Schaeffer (1987). <https://www.nrcresearchpress.com/doi/pdf/10.4141/cjas87-067> (25) Fractional Polynomial (Elvira et al. 2013): Elvira, L., F. Hernandez, P. Cuesta, S. Cano, J.-V. Gonzalez-Martin, and S. Astiz (2012). <doi:10.1017/S175173111200239X> (26) Pollott multiplicative (Elvira): Elvira, L., F. Hernandez, P. Cuesta, S. Cano, J.-V. Gonzalez-Martin, and S. Astiz (2012). <doi:10.1017/S175173111200239X> (27) Pollott modified: Adediran, S.A., D.A. Ratkowsky, D.J. Donaghy, and A.E.O. Malau-Aduli (2012). <doi:10.3168/jds.2011-4663> (28) Monophasic Grossman: Grossman, M. and W.J. Koops (1988). <doi:10.3168/jds.S0022-0302(88)79723-4> (29) Monophasic Power Transformed (Grossman 1999): Grossman, M., S.M. Hartz, and W.J. Koops (1999). <doi:10.3168/jds.S0022-0302(99)75464-0> (30) Diphasic (Grossman 1999): Grossman, M., S.M. Hartz, and W.J. Koops (1999). <doi:10.3168/jds.S0022-0302(99)75464-0> (31) Diphasic Power Transformed (Grossman 1999): Grossman, M., S.M. Hartz, and W.J. Koops (1999). <doi:10.3168/jds.S0022-0302(99)75464-0> (32) Legendre Polynomial (3th order): Jakobsen J.H., P. Madsen, J. Jensen, J. Pedersen, L.G. Christensen, and D.A. Sorensen (2002). <doi:10.3168/jds.S0022-0302(02)74231-8> (33) Legendre Polynomial (4th order): Jakobsen J.H., P. Madsen, J. Jensen, J. Pedersen, L.G. Christensen, and D.A. Sorensen (2002). <doi:10.3168/jds.S0022-0302(02)74231-8> (34) Legendre + Wilmink (Lidauer): Lidauer, M. and E.A. Mantysaari (1999). <https://journal.interbull.org/index.php/ib/article/view/417> (35) Natural Cubic Spline (3 percentiles): White, I.M.S., R. Thompson, and S. Brotherstone (1999). <doi:10.3168/jds.S0022-0302(99)75277-X> (36) Natural Cubic Spline (4 percentiles): White, I.M.S., R. Thompson, and S. Brotherstone (1999). <doi:10.3168/jds.S0022-0302(99)75277-X> (37) Natural Cubic Spline (5 percentiles): White, I.M.S., R. Thompson, and S. Brotherstone (1999) <doi:10.3168/jds.S0022-0302(99)75277-X> (38) Natural Cubic Spline (defined knots according to Harrell 2001): Jr. Harrell, F.E. (2001). <https://link.springer.com/book/10.1007/978-3-319-19425-7> The selection criteria measure the goodness of fit of the model and include: Residual standard error (RSE), R-square (R2), log likelihood, Akaike information criterion (AIC), Akaike information criterion corrected (AICC), Bayesian Information Criterion (BIC), Durbin Watson coefficient (DW). The following model parameters are included: Residual sum of squares (RSS), Residual standard deviation (RSD), F-value (F) based on F-ratio test.
License: GPL-3
Depends: orthopolynom,splines
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-08-20 05:10:34 UTC; estrucke
Repository: CRAN
Date/Publication: 2019-08-20 16:30:02 UTC

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New package spread with initial version 2019.8.5
Package: spread
Title: Infectious Disease Spread Models
Version: 2019.8.5
Authors@R: c( person("Solveig", "Engebretsen", email = "solveig.engebretsen@medisin.uio.no", role = c("aut")), person("Andreas Nygård", "Osnes", email = "andreas.n.osnes@gmail.com", role = c("aut")), person("Richard", "White", email = "w@rwhite.no", role = c("aut", "cre")))
Description: A stochastic SEIIaR (susceptible, exposed, infectious, infectious asymptomatic, recovered) metapopulation model that including commuting. Each location has a local infection system, while the locations are connected by people who commute each day. The model differentiates between day and night. During the day you can infect/be infected in the location where you work, while during the night you can infect/be infected in the location where you live. It is the same commuters who travel back and forth each day. At the start of a day, all commuters are sent to their work location, where they mix for 12 hours. The commuters are then sent to their respective home locations, where they mix for 12 hours. The model is loosely based upon a published model by Engebretsen (2019) <doi:10.1371/journal.pcbi.1006879>.
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 0.9.4), RcppProgress (>= 0.1), data.table, fhidata, stringr, readxl, zoo
Suggests: testthat, knitr, ggplot2, glue, rmarkdown
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppProgress
VignetteBuilder: knitr
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2019-08-20 06:47:56 UTC; rstudio
Author: Solveig Engebretsen [aut], Andreas Nygård Osnes [aut], Richard White [aut, cre]
Maintainer: Richard White <w@rwhite.no>
Repository: CRAN
Date/Publication: 2019-08-20 15:50:02 UTC

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New package pass.lme with initial version 0.9.0
Package: pass.lme
Type: Package
Title: Power and Sample Size for Linear Mixed Effect Models
Version: 0.9.0
Depends: R (>= 3.2.5)
Author: Marco Chak Yan YU
Maintainer: Marco Chak Yan YU <marcocyyu@gmail.com>
Description: Power and sample size calculation for testing fixed effect coefficients in multilevel linear mixed effect models with one or more than one independent populations. Laird, Nan M. and Ware, James H. (1982) <doi:10.2307/2529876>.
License: GPL-3
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-20 08:34:36 UTC; marco
Repository: CRAN
Date/Publication: 2019-08-20 15:50:05 UTC

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New package implicitMeasures with initial version 0.1.0
Package: implicitMeasures
Type: Package
Title: Computes the Scores for Different Implicit Measures
Version: 0.1.0
Author: Ottavia M. Epifania [aut, cre], Pasquale Anselmi [ctb], Egidio Robusto [ctb]
Maintainer: Ottavia M. Epifania <otta.epifania@gmail.com>
Description: A tool for computing the scores for the Implicit Association Test (IAT; Greenwald, McGhee & Schwartz (1998) <doi:10.1037/0022-3514.74.6.1464>) and the Single Category-IAT (SC-IAT: Karpinski & Steinman (2006) <doi:10.1037/0022-3514.91.1.16>). Functions for preparing the data (both for the IAT and the SC-IAT), plotting the results, and obtaining a table with the scores of implicit measures descriptive statistics are provided.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: dplyr, ggplot2, methods, plyr, qpdf, tidyr, xtable
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, tableHTML, data.table
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-02 11:46:22 UTC; huawei
Repository: CRAN
Date/Publication: 2019-08-20 15:40:05 UTC

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New package electivity with initial version 1.0.2
Package: electivity
Type: Package
Title: Algorithms for Electivity Indices
Version: 1.0.2
Date: 2019-08-13
Authors@R: person("Desi", "Quintans", email = "science@desiquintans.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3356-0293"))
Description: Provides all electivity algorithms (including Vanderploeg and Scavia electivity) that were examined in Lechowicz (1982) <doi:10.1007/BF00349007>, plus the example data that were provided for moth resource utilisation.
URL: https://github.com/DesiQuintans/electivity
BugReports: https://github.com/DesiQuintans/electivity/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Suggests: utils (>= 3.4.2), usethis (>= 1.0.0)
RoxygenNote: 6.1.1
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2019-08-19 21:38:27 UTC; 90928711
Author: Desi Quintans [aut, cre] (<https://orcid.org/0000-0003-3356-0293>)
Maintainer: Desi Quintans <science@desiquintans.com>
Repository: CRAN
Date/Publication: 2019-08-20 14:50:05 UTC

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New package NetSimR with initial version 0.1.0
Package: NetSimR
Type: Package
Title: Actuarial Functions for Non-Life Insurance Modelling
Version: 0.1.0
Author: Yiannis Parizas [aut, cre]
Authors@R: person("Yiannis", "Parizas", email = "yiannis.parizas@gmail.com", role = c("aut", "cre"))
Maintainer: Yiannis Parizas <yiannis.parizas@gmail.com>
Description: Assists actuaries and other insurance modellers in pricing, reserving and capital modelling for non-life insurance and reinsurance modelling. Provides functions that help model excess levels, capping and pure Incurred but not reported claims (pure IBNR). Includes capped mean, exposure curves and increased limit factor curves (ILFs) for LogNormal, Gamma, Pareto, Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes mean, probability density function (pdf), cumulative probability function (cdf) and inverse cumulative probability function for Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes calculating pure IBNR exposure with LogNormal and Gamma distribution for reporting delay.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: knitr, crch, testthat
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-19 16:31:54 UTC; yiann
Repository: CRAN
Date/Publication: 2019-08-20 11:30:12 UTC

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New package ihpdr with initial version 1.0.0
Package: ihpdr
Title: Download Data from the International House Price Database
Version: 1.0.0
Authors@R: person(given = "Kostas", family = "Vasilopoulos", role = c("aut", "cre"), email = "k.vasilopoulo@gmail.com")
Description: Web scraping the <https://www.dallasfed.org> for up-to-date data on international house prices and exuberance indicators. Download data in tidy format.
Encoding: UTF-8
LazyData: true
Imports: rvest (>= 0.3.4), xml2 (>= 1.2.0), magrittr (>= 1.5), httr (>= 1.4.0), readxl (>= 1.3.1), dplyr (>= 0.8.3), lubridate (>= 1.7.4), purrr (>= 0.3.2), rlang (>= 0.4.0), tidyr (>= 0.8.3)
RoxygenNote: 6.1.1
URL: https://github.com/kvasilopoulos/ihpdr
BugReports: https://github.com/kvasilopoulos/ihpdr/issues
Suggests: spelling, testthat (>= 2.1.0), covr
Language: en-US
License: GPL-3
NeedsCompilation: no
Packaged: 2019-08-19 16:26:00 UTC; T460p
Author: Kostas Vasilopoulos [aut, cre]
Maintainer: Kostas Vasilopoulos <k.vasilopoulo@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-20 11:30:06 UTC

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New package tidycells with initial version 0.2.0
Type: Package
Package: tidycells
Title: Read Tabular Data from Diverse Sources and Easily Make Them Tidy
Version: 0.2.0
Authors@R: person(given = "Indranil", family = "Gayen", role = c("aut", "cre"), email = "nil.gayen@gmail.com", comment = c(ORCID = "0000-0003-0197-1944"))
Description: Provides utilities to read, cells from complex tabular data and heuristic detection based 'structural assignment' of those cells to a columnar or tidy format. Read functionality has the ability to read structured, partially structured or unstructured tabular data from various types of documents. The 'structural assignment' functionality has both supervised and unsupervised way of assigning cells data to columnar/tidy format. Multiple disconnected blocks of tables in a single sheet are also handled appropriately. These tools are suitable for unattended conversation of messy tables into a consumable format(usable for further analysis and data wrangling).
License: MIT + file LICENSE
URL: https://r-rudra.github.io/tidycells/, https://github.com/r-rudra/tidycells
BugReports: https://github.com/r-rudra/tidycells/issues
Depends: R (>= 3.2.0)
Imports: dplyr (>= 0.8.1), ggplot2, graphics, magrittr, methods, purrr (>= 0.3.2), rlang, stats, stringr (>= 1.4.0), tibble, tidyr, unpivotr (>= 0.5.1), utils
Suggests: cli, covr, docxtractr, DT, knitr, miniUI, plotly, readr, readxl, rmarkdown, rstudioapi, shiny, shinytest, stringdist, tabulizer, testthat (>= 2.1.0), tidyxl, xlsx, XML
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-19 13:36:24 UTC; igayen
Author: Indranil Gayen [aut, cre] (<https://orcid.org/0000-0003-0197-1944>)
Maintainer: Indranil Gayen <nil.gayen@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-20 10:30:02 UTC

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New package disk.frame with initial version 0.1.0
Type: Package
Package: disk.frame
Title: Larger-than-RAM Disk-Based Data Manipulation Framework
Version: 0.1.0
Date: 2019-08-03
Authors@R: person("Dai", "ZJ", email = "zhuojia.dai@gmail.com", role = c("aut", "cre"))
Maintainer: Dai ZJ <zhuojia.dai@gmail.com>
Description: A disk-based data manipulation tool for working with arbitrarily large datasets as long as they fit on disk.
License: MIT + file LICENSE
Imports: Rcpp (>= 0.12.13), glue (>= 1.3.1), rlang (>= 0.4.0), furrr (>= 0.1.0), future.apply (>= 1.3.0), fs (>= 1.3.1), jsonlite (>= 1.6), pryr (>= 0.1.4), stringr (>= 1.4.0), fst (>= 0.8.0), assertthat (>= 0.2.1), globals (>= 0.12.4), future (>= 1.14.0), data.table (>= 1.12.2), crayon (>= 1.3.4)
Depends: R (>= 3.5.0), dplyr (>= 0.8.3), purrr (>= 0.3.2)
Suggests: testthat, knitr, rmarkdown, nycflights13, magrittr, shiny
LinkingTo: Rcpp
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Encoding: UTF-8
URL: http://diskframe.com
BugReports: https://github.com/xiaodaigh/disk.frame/issues
NeedsCompilation: yes
Packaged: 2019-08-19 13:19:13 UTC; RTX2080
Author: Dai ZJ [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-20 10:10:02 UTC

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New package testequavar with initial version 0.1.2
Package: testequavar
Type: Package
Title: Bootstrap Tests for Equality of 2, 3, or 4 Population Variances
Version: 0.1.2
Author: Dexter Cahoy
Maintainer: Dexter Cahoy <cahoyd@uhd.edu>
Description: Tests the hypothesis that variances are homogeneous or not using bootstrap. The procedure uses a variance-based statistic, and is derived from a normal-theory test. The test equivalently expressed the hypothesis as a function of the log contrasts of the population variances. A box-type acceptance region is constructed to test the hypothesis. See Cahoy (2010) <doi:10.1016/j.csda.2010.04.012>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: stats
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-19 12:27:57 UTC; cahoyd
Repository: CRAN
Date/Publication: 2019-08-20 09:30:02 UTC

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New package TestDesign with initial version 0.2.2
Package: TestDesign
Type: Package
Title: Optimal Test Design Approach to Fixed and Adaptive Test Construction
Version: 0.2.2
Date: 2019-08-10
Authors@R: c( person("Seung W.", "Choi", email = "schoi@austin.utexas.edu", role = c("aut", "cre")), person("Sangdon", "Lim", email = "sangdonlim@utexas.edu", role = "aut"))
Maintainer: Seung W. Choi <schoi@austin.utexas.edu>
Description: Use the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) <doi:10.1201/9781315117430> in constructing fixed and adaptive tests. Supports the following mixed-integer programming (MIP) solver packages: 'Rsymphony', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see <https://www.gurobi.com/downloads>. See vignette for installing 'Rsymphony' package on Mac systems.
License: GPL (>= 2)
Depends: R (>= 2.10)
Imports: Rcpp (>= 1.0.0), methods, Matrix, lpSolve, foreach, logitnorm, Rdpack, crayon
Suggests: gurobi, Rsymphony, Rglpk, shiny, shinythemes, shinyWidgets, shinyjs, DT, knitr, rmarkdown, testthat (>= 2.1.0)
LinkingTo: Rcpp
RoxygenNote: 6.1.1
Encoding: UTF-8
LazyData: true
RdMacros: Rdpack
VignetteBuilder: knitr
Collate: 'import.R' 'RcppExports.R' 'item_class.R' 'item_functions.R' 'loading_functions.R' 'ATA_class.R' 'ATA_functions.R' 'solver_functions.R' 'shadow_class.R' 'shadow_functions.R' 'datasets.R' 'runshiny.R'
NeedsCompilation: yes
Packaged: 2019-08-19 00:17:52 UTC; chois1
Author: Seung W. Choi [aut, cre], Sangdon Lim [aut]
Repository: CRAN
Date/Publication: 2019-08-20 09:10:05 UTC

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New package ssr with initial version 0.1.0
Package: ssr
Type: Package
Title: Semi-Supervised Regression Methods
Version: 0.1.0
Authors@R: c(person("Enrique", "Garcia-Ceja", role = c("aut", "cre"), email = "e.g.mx@ieee.org", comment = c(ORCID = "0000-0001-6864-8557")))
Description: An implementation of semi-supervised regression methods including self-learning and co-training by committee based on Hady, M. F. A., Schwenker, F., & Palm, G. (2009) <doi:10.1007/978-3-642-04274-4_13>. Users can define which set of regressors to use as base models from the 'caret' package, other packages, or custom functions.
Depends: R (>= 3.6.0)
License: GPL-3
Encoding: UTF-8
URL: https://github.com/enriquegit/ssr
BugReports: https://github.com/enriquegit/ssr/issues
LazyData: true
Imports: caret
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, tgp
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-19 12:20:47 UTC; enriqueg
Author: Enrique Garcia-Ceja [aut, cre] (<https://orcid.org/0000-0001-6864-8557>)
Maintainer: Enrique Garcia-Ceja <e.g.mx@ieee.org>
Repository: CRAN
Date/Publication: 2019-08-20 09:30:05 UTC

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New package rSPDE with initial version 0.4.6
Package: rSPDE
Type: Package
Date: 2019-08-19
Title: Rational Approximations of Fractional Stochastic Partial Differential Equations
Version: 0.4.6
Authors@R: person("David","Bolin", email = "davidbolin@gmail.com", role = c("cre", "aut"))
Maintainer: David Bolin <davidbolin@gmail.com>
Description: Functions that compute rational approximations of fractional elliptic stochastic partial differential equations. The package also contains functions for common statistical usage of these approximations. The main reference for the methods is Bolin and Kirchner (2019) <arXiv:1711.04333>, which can be generated by the citation function in R.
Depends: R (>= 3.2.0), Matrix
Imports: stats
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, INLA (>= 0.0-1468840039), testthat, excursions
Additional_repositories: https://inla.r-inla-download.org/R/stable
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-19 10:55:52 UTC; davidbolin
Author: David Bolin [cre, aut]
Repository: CRAN
Date/Publication: 2019-08-20 09:10:02 UTC

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New package noisyCE2 with initial version 1.0.0
Package: noisyCE2
Type: Package
Title: Cross-Entropy Optimisation of Noisy Functions
Date: 2019-08-15
Version: 1.0.0
Authors@R: person(given = "Flavio", family = "Santi", role = c("cre", "aut"), email = "flavio.santi@univr.it", comment = c(ORCID = "0000-0002-2014-1981"))
Author: Flavio Santi [cre, aut] (<https://orcid.org/0000-0002-2014-1981>)
Maintainer: Flavio Santi <flavio.santi@univr.it>
URL: https://www.flaviosanti.it/software/noisyCE2
BugReports: https://github.com/f-santi/noisyCE2
Description: Cross-Entropy optimisation of unconstrained deterministic and noisy functions illustrated in Rubinstein and Kroese (2004, ISBN: 978-1-4419-1940-3) through a highly flexible and customisable function which allows user to define custom variable domains, sampling distributions, updating and smoothing rules, and stopping criteria. Several built-in methods and settings make the package very easy-to-use under standard optimisation problems.
Imports: magrittr
Suggests: coda
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-19 12:51:27 UTC; flavio
Repository: CRAN
Date/Publication: 2019-08-20 09:50:02 UTC

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Mon, 19 Aug 2019

New package Rpoet with initial version 1.1.0
Package: Rpoet
Type: Package
Title: 'PoetryDB' API Wrapper
Version: 1.1.0
Author: Aaron Schlegel
Maintainer: Aaron Schlegel <aaron@aaronschlegel.me>
Description: Wrapper for the 'PoetryDB' API <http://poetrydb.org> that allows for interaction and data extraction from the database in an R interface. The 'PoetryDB' API is a database of poetry and poets implemented with 'MongoDB' to enable developers and poets to easily access one of the most comprehensive poetry databases currently available.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
VignetteBuilder: knitr
Suggests: testthat, knitr, rmarkdown, jsonlite, httr, stringr
NeedsCompilation: no
Packaged: 2019-08-19 18:01:10 UTC; aaronschlegel
Repository: CRAN
Date/Publication: 2019-08-19 18:30:06 UTC

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New package hpackedbubble with initial version 0.1.0
Package: hpackedbubble
Title: Create Split Packed Bubble Charts
Version: 0.1.0
Authors@R: person(given = "Zhenxing", family = "Cheng", role = c("aut", "cre"), email = "czxjnu@163.com")
Description: By binding R functions and the 'Highcharts' <http://www.highcharts.com/> charting library, 'hpackedbubble' package provides a simple way to draw split packed bubble charts.
License: MIT + file LICENSE
Date: 2019-08-18
Encoding: UTF-8
Depends: R (>= 3.0.0)
LazyData: true
Imports: htmlwidgets
Suggests: knitr, rmarkdown, shiny, colourpicker
VignetteBuilder: knitr
URL: https://github.com/czxa/hpackedbubble
BugReports: https://github.com/czxa/hpackedbubble/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-19 09:20:52 UTC; czx
Author: Zhenxing Cheng [aut, cre]
Maintainer: Zhenxing Cheng <czxjnu@163.com>
Repository: CRAN
Date/Publication: 2019-08-19 10:40:02 UTC

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New package EmbedSOM with initial version 1.9
Package: EmbedSOM
Version: 1.9
Title: Fast Embedding Guided by Self-Organizing Map
Authors@R: c(person("Mirek", "Kratochvil", role = c("aut", "cre"), email = "exa.exa@gmail.com"), person("Sofie", "Van Gassen", role = "cph", email = "sofie.vangassen@ugent.be"), person("Britt", "Callebaut", role = "cph", email = "britt.callebaut@ugent.be"), person("Yvan", "Saeys", role = "cph", email = "yvan.saeys@ugent.be"), person("Ron", "Wehrens", role = "cph", email = "ron.wehrens@gmail.com"))
Depends: R (>= 3.2)
Suggests: ggplot2, Matrix, igraph, Rtsne, umap, uwot, knitr, rmarkdown
Description: Provides a smooth mapping of multidimensional points into low-dimensional space defined by a self-organizing map. Designed to work with 'FlowSOM' and flow-cytometry use-cases. See Kratochvil et al. (2019) <doi:10.1101/496869>.
License: GPL (>= 3)
LazyData: true
URL: https://bioinfo.uochb.cas.cz/embedsom
Encoding: UTF-8
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-08-19 08:14:27 UTC; exa
Author: Mirek Kratochvil [aut, cre], Sofie Van Gassen [cph], Britt Callebaut [cph], Yvan Saeys [cph], Ron Wehrens [cph]
Maintainer: Mirek Kratochvil <exa.exa@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-19 09:50:02 UTC

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New package APIS with initial version 0.1.0
Package: APIS
Type: Package
Title: Auto-Adaptive Parentage Inference Software Tolerant to Missing Parents
Version: 0.1.0
Author: Ronan Griot, François Allal, Romain Morvezen, Sophie Brard-Fudulea, Pierrick Haffray, Florence Phocas and Marc Vandeputte
Maintainer: Ronan Griot <ronan.griot@gmail.com>
Description: Parentage assignment package. Parentage assignment is performed based on observed average Mendelian transmission probability distributions. The main function of this package is the function APIS(), which is the parentage assignment function.
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.4.0)
Imports: foreach, parallel, doParallel, ggplot2, gridExtra
NeedsCompilation: yes
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Packaged: 2019-08-19 08:13:22 UTC; rgriot
Repository: CRAN
Date/Publication: 2019-08-19 09:50:05 UTC

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New package cotram with initial version 0.1-0
Package: cotram
Title: Count Transformation Models
Version: 0.1-0
Date: 2019-08-19
Authors@R: c( person(given = "Sandra", family = "Siegfried", role = "aut"), person(given = "Torsten", family = "Hothorn", role = c("aut", "cre"), email = "Torsten.Hothorn@R-project.org", comment = c(ORCID = "0000-0001-8301-0471")))
Description: Count transformation models featuring parameters interpretable as discrete hazard ratios, odds ratios, reverse-time discrete hazard ratios, or transformed expectations. An appropriate data transformation for a count outcome and regression coefficients are simultaneously estimated by maximising the exact discrete log-likelihood using the computational framework provided in package 'mlt', technical details are given in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>.
Depends: tram (>= 0.2-6), mlt (>= 1.0-5)
Imports: variables (>= 1.0-2), basefun (>= 1.0-5)
Suggests: TH.data, knitr, lattice, colorspace
VignetteBuilder: knitr
Encoding: UTF-8
License: GPL-2
NeedsCompilation: no
Packaged: 2019-08-19 05:03:34 UTC; hothorn
Author: Sandra Siegfried [aut], Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
Repository: CRAN
Date/Publication: 2019-08-19 08:20:16 UTC

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New package HellCor with initial version 1.2
Package: HellCor
Type: Package
Title: The Hellinger Correlation
Version: 1.2
Date: 2019-08-12
Author: Gery Geenens [aut], Pierre Lafaye De Micheaux [aut, cre]
Authors@R: c(person("Gery", "Geenens", role = c("aut"), email = "ggeenens@unsw.edu.au"), person("Pierre", "Lafaye De Micheaux", role = c("aut", "cre"), email = "lafaye@unsw.edu.au"))
Maintainer: Pierre Lafaye De Micheaux <lafaye@unsw.edu.au>
Description: Empirical value of the Hellinger correlation, a new measure of dependence between two continuous random variables that satisfies a set of 7 desirable axioms (existence, symmetry, normalisation, characterisation of independence, weak Gaussian conformity, characterisation of pure dependence, generalised Data Processing Inequality). More details can be found in Geenens and Lafaye De Micheaux (2018) <arXiv:1810.10276>.
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 2.10.0), energy
Imports: stats
Packaged: 2019-08-12 03:30:27 UTC; lafaye
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2019-08-19 08:00:02 UTC

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Mon, 12 Aug 2019

New package GlmSimulatoR with initial version 0.1.0
Package: GlmSimulatoR
Type: Package
Title: Creates Ideal Data for Generalized Linear Models
Version: 0.1.0
Author: Greg McMahan
Maintainer: Greg McMahan <gmcmacran@gmail.com>
Description: Have you ever struggled to find "good data" for a generalized linear model? Would you like to test how quickly statistics converge to parameters, or learn how picking different link functions affects model performance? This package creates ideal data for both common and novel generalized linear models so your questions can be empirically answered.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: assertthat, stats, purrr, stringr, dplyr, statmod, magrittr, rlang, ggplot2, MASS
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-09 02:01:15 UTC; gmcma
Repository: CRAN
Date/Publication: 2019-08-12 07:20:02 UTC

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Sat, 10 Aug 2019

New package xgxr with initial version 1.0.0
Package: xgxr
Title: Exploratory Graphics for Pharmacometrics
Version: 1.0.0
Authors@R: c(person(given = "Andrew", family = "Stein", role = c("aut", "cre"), email = "andy.stein@gmail.com"), person(given = "Alison", family = "Margolskee", role = "aut"), person(given = "Fariba", family = "Khanshan", role = "aut"), person(given = "Konstantin", family = "Krismer", role = "aut", email = "krismer@mit.edu", comment = c(ORCID = "0000-0001-8994-3416")), person(given = "Matthew", family = "Fidler", role = "ctb", email = "matthew.fidler@gmail.com", comment = c(ORCID = "0000-0001-8538-6691")), person("Novartis Pharma AG", role = c("cph","fnd")))
Description: Supports a structured approach for exploring PKPD data <https://opensource.nibr.com/xgx>. It also contains helper functions for enabling the modeler to follow best R practices (by appending the program name, figure name location, and draft status to each plot). In addition, it enables the modeler to follow best graphical practices (by providing a theme that reduces chart ink, and by providing time-scale, log-scale, and reverse-log-transform-scale functions for more readable axes). Finally, it provides some data checking and summarizing functions for rapidly exploring pharmacokinetics and pharmacodynamics (PKPD) datasets.
License: MIT + file LICENSE
URL: https://opensource.nibr.com/xgx
Depends: R (>= 3.4.0)
Imports: assertthat, binom, dplyr, ggplot2, graphics, grDevices, labeling, magrittr, pander, png, scales, stats, tibble, utils
Suggests: caTools, gridExtra, knitr, rmarkdown, RxODE, stringr, testthat, tidyr
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-09 16:35:29 UTC; steinanf
Author: Andrew Stein [aut, cre], Alison Margolskee [aut], Fariba Khanshan [aut], Konstantin Krismer [aut] (<https://orcid.org/0000-0001-8994-3416>), Matthew Fidler [ctb] (<https://orcid.org/0000-0001-8538-6691>), Novartis Pharma AG [cph, fnd]
Maintainer: Andrew Stein <andy.stein@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-10 09:30:02 UTC

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New package spiritR with initial version 0.1.0
Package: spiritR
Title: Template for Clinical Trial Protocol
Version: 0.1.0
Authors@R: person(given = "Aaron", family = "Conway", role = c("aut", "cre"), email = "aaron.conway@utoronto.ca", comment = c(ORCID = "0000-0002-9583-8636"))
Description: Contains an R Markdown template for a clinical trial protocol adhering to the SPIRIT statement. The SPIRIT (Standard Protocol Items for Interventional Trials) statement outlines recommendations for a minimum set of elements to be addressed in a clinical trial protocol. Also contains functions to create a xml document from the template and upload it to clinicaltrials.gov<https://www.clinicaltrials.gov/> for trial registration.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: xml2, httr, magrittr, tibble
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, pkgdown
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2019-08-09 18:10:55 UTC; aaronconway
Author: Aaron Conway [aut, cre] (<https://orcid.org/0000-0002-9583-8636>)
Maintainer: Aaron Conway <aaron.conway@utoronto.ca>
Repository: CRAN
Date/Publication: 2019-08-10 09:30:07 UTC

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New package ds4psy with initial version 0.1.0
Package: ds4psy
Type: Package
Title: Data Science for Psychologists
Version: 0.1.0
Date: 2019-08-09
Authors@R: c(person("Hansjoerg", "Neth", role = c("aut", "cre"), email = "h.neth@uni.kn"))
Author: Hansjoerg Neth [aut, cre]
Maintainer: Hansjoerg Neth <h.neth@uni.kn>
Description: All data sets required for the examples and exercises in the book "Data Science for Psychologists" (by Hansjoerg Neth, Konstanz University, 2019), freely available at <https://bookdown.org/hneth/ds4psy/>. The book and course introduce principles and methods of data science to students of psychology and other biological or social sciences. The 'ds4psy' package primarily provides datasets, but also functions for graphics and text-manipulation that are used in the book and its exercises.
Depends: R (>= 3.4.0)
Imports: ggplot2, cowplot, here, readr, stringr, tibble, tidyr, tidyverse, unikn
Suggests: knitr, rmarkdown, spelling
Collate: 'data.R' 'color_fun.R' 'text_fun.R' 'data_fun.R' 'theme_fun.R' 'plot_fun.R' 'util_fun.R' 'start.R'
Encoding: UTF-8
LazyData: true
License: CC BY-SA 4.0
URL: https://bookdown.org/hneth/ds4psy/, https://github.com/hneth/ds4psy/
BugReports: https://github.com/hneth/ds4psy/issues
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Language: en-US
NeedsCompilation: no
Packaged: 2019-08-09 17:52:11 UTC; hneth
Repository: CRAN
Date/Publication: 2019-08-10 09:30:10 UTC

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Fri, 09 Aug 2019

New package censusxy with initial version 0.1.2
Package: censusxy
Title: Access the U.S. Census Bureau Geocoder
Version: 0.1.2
Authors@R: c( person("Christopher", "Prener", ,"chris.prener@slu.edu", c("aut", "cre"), comment = c(ORCID = "0000-0002-4310-9888")), person("Branson", "Fox", ,"branson.fox@slu.edu", c("aut"), comment = c(ORCID = "0000-0002-4361-2811")) )
Description: Provides access to the U.S. Census Bureau's API for batch geocoding American street addresses (<https://geocoding.geo.census.gov/geocoder>). The package offers a batch solution for address geocoding, as opposed to geocoding a single address at a time. It has also been developed specifically with large data sets in mind - only unique addresses are passed to the API for geocoding. If a data set exceeds 1,000 unique addresses, it will be automatically subset into appropriately sized API calls, geocoded, and then put back together so that a single object is returned.
Depends: R (>= 3.3)
License: GPL-3
URL: https://github.com/slu-openGIS/censusxy
BugReports: https://github.com/slu-openGIS/censusxy/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: dplyr, httr, readr, rlang, sf, tibble, tidyr
Suggests: covr, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-09 15:12:52 UTC; chris
Author: Christopher Prener [aut, cre] (<https://orcid.org/0000-0002-4310-9888>), Branson Fox [aut] (<https://orcid.org/0000-0002-4361-2811>)
Maintainer: Christopher Prener <chris.prener@slu.edu>
Repository: CRAN
Date/Publication: 2019-08-09 22:10:05 UTC

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New package butcher with initial version 0.1.0
Package: butcher
Title: Model Butcher
Version: 0.1.0
Authors@R: c( person(given = "Joyce", family = "Cahoon", role = c("aut", "cre"), email = "joyceyu48@gmail.com", comment = c(ORCID = "0000-0001-7217-4702")), person(given = "Davis", family = "Vaughan", role = "aut", email = "davis@rstudio.com"), person(given = "Max", family = "Kuhn", role = "aut", email = "max@rstudio.com"), person(given = "Alex", family = "Hayes", role = "aut", email = "alexpghayes@gmail.com"))
Description: Provides a set of five S3 generics to axe components of fitted model objects and help reduce the size of model objects saved to disk.
License: MIT + file LICENSE
URL: https://tidymodels.github.io/butcher, https://github.com/tidymodels/butcher
BugReports: https://github.com/tidymodels/butcher/issues
Encoding: UTF-8
LazyData: true
Imports: purrr, rlang, lobstr (>= 1.1.1), tibble (>= 2.1.1), usethis, fs, utils, methods
RoxygenNote: 6.1.1
Suggests: clisymbols, testthat (>= 2.1.0), parsnip, knitr, rmarkdown, C50, kknn, glmnet, rpart, ranger, recipes, rsample, TH.data, ipred, survival, MASS, QSARdata, caret, flexsurv, pkgload, sparklyr, randomForest, kernlab, earth, covr, rstan, rstanarm, e1071, nnet, xgboost, dplyr, mda
Depends: R (>= 3.1)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-09 14:27:47 UTC; jcahoon
Author: Joyce Cahoon [aut, cre] (<https://orcid.org/0000-0001-7217-4702>), Davis Vaughan [aut], Max Kuhn [aut], Alex Hayes [aut]
Maintainer: Joyce Cahoon <joyceyu48@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-09 15:30:02 UTC

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New package scrypt with initial version 0.1.3
Package: scrypt
Type: Package
Title: Key Derivation Functions for R Based on Scrypt
Version: 0.1.3
Authors@R: c( person("Bob", "Jansen", email = "bobjansen@gmail.com", role = c("ctb", "cre")), person("Andy", "Kipp", email = "andy@rstudio.com", role = c("aut")), person("Colin", "Percival", role = c("aut", "cph")), person(family = "RStudio", role = "cph") )
Copyright: RStudio, Inc.; Colin Percival
Maintainer: Bob Jansen <bobjansen@gmail.com>
Description: Functions for working with the scrypt key derivation functions originally described by Colin Percival <https://www.tarsnap.com/scrypt/scrypt.pdf> and in Percival and Josefsson (2016) <doi:10.17487/RFC7914>. Scrypt is a password-based key derivation function created by Colin Percival. The algorithm was specifically designed to make it costly to perform large-scale custom hardware attacks by requiring large amounts of memory.
License: FreeBSD
Depends: R (>= 3.0.0)
URL: https://github.com/rstudio/rscrypt
Imports: Rcpp (>= 0.10.6)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2019-07-21 16:15:29 UTC; brj
Author: Bob Jansen [ctb, cre], Andy Kipp [aut], Colin Percival [aut, cph], RStudio [cph]
Repository: CRAN
Date/Publication: 2019-08-09 13:30:08 UTC

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New package interimApp with initial version 0.0.1
Package: interimApp
Title: App for Scheduling Interim Analyses in Clinical Trials
Version: 0.0.1
Author: Bastian Becker, Katharina Mueller, Hermann Kulmann
Maintainer: Bastian Becker <bastian.becker@bayer.com>
Description: Allows an interactive assessment of the timing of interim analyses. The algorithm simulates both the recruitment and treatment/event phase of a clinical trial based on the package 'interim'.
License: GPL
Encoding: UTF-8
LazyData: true
Depends: interim, shiny, shinyBS
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2019-08-08 14:12:19 UTC; EUFIB
Repository: CRAN
Date/Publication: 2019-08-09 13:40:02 UTC

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New package tabulog with initial version 0.1.1
Package: tabulog
Type: Package
Title: Parsing Semi-Structured Log Files into Tabular Format
Version: 0.1.1
Author: Austin Nar
Maintainer: Austin Nar <austin.nar@gmail.com>
Description: Convert semi-structured log files (such as 'Apache' access.log files) into a tabular format (data.frame) using a standard template system.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: yaml
Suggests: lubridate, knitr, readr
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-08 23:26:40 UTC; nar
Repository: CRAN
Date/Publication: 2019-08-09 13:00:02 UTC

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New package spatstat.Knet with initial version 1.11-2
Package: spatstat.Knet
Type: Package
Title: Extension to 'spatstat' for Large Datasets on a Linear Network
Version: 1.11-2
Date: 2019-08-09
Depends: R (>= 3.3.0), spatstat (>= 1.60-0)
Imports: spatstat.utils, Matrix
Authors@R: c(person(given="Suman", family="Rakshit", role = c("aut", "cph"), email = "suman.rakshit@curtin.edu.au", comment=c(ORCID="0000-0003-0052-128X")), person(given="Adrian", family="Baddeley", role = c("cre", "cph"), email = "Adrian.Baddeley@curtin.edu.au", comment = c(ORCID="0000-0001-9499-8382")))
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>
Description: Extension to the 'spatstat' package, for analysing large datasets of spatial points on a network. Provides a memory-efficient algorithm for computing the geometrically-corrected K function, described in S. Rakshit, A. Baddeley and G. Nair (2019) <doi:10.18637/jss.v090.i01>
License: GPL (>= 2)
NeedsCompilation: yes
ByteCompile: true
Packaged: 2019-08-09 07:15:42 UTC; adrian
Author: Suman Rakshit [aut, cph] (<https://orcid.org/0000-0003-0052-128X>), Adrian Baddeley [cre, cph] (<https://orcid.org/0000-0001-9499-8382>)
Repository: CRAN
Date/Publication: 2019-08-09 11:40:02 UTC

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New package VOSONDash with initial version 0.4.4
Package: VOSONDash
Version: 0.4.4
Title: User Interface for Collecting and Analysing Social Networks
Description: A 'Shiny' application for the interactive visualisation and analysis of networks that also provides a web interface for collecting social media data using 'vosonSML'.
Type: Package
Imports: shiny (>= 1.3.2), magrittr, igraph (>= 1.2.2), rtweet (>= 0.6.8), vosonSML (>= 0.27.0), RColorBrewer, tm, wordcloud, syuzhet, httr, utils, graphics, lattice, httpuv
Depends: R (>= 3.2.0)
Encoding: UTF-8
Author: Bryan Gertzel, Robert Ackland
Maintainer: Bryan Gertzel <bryan.gertzel@anu.edu.au>
License: GPL (>= 3)
RoxygenNote: 6.1.1
NeedsCompilation: no
URL: https://github.com/vosonlab/VOSONDash
BugReports: https://github.com/vosonlab/VOSONDash/issues
Packaged: 2019-08-08 13:01:10 UTC; blue
Repository: CRAN
Date/Publication: 2019-08-09 10:20:03 UTC

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New package valetr with initial version 0.1.0
Package: valetr
Version: 0.1.0
Title: Interface to Bank of Canada's 'Valet' API
Authors@R: person("José", "de Mello", role=c("aut", "cre"), email="zedemellonetto@gmail.com")
Depends: R (>= 3.1.0)
Imports: jsonlite (>= 0.9), curl
Suggests: knitr, rmarkdown, data.table, ggplot2
VignetteBuilder: knitr
Maintainer: José de Mello <zedemellonetto@gmail.com>
Description: Interface to Bank of Canada's 'Valet' API (<https://www.bankofcanada.ca/valet/docs>). Please read the API terms and conditions: <https://www.bankofcanada.ca/terms/>.
License: GPL-3
URL: https://github.com/jdemello/valetr
BugReports: https://github.com/jdemello/valetr/issues
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-08 14:38:30 UTC; jdemello
Author: José de Mello [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-09 10:50:02 UTC

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New package thurstonianIRT with initial version 0.9.0
Package: thurstonianIRT
Encoding: UTF-8
Type: Package
Title: Thurstonian IRT Models
Version: 0.9.0
Date: 2019-08-07
Authors@R: c(person("Paul-Christian", "Bürkner", email = "paul.buerkner@gmail.com", role = c("aut", "cre")), person("Trustees of Columbia University", role = "cph"))
Description: Fit Thurstonian Item Response Theory (IRT) models in R. This package supports fitting Thurstonian IRT models and its extensions using 'Stan', 'lavaan', or 'Mplus' for the model estimation. Functionality for extracting results and simulating data is provided as well. References: Brown & Maydeu-Olivares (2011) <doi:10.1177/0013164410375112>; Bürkner et al. (2019) <doi:10.1177/0013164419832063>.
License: GPL (>= 3)
LazyData: true
ByteCompile: true
Depends: R (>= 3.2.0), Rcpp (>= 0.12.16), methods
Imports: rstan (>= 2.17.3), rstantools (>= 1.5.0), lavaan (>= 0.6-1), MplusAutomation, dplyr (>= 0.6.0), tibble (>= 1.3.1), tidyr, magrittr, mvtnorm, utils, stats, rlang
Suggests: testthat (>= 0.9.1),
LinkingTo: StanHeaders (>= 2.17.2), rstan (>= 2.17.3), BH (>= 1.66.0-1), Rcpp (>= 0.12.16), RcppEigen (>= 0.3.3.4.0)
SystemRequirements: GNU make
URL: https://github.com/paul-buerkner/thurstonianIRT
BugReports: https://github.com/paul-buerkner/thurstonianIRT/issues
NeedsCompilation: yes
RoxygenNote: 6.1.1
Packaged: 2019-08-08 14:24:48 UTC; paulb
Author: Paul-Christian Bürkner [aut, cre], Trustees of Columbia University [cph]
Maintainer: Paul-Christian Bürkner <paul.buerkner@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-09 10:40:02 UTC

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New package protag with initial version 1.0.0
Package: protag
Title: Search Tagged Peptides & Draw Highlighted Mass Spectra
Version: 1.0.0
Authors@R: person(given = "Bo", family = "Yuan", role = c("aut", "cre"), email = "yuanbo.faith@gmail.com")
Description: In a typical protein labelling procedure, proteins are chemically tagged with a functional group, usually at specific sites, then digested into peptides, which are then analyzed using matrix-assisted laser desorption ionization - time of flight mass spectrometry (MALDI-TOF MS) to generate peptide fingerprint. Relative to the control, peptides that are heavier by the mass of the labelling group are informative for sequence determination. Searching for peptides with such mass shifts, however, can be difficult. This package, designed to tackle this inconvenience, takes as input the mass list of two or multiple MALDI-TOF MS mass lists, and makes pairwise comparisons between the labeled groups vs. control, and restores centroid mass spectra with highlighted peaks of interest for easier visual examination. Particularly, peaks differentiated by the mass of the labelling group are defined as a “pair”, those with equal masses as a “match”, and all the other peaks as a “mismatch”.For more bioanalytical background information, refer to following publications: Jingjing Deng (2015) <doi:10.1007/978-1-4939-2550-6_19>; Elizabeth Chang (2016) <doi:10.7171/jbt.16-2702-002>.
Depends: R (>= 2.10)
Imports: ggplot2, dplyr, RColorBrewer, grDevices
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-08-08 00:17:47 UTC; Boyuan
Author: Bo Yuan [aut, cre]
Maintainer: Bo Yuan <yuanbo.faith@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-09 10:10:02 UTC

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New package PPMR with initial version 1.0
Package: PPMR
Title: Probabilistic Two Sample Mendelian Randomization
Type: Package
Version: 1.0
Authors@R: c( person(given = "Zhongshang", family = "Yuan", role = c("aut")), person(given = "Xiang", family = "Zhou", role = c("aut"), email = "xzhousph@umich.edu"), person(given = "Michael", family = "Kleinsasser", role = c("cre"), email = "mkleinsa@umich.edu"))
Description: Efficient statistical inference of two-sample MR (Mendelian Randomization) analysis. It can account for the correlated instruments and the horizontal pleiotropy, and can provide the accurate estimates of both causal effect and horizontal pleiotropy effect as well as the two corresponding p-values. There are two main functions in the 'PPMR' package. One is PMR_individual() for individual level data, the other is PMR_summary() for summary data.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1.9000
NeedsCompilation: yes
BugReports: https://github.com/umich-biostatistics/PPMR/issues
Packaged: 2019-08-08 13:46:00 UTC; mkleinsa
Author: Zhongshang Yuan [aut], Xiang Zhou [aut], Michael Kleinsasser [cre]
Maintainer: Michael Kleinsasser <mkleinsa@umich.edu>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-08-09 10:20:07 UTC

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New package grainscape with initial version 0.4.0
Package: grainscape
Type: Package
Title: Landscape Connectivity, Habitat, and Protected Area Networks
Description: Given a landscape resistance surface, creates grains of connectivity (Galpern et al. (2012) <doi:10.1111/j.1365-294X.2012.05677.x>) and minimum planar graph (Fall et al. (2007) <doi:10.1007/s10021-007-9038-7>) models that can be used to calculate effective distances for landscape connectivity at multiple scales.
URL: https://achubaty.github.io/grainscape, https://github.com/achubaty/grainscape
Version: 0.4.0
Date: 2019-08-06
Authors@R: c( person("Paul", "Galpern", email = "pgalpern@gmail.com", role = c("aut", "cph")), person("Sam", "Doctolero", email = "sam.doctolero@gmail.com", role = "aut"), person("Alex M", "Chubaty", email = "alex.chubaty@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7146-8135")) )
License: GPL (>= 2)
Imports: ggplot2, graphics, grDevices, igraph, methods, sp, raster, Rcpp (>= 0.12.11.4), rgdal, utils
LinkingTo: Rcpp
Suggests: cowplot, ggthemes, hunspell, knitr, parallel, rgeos, rmarkdown, spelling, testthat
VignetteBuilder: knitr, rmarkdown
BugReports: https://github.com/achubaty/grainscape/issues
ByteCompile: yes
Collate: 'grainscape-package.R' 'classes.R' 'GOC.R' 'MPG.R' 'RcppExports.R' 'grain.R' 'corridor.R' 'deprecated.R' 'distance.R' 'export.R' 'extract.R' 'ggGS.R' 'graphdf.R' 'habitatConnectivityEngine.R' 'patchFilter.R' 'plot.R' 'point.R' 'theme_grainscape.R' 'threshold.R' 'zzz.R'
Encoding: UTF-8
Language: en-CA
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-08-08 14:13:50 UTC; achubaty
Author: Paul Galpern [aut, cph], Sam Doctolero [aut], Alex M Chubaty [aut, cre] (<https://orcid.org/0000-0001-7146-8135>)
Maintainer: Alex M Chubaty <alex.chubaty@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-09 10:30:02 UTC

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New package cyanoFilter with initial version 0.1.1
Package: cyanoFilter
Title: Cyanobacteria Population Identification for Flow Cytometry
Version: 0.1.1
Authors@R: c(person("Oluwafemi", "Olusoji", email = "oluwafemi.olusoji@uhasselt.be", role = c("aut", "cre")), person("Aerts", "Marc", email = "marc.aerts@uhasselt.be", role = "ctb"), person("Delaender", "Frederik", email = "frederik.delaender@unamur.be", role = "ctb"), person("Neyens", "Thomas", email = "thomas.neyens@uhasselt.be", role = "ctb"), person("Spaak", "jurg", email = "jurg.spaak@unamur.be", role = "aut"))
Maintainer: Oluwafemi Olusoji <oluwafemi.olusoji@uhasselt.be>
Description: An approach to filter out and/or identify two synechococcus type cyanobacteria cells from all particles measured via flow cytometry. It combines known characteristics of these two cyanobacteria strains (BS4 and BS5) alongside gating techniques developed by Mehrnoush, M. et al. (2015) <doi:10.1093/bioinformatics/btu677> in the 'flowDensity' package to identify and separate these cyanobacteria cells from other cell types. Aside the gating techniques in the 'flowDensity' package, an EM style clustering technique is also developed to identify these cyanobacteria cell populations.
URL: https://github.com/fomotis/cyanoFilter
BugReports: https://github.com/fomotis/cyanoFilter/issues
Depends: R(>= 3.4), Biobase(>= 2.40.0)
Imports: flowCore(>= 1.42.3), flowDensity (>= 1.10.0), graphics(>= 3.6.0), grDevices(>= 3.6.0), methods(>= 3.5.1), RColorBrewer(>= 1.1-2), Rdpack(>= 0.11-0), stats(>= 3.6.0), stringr(>= 1.3.1), utils(>= 3.6.0)
RdMacros: Rdpack
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: dplyr, magrittr, knitr, rmarkdown, tidyr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-08 13:35:48 UTC; lucp9544
Author: Oluwafemi Olusoji [aut, cre], Aerts Marc [ctb], Delaender Frederik [ctb], Neyens Thomas [ctb], Spaak jurg [aut]
Repository: CRAN
Date/Publication: 2019-08-09 10:30:06 UTC

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New package BESTree with initial version 0.5.2
Package: BESTree
Type: Package
Title: Branch-Exclusive Splits Trees
Version: 0.5.2
Authors@R: person("Beaulac", "Cedric", email = "cedric@utstat.toronto.edu", role = c("aut", "cre"))
Description: Decision tree algorithm with a major feature added. Allows for users to define an ordering on the partitioning process. Resulting in Branch-Exclusive Splits Trees (BEST). Cedric Beaulac and Jeffrey S. Rosentahl (2019) <arXiv:1804.10168>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: plyr, compiler, utils, stats
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
Depends: R (>= 2.10)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-08 16:22:38 UTC; The Beast
Author: Beaulac Cedric [aut, cre]
Maintainer: Beaulac Cedric <cedric@utstat.toronto.edu>
Repository: CRAN
Date/Publication: 2019-08-09 11:00:02 UTC

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Thu, 08 Aug 2019

New package sass with initial version 0.1.2.1
Type: Package
Package: sass
Version: 0.1.2.1
Title: Syntactically Awesome Style Sheets ('Sass')
Description: An 'SCSS' compiler, powered by the 'LibSass' library. With this, R developers can use variables, inheritance, and functions to generate dynamic style sheets. The package uses the 'Sass CSS' extension language, which is stable, powerful, and CSS compatible.
Authors@R: c( person("Joe", "Cheng", , "joe@rstudio.com", c("aut", "cre")), person("Timothy", "Mastny", , "tim.mastny@gmail.com", "aut"), person("Richard", "Iannone", , "rich@rstudio.com", "aut", comment = c(ORCID = "0000-0003-3925-190X")), person("Barret", "Schloerke", , "barret@rstudio.com", "aut", comment = c(ORCID = "0000-0001-9986-114X")), person(family = "RStudio", role = c("cph", "fnd")), person(family = "Sass Open Source Foundation", role = c("ctb", "cph"), comment = "LibSass library"), person("Greter", "Marcel", role = c("ctb", "cph"), comment = "LibSass library"), person("Mifsud", "Michael", role = c("ctb", "cph"), comment = "LibSass library"), person("Hampton", "Catlin", role = c("ctb", "cph"), comment = "LibSass library"), person("Natalie", "Weizenbaum", role = c("ctb", "cph"), comment = "LibSass library"), person("Chris", "Eppstein", role = c("ctb", "cph"), comment = "LibSass library"), person("Adams", "Joseph", role = c("ctb", "cph"), comment = "json.cpp"), person("Trifunovic", "Nemanja", role = c("ctb", "cph"), comment = "utf8.h") )
License: MIT + file LICENSE
URL: https://github.com/rstudio/sass
BugReports: https://github.com/rstudio/sass/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
SystemRequirements: GNU make
Imports: digest
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-08-08 15:52:57 UTC; jcheng
Author: Joe Cheng [aut, cre], Timothy Mastny [aut], Richard Iannone [aut] (<https://orcid.org/0000-0003-3925-190X>), Barret Schloerke [aut] (<https://orcid.org/0000-0001-9986-114X>), RStudio [cph, fnd], Sass Open Source Foundation [ctb, cph] (LibSass library), Greter Marcel [ctb, cph] (LibSass library), Mifsud Michael [ctb, cph] (LibSass library), Hampton Catlin [ctb, cph] (LibSass library), Natalie Weizenbaum [ctb, cph] (LibSass library), Chris Eppstein [ctb, cph] (LibSass library), Adams Joseph [ctb, cph] (json.cpp), Trifunovic Nemanja [ctb, cph] (utf8.h)
Maintainer: Joe Cheng <joe@rstudio.com>
Repository: CRAN
Date/Publication: 2019-08-08 22:40:02 UTC

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New package mssm with initial version 0.1.2
Package: mssm
Type: Package
Title: Multivariate State Space Models
Version: 0.1.2
Authors@R: c( person("Benjamin", "Christoffersen", email = "boennecd@gmail.com", role = c("cre", "aut")), person("Anthony", "Williams", role = c("cph")))
Description: Provides methods to perform parameter estimation and make analysis of multivariate observed outcomes through time which depends on a latent state variable. All methods scale well in the dimension of the observed outcomes at each time point. The package contains an implementation of a Laplace approximation, particle filters like suggested by Lin, Zhang, Cheng, & Chen (2005) <doi:10.1198/016214505000000349>, and the gradient and observed information matrix approximation suggested by Poyiadjis, Doucet, & Singh (2011) <doi:10.1093/biomet/asq062>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), stats, graphics
LinkingTo: Rcpp, RcppArmadillo, testthat, nloptr (>= 1.2.0)
Imports: Rcpp, nloptr (>= 1.2.0)
RoxygenNote: 6.1.1
SystemRequirements: C++11
Suggests: testthat, microbenchmark, Ecdat
NeedsCompilation: yes
Packaged: 2019-08-08 19:51:19 UTC; boennecd
Author: Benjamin Christoffersen [cre, aut], Anthony Williams [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-08 22:50:02 UTC

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New package diffman with initial version 0.1.0
Package: diffman
Type: Package
Title: Detect Differentiation Problems
Version: 0.1.0
Date: 2019-08-01
Maintainer: Vianney Costemalle <vianney.costemalle@insee.fr>
Description: An algorithm based on graph theory tools to detect differentiation problems. A differentiation problem occurs when aggregated data are disseminated according to two different nomenclatures. By making the difference for an additive variable X between an aggregate composed of categories of the first nomenclature and an other aggregate, included in that first aggregate, composed of categories of the second nomenclature, it is sometimes possible to derive X on a small aggregate of records which could then lead to a break of confidentiality. The purpose of this package is to detect the set of aggregates composed of categories of the first nomenclature which lead to a differentiation problem, when given a confidentiality threshold.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat
Imports: tidyverse, igraph, progress, Rcpp, sf, dplyr, Matrix, data.table
LinkingTo: Rcpp
Authors@R: c(person("Vianney", "Costemalle", email = "vianney.costemalle@insee.fr", role = c("aut", "cre")),person("Arlindo", "Dos Santos", email = "arlindo.dos.santos@insee.fr", role = "aut"),person("Francois", "Semecurbe", email = "francois.semecurbe@insee.fr", role = "aut"))
NeedsCompilation: yes
Packaged: 2019-08-07 16:49:09 UTC; wjly0q
Author: Vianney Costemalle [aut, cre], Arlindo Dos Santos [aut], Francois Semecurbe [aut]
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-08-08 15:10:02 UTC

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New package fabletools with initial version 0.1.0
Package: fabletools
Version: 0.1.0
Title: Core Tools for Packages in the 'fable' Framework
Description: Provides tools, helpers and data structures for developing models and time series functions for 'fable' and extension packages. These tools support a consistent and tidy interface for time series modelling and analysis.
Authors@R: c(person(given = "Mitchell", family = "O'Hara-Wild", email = "mail@mitchelloharawild.com", role = c("aut", "cre")), person(given = "Rob", family = "Hyndman", role = "aut"), person(given = "Earo", family = "Wang", role = "aut"), person(given = "Di", family = "Cook", role = "ctb"))
Depends: R (>= 3.1.3)
Imports: tsibble (>= 0.8.0), ggplot2 (>= 3.0.0), tidyselect, rlang (>= 0.2.0), stats, dplyr (>= 0.8.0), tidyr (>= 0.8.3), generics, R6, utils
Suggests: colorspace, covr, crayon, digest, fable, furrr, knitr, methods, tibble (>= 1.4.1), pillar (>= 1.0.1), feasts, rmarkdown, scales, spelling, testthat, tsibbledata, lubridate, SparseM
Additional_repositories: https://tidyverts.org/
ByteCompile: true
License: GPL-3
URL: http://fabletools.tidyverts.org/
BugReports: https://github.com/tidyverts/fabletools/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Language: en-GB
NeedsCompilation: no
Packaged: 2019-08-08 12:20:24 UTC; mitchell
Author: Mitchell O'Hara-Wild [aut, cre], Rob Hyndman [aut], Earo Wang [aut], Di Cook [ctb]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>
Repository: CRAN
Date/Publication: 2019-08-08 14:30:02 UTC

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New package accept with initial version 0.7.0
Package: accept
Title: The Acute COPD Exacerbation Prediction Tool (ACCEPT)
Version: 0.7.0
Authors@R: c( person("Amin", "Adibi", email = "adibi@alumni.ubc.ca", role = c("aut", "cre")), person("Mohsen", "Sadatsafavi", email = "mohsen.sadatsafavi@ubc.ca", role = c("aut", "cph")), person("Ainsleigh", "Hill", email = "ainsleigh.hill@alumni.ubc.ca", role = c("aut")))
Description: Allows clinicians to predict the rate and severity of future acute exacerbation in Chronic Obstructive Pulmonary Disease (COPD) patients, based on the clinical prediction model published in Adibi et al. (2019) <doi:10.1101/651901>.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: stats, MASS, dplyr, stringr, extrafont, plotly, viridis
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-08 12:11:32 UTC; amin
Author: Amin Adibi [aut, cre], Mohsen Sadatsafavi [aut, cph], Ainsleigh Hill [aut]
Maintainer: Amin Adibi <adibi@alumni.ubc.ca>
Repository: CRAN
Date/Publication: 2019-08-08 14:30:04 UTC

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New package mrfse with initial version 0.1
Package: mrfse
Title: Markov Random Field Structure Estimator
Version: 0.1
Date: 2019-08-06
Description: A Markov random field structure estimator that uses a penalized maximum conditional likelihood method similar to the Bayesian Information Criterion (Frondana, 2016) <doi:10.11606/T.45.2018.tde-02022018-151123>.
License: GPL (>= 3)
Author: Rodrigo Carvalho [aut, cre], Florencia Leonardi [rev, ths]
Maintainer: Rodrigo Carvalho <rodrigorsdc@gmail.com>
NeedsCompilation: yes
Packaged: 2019-08-07 17:07:54 UTC; root
Repository: CRAN
Date/Publication: 2019-08-08 13:40:02 UTC

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New package meteor with initial version 0.3-4
Package: meteor
Type: Package
Title: Meteorological Data Manipulation
Version: 0.3-4
LinkingTo: Rcpp
SystemRequirements: C++11
Imports: methods, Rcpp (>= 0.12.4)
Date: 2019-08-07
Description: A set of functions for weather and climate data manipulation, and other helper functions, to support dynamic ecological modelling, particularly crop and crop disease modeling.
License: GPL (>= 3)
Authors@R: c(person("Robert J.", "Hijmans", role = c("cre", "aut"), email = "r.hijmans@gmail.com", comment = c(ORCID = "0000-0001-5872-2872")), person("Maarten", "Waterloo", role = "ctb"))
BugReports: https://github.com/cropmodels/meteor/issues/
NeedsCompilation: yes
Packaged: 2019-08-08 06:55:58 UTC; rhijm
Author: Robert J. Hijmans [cre, aut] (<https://orcid.org/0000-0001-5872-2872>), Maarten Waterloo [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-08 14:00:02 UTC

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New package CorBin with initial version 0.3.1
Package: CorBin
Type: Package
Title: Generate High-Dimensional Binary Data with Correlation Structures
Version: 0.3.1
Author: Shuang Song [aut, cre], Wei Jiang [aut], Lin Hou [aut] and Hongyu Zhao [aut]
Maintainer: Shuang Song <song-s19@mails.tsinghua.edu.cn>
Description: We design algorithms with linear time complexity with respect to the dimension for three commonly studied correlation structures, including exchangeable, decaying-product and K-dependent correlation structures, and extend the algorithms to generate binary data of general non-negative correlation matrices with quadratic time complexity. Jiang, W., Song, S., Hou, L. and Zhao, H. "CorBin: An efficient R package to generate high-dimensional binary data with correlation structures." Submitted to Journal of Statistical Software.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-08 02:42:31 UTC; lenovo
Repository: CRAN
Date/Publication: 2019-08-08 13:40:05 UTC

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New package ClickClustCont with initial version 0.1.6
Package: ClickClustCont
Type: Package
Title: Mixtures of Continuous Time Markov Models
Version: 0.1.6
Date: 2019-08-08
Author: Michael P.B. Gallaugher, Paul D. McNicholas
Maintainer: Michael P.B. Gallaugher <gallaump@mcmaster.ca>
Description: Provides an expectation maximization (EM) algorithm to fit a mixture of continuous time Markov models for use with clickstream or other sequence type data. Gallaugher, M.P.B and McNicholas, P.D. (2018) <arXiv:1802.04849>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: gtools
NeedsCompilation: no
Packaged: 2019-08-08 05:47:35 UTC; michaelgallaugher
Repository: CRAN
Date/Publication: 2019-08-08 13:50:03 UTC

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New package sabarsi with initial version 0.1.0
Package: sabarsi
Type: Package
Title: Background Removal and Spectrum Identification for SERS Data
Version: 0.1.0
Authors@R: c( person("Li", "Jun", email = "jun.li@nd.edu", role = "cre"), person("Wang", "Chuanqi", email = "cwang14@nd.edu", role = 'aut'))
Description: Implements a new approach 'SABARSI' described in Wang et al., "A Statistical Approach of Background Removal and Spectrum Identification for SERS Data" (Unpublished). Sabarsi forms a pipeline for SERS (surface-enhanced Raman scattering) data analysis including background removal, signal detection, signal integration, and cross-experiment comparison. The background removal algorithm, the very first step of SERS data analysis, takes into account the change of background shape.
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown (>= 1.13)
Imports: stats (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-07 11:29:47 UTC; Chuanqi
Author: Li Jun [cre], Wang Chuanqi [aut]
Maintainer: Li Jun <jun.li@nd.edu>
Repository: CRAN
Date/Publication: 2019-08-08 12:30:02 UTC

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New package bracer with initial version 1.0.1
Package: bracer
Title: Brace Expansions
Version: 1.0.1
Authors@R: person(given = "Trevor", family = "Davis", role = c("aut", "cre"), email = "trevor.l.davis@gmail.com")
Description: Performs brace expansions on strings. Made popular by Unix shells, brace expansion allows users to quickly generate certain character vectors by taking a single string and (recursively) expanding the comma-separated lists and double-period-separated integer and character sequences enclosed within braces in that string. The double-period-separated numeric integer expansion also supports padding the resulting numbers with zeros.
Imports: stringr
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: covr, testthat
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-07 18:36:31 UTC; trevorld
Author: Trevor Davis [aut, cre]
Maintainer: Trevor Davis <trevor.l.davis@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-08 13:00:03 UTC

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Wed, 07 Aug 2019

New package DistributionTest with initial version 1.0
Package: DistributionTest
Type: Package
Title: Powerful Goodness-of-Fit Tests Based on the Likelihood Ratio
Version: 1.0
Date: 2019-08-02
Author: Ning Cui [aut, cre], Maoyuan Zhou [ctb]
Maintainer: Ning Cui <2433971953@qq.com>
Description: Provides new types of omnibus tests which are generally much more powerful than traditional tests (including the Kolmogorov-Smirnov, Cramer-von Mises and Anderson-Darling tests),see Zhang (2002) <doi:10.1111/1467-9868.00337>.
License: GPL (>= 3)
Imports: stats, MASS
Repository: CRAN
NeedsCompilation: no
Packaged: 2019-08-07 03:44:52 UTC; Lenovo
Date/Publication: 2019-08-07 15:20:03 UTC

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New package ClimMobTools with initial version 0.2-6
Package: ClimMobTools
Type: Package
Title: Tools for Crowdsourcing Citizen Science in Agriculture
Version: 0.2-6
Authors@R: c(person("Kaue", "de Sousa", email = "kaue.desousa@inn.no", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7571-7845")), person("Jacob", "van Etten", role = c("aut", "ctb"), comment = c(ORCID = "0000-0001-7554-2558")), person("Sam", "Dumble", role = c("aut", "ctb")), person("Brandon", "Madriz", role = c("aut","ctb")), person("Carlos", "Quiros", role = c("aut","ctb")))
Maintainer: Kaue de Sousa <kaue.desousa@inn.no>
URL: https://agrobioinfoservices.github.io/ClimMobTools/
BugReports: https://github.com/agrobioinfoservices/ClimMobTools/issues
Description: Toolkit for the 'ClimMob' platform in R. 'ClimMob' is an open source software for crowdsourcing citizen science in agriculture <https://climmob.net/climmob3/>. Developed by van Etten et al. (2019) <doi:10.1017/S0014479716000739>, it turns the research paradigm on its head; instead of a few researchers designing complicated trials to compare several technologies in search of the best solutions, it enables many farmers to carry out reasonably simple experiments that taken together can offer even more information. 'ClimMobTools' enables project managers to deep explore and analyse their 'ClimMob' data in R.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: httr, jsonlite, Matrix, methods, nasapower, PlackettLuce, raster, RSpectra, tibble, tidyr, utils
Suggests: psychotree, psychotools, qvcalc, knitr, rmarkdown, testthat (>= 2.1.0)
Language: en-GB
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-07 10:09:54 UTC; kaued
Author: Kaue de Sousa [aut, cre] (<https://orcid.org/0000-0002-7571-7845>), Jacob van Etten [aut, ctb] (<https://orcid.org/0000-0001-7554-2558>), Sam Dumble [aut, ctb], Brandon Madriz [aut, ctb], Carlos Quiros [aut, ctb]
Repository: CRAN
Date/Publication: 2019-08-07 16:00:02 UTC

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New package featuretoolsR with initial version 0.4.3
Package: featuretoolsR
Type: Package
Title: Interact with the 'Python' Module 'Featuretools'
Version: 0.4.3
Authors@R: person("Magnus", "Furugård", email = "magnus.furugard@gmail.com", role = c("aut", "cre"))
Maintainer: Magnus Furugård <magnus.furugard@gmail.com>
Description: A 'reticulate'-based interface to the 'Python' module 'Featuretools'. The package grants functionality to interact with 'Pythons' 'Featuretools' module, which allows for automated feature engineering on any data frame. Valid features and new data sets can, after feature synthesis, easily be extracted.
License: MIT + file LICENSE
URL: https://github.com/magnusfurugard/featuretoolsR
BugReports: https://github.com/magnusfurugard/featuretoolsR/issues
Depends: R (>= 3.4.2)
Imports: reticulate, caret, dplyr, purrr, stringr, tibble, magrittr, cli, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-06 15:48:38 UTC; Magnus
Author: Magnus Furugård [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-07 08:40:02 UTC

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New package rapbase with initial version 1.10.0
Package: rapbase
Type: Package
Title: Base Functions and Resources for Rapporteket
Version: 1.10.0
Date: 2019-07-23
Authors@R: c( person(given = "Are", family = "Edvardsen", role = c("aut", "cre"), email = "biorakel@gmail.com", comment = c(ORCID = "0000-0002-5210-3656")), person(given = "Kevin Otto", family = "Thon", role = c("aut"), email = "kevin.thon@helse-nord.no"))
Maintainer: Are Edvardsen <biorakel@gmail.com>
Description: Provide common functions and resources for registry specific R-packages at Rapporteket <https://rapporteket.github.io/rapporteket/articles/short_introduction.html>. This package is relevant for developers of packages/registries at Rapporteket.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: DBI, devtools, digest, gistr, httr, knitr, magrittr, readr, RJDBC, RMariaDB, sendmailR, shiny, utils, yaml
RoxygenNote: 6.1.1
URL: http://github.com/Rapporteket/rapbase
BugReports: http://github.com/Rapporteket/rapbase/issues
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-08-06 08:56:24 UTC; rstudio
Author: Are Edvardsen [aut, cre] (<https://orcid.org/0000-0002-5210-3656>), Kevin Otto Thon [aut]
Repository: CRAN
Date/Publication: 2019-08-07 07:30:02 UTC

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New package planets with initial version 0.1.0
Package: planets
Title: Simple and Accessible Data from all Known Planets
Version: 0.1.0
Authors@R: person(given = "Alejandro", family = "Jiménez Rico", role = c("aut", "cre"), email = "aljrico@gmail.com")
Description: The goal of 'planets' is to provide of very simple and accessible data containing basic information from all known planets.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2019-08-06 11:29:40 UTC; alejandro
Author: Alejandro Jiménez Rico [aut, cre]
Maintainer: Alejandro Jiménez Rico <aljrico@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-07 07:40:02 UTC

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New package TrendSLR with initial version 1.0
Package: TrendSLR
Type: Package
Title: Estimating Trend, Velocity and Acceleration from Sea Level Records
Version: 1.0
Depends: R (>= 3.2.2)
Date: 2019-08-05
Description: Analysis of annual average ocean water level time series, providing improved estimates of trend (mean sea level) and associated real-time velocities and accelerations. Improved trend estimates are based on singular spectrum analysis methods. Various gap-filling options are included to accommodate incomplete time series records. The package also includes a range of diagnostic tools to inspect the components comprising the original time series which enables expert interpretation and selection of likely trend components. A wide range of screen and plot to file options are available in the package.
Author: Phil J Watson <philwatson.slr@gmail.com>
Maintainer: Phil J Watson <philwatson.slr@gmail.com>
License: GPL (>= 3)
LazyData: TRUE
Imports: changepoint (>= 2.1.1), forecast (>= 6.2), plyr (>= 1.8.3), Rssa (>= 0.13-1), tseries (>= 0.10-34), zoo (>= 1.7-12), imputeTS (>= 1.8)
Repository: CRAN
NeedsCompilation: no
RoxygenNote: 6.1.1
Packaged: 2019-08-06 01:16:31 UTC; tiara
Date/Publication: 2019-08-07 05:00:03 UTC

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New package hwordcloud with initial version 0.1.0
Package: hwordcloud
Type: Package
Title: Rendering Word Clouds
Version: 0.1.0
Authors@R: person(given = "Zhenxing", family = "Cheng", email = "czxjnu@163.com", role = c("aut", "cre"))
Description: Provides a way to display word clouds in R. The word cloud is a html widget, so you can use it in interactive documents and 'shiny' applications.
License: MIT + file LICENSE
Date: 2019-08-05
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.0.0)
URL: https://github.com/czxa/hwordcloud
BugReports: https://github.com/czxa/hwordcloud/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Imports: htmlwidgets, wordcloud2, shiny, colourpicker
NeedsCompilation: no
Packaged: 2019-08-05 23:28:24 UTC; czx
Author: Zhenxing Cheng [aut, cre]
Maintainer: Zhenxing Cheng <czxjnu@163.com>
Repository: CRAN
Date/Publication: 2019-08-07 04:50:02 UTC

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Tue, 06 Aug 2019

New package PupilPre with initial version 0.6.0
Package: PupilPre
Type: Package
Title: Preprocessing Pupil Size Data
Version: 0.6.0
Date: 2019-08-04
Authors@R: c(person("Aki-Juhani", "Kyröläinen", role = c("aut", "cre"), email = "akkyro@gmail.com"), person("Vincent", "Porretta", role = "aut"), person("Jacolien", "van Rij", role = "ctb"), person("Juhani", "Järvikivi", role = "ctb"))
Author: Aki-Juhani Kyröläinen [aut, cre], Vincent Porretta [aut], Jacolien van Rij [ctb], Juhani Järvikivi [ctb]
Maintainer: Aki-Juhani Kyröläinen <akkyro@gmail.com>
Description: Pupillometric data collected using SR Research Eyelink eye trackers requires significant preprocessing. This package contains functions for preparing pupil dilation data for visualization and statistical analysis. Specifically, it provides a pipeline of functions which aid in data validation, the removal of blinks/artifacts, downsampling, and baselining, among others. Additionally, plotting functions for creating grand average and conditional average plots are provided. See the vignette for samples of the functionality. The package is designed for handling data collected with SR Research Eyelink eye trackers using Sample Reports created in SR Research Data Viewer.
Depends: R (>= 3.5.0), dplyr (>= 0.8.0), rlang (>= 0.1.1), VWPre (>= 1.2.0)
Imports: ggplot2 (>= 2.2.0), mgcv (>= 1.8-16), shiny (>= 0.14.2), tidyr (>= 0.6.0), stats (>= 3.3.2), robustbase (>= 0.93-3), zoo (>= 1.8-4), signal (>= 0.7-6)
License: GPL-3
LazyData: true
Suggests: knitr, rmarkdown, gridExtra
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-04 19:21:51 UTC; vjp
Repository: CRAN
Date/Publication: 2019-08-06 09:10:05 UTC

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New package flightplanning with initial version 0.7.2
Package: flightplanning
Type: Package
Title: UAV Flight Planning
Version: 0.7.2
Authors@R: c( person("Caio", "Hamamura", email = "caiohamamura@gmail.com", role = c("aut", "cre")), person("Danilo Roberti Alves de", "Almeida", email = "daniloflorestas@gmail.com", role = c("aut")), person("Daniel de Almeida", "Papa", email = "daniel.papa@embrapa.br", role = c("aut")), person("Hudson Franklin Pessoa", "Veras", email = "hudson@engeverde.com", role = c("aut")), person("Evandro Orfanó", "Figueiredo", email = "evandro.figueiredo@embrapa.br", role = c("aut")))
Description: Utility functions for creating flight plans for unmanned aerial vehicles (UAV), specially for the Litchi Hub platform. It calculates the flight and camera settings based on the camera specifications, exporting the flight plan CSV format ready to import into Litchi Hub.
Imports: graphics, grDevices, methods, rgdal, rgeos, sp
Depends: R (>= 3.0)
Suggests: testthat
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/caiohamamura/flightplanning-R.git
BugReports: https://github.com/caiohamamura/flightplanning-R/issues
Author: Caio Hamamura [aut, cre], Danilo Roberti Alves de Almeida [aut], Daniel de Almeida Papa [aut], Hudson Franklin Pessoa Veras [aut], Evandro Orfanó Figueiredo [aut]
Maintainer: Caio Hamamura <caiohamamura@gmail.com>
Repository: CRAN
Repository/R-Forge/Project: flightplanning
Repository/R-Forge/Revision: 8
Repository/R-Forge/DateTimeStamp: 2019-08-01 22:51:09
Date/Publication: 2019-08-06 09:20:02 UTC
NeedsCompilation: no
Packaged: 2019-08-01 23:10:13 UTC; rforge

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New package flamingos with initial version 0.1.0
Type: Package
Package: flamingos
Title: Functional Latent Data Models for Clustering Heterogeneous Curves ('FLaMingos')
Version: 0.1.0
Authors@R: c(person("Faicel", "Chamroukhi", role = c("aut"), email = "faicel.chamroukhi@unicaen.fr", comment = c(ORCID = "0000-0002-5894-3103")), 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 variety of original and flexible user-friendly statistical latent variable models for the simultaneous clustering and segmentation of heterogeneous functional data (i.e time series, or more generally longitudinal data, fitted by unsupervised algorithms, including EM algorithms. Functional Latent Data Models for Clustering heterogeneous curves ('FLaMingos') are originally introduced and written in 'Matlab' by Faicel Chamroukhi <https://github.com/fchamroukhi?utf8=?&tab=repositories&q=mix&type=public&language=matlab>. The references are mainly the following ones. Chamroukhi F. (2010) <https://chamroukhi.com/FChamroukhi-PhD.pdf>. Chamroukhi F., Same A., Govaert, G. and Aknin P. (2010) <doi:10.1016/j.neucom.2009.12.023>. Chamroukhi F., Same A., Aknin P. and Govaert G. (2011). <doi:10.1109/IJCNN.2011.6033590>. Same A., Chamroukhi F., Govaert G. and Aknin, P. (2011) <doi:10.1007/s11634-011-0096-5>. Chamroukhi F., and Glotin H. (2012) <doi:10.1109/IJCNN.2012.6252818>. Chamroukhi F., Glotin H. and Same A. (2013) <doi:10.1016/j.neucom.2012.10.030>. Chamroukhi F. (2015) <https://chamroukhi.com/FChamroukhi-HDR.pdf>. Chamroukhi F. and Nguyen H-D. (2019) <doi:10.1002/widm.1298>.
URL: https://github.com/fchamroukhi/FLaMingos
BugReports: https://github.com/fchamroukhi/FLaMingos/issues
License: GPL (>= 3)
Depends: R (>= 2.10)
Imports: methods, stats, Rcpp
Suggests: knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
Collate: flamingos-package.R RcppExports.R utils.R kmeans.R mkStochastic.R FData.R ParamMixHMM.R ParamMixHMMR.R ParamMixRHLP.R StatMixHMM.R StatMixHMMR.R StatMixRHLP.R ModelMixHMMR.R ModelMixHMM.R ModelMixRHLP.R emMixHMM.R emMixHMMR.R emMixRHLP.R cemMixRHLP.R data-toydataset.R
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-08-05 19:08:18 UTC; lecocq191
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: 2019-08-06 09:30:02 UTC

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New package cvcqv with initial version 1.0.0
Package: cvcqv
Type: Package
Title: Coefficient of Variation (CV) with Confidence Intervals (CI)
Version: 1.0.0
Date: 2019-08-01
Authors@R: person("Maani", "Beigy", email = "manibeygi@gmail.com", role = c("aut", "cre"))
Maintainer: Maani Beigy <manibeygi@gmail.com>
Description: Provides some easy-to-use functions and classes to calculate variability measures such as coefficient of variation with confidence intervals provided with all available methods. References are Panichkitkosolkul (2013) <doi:10.1155/2013/324940> , Altunkaynak & Gamgam (2018) <doi:10.1080/03610918.2018.1435800> , Albatineh, Kibria, Wilcox & Zogheib (2014) <doi:10.1080/02664763.2013.847405> .
Depends: R (>= 3.1.2), dplyr (>= 0.8.0.1)
Imports: R6, SciViews, boot, MBESS
Suggests: testthat, knitr, rmarkdown, covr
VignetteBuilder: knitr
URL: https://github.com/MaaniBeigy/cvcqv
BugReports: https://github.com/MaaniBeigy/cvcqv/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-05 20:22:41 UTC; maanib
Author: Maani Beigy [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-06 09:30:06 UTC

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New package correlationfunnel with initial version 0.1.0
Package: correlationfunnel
Type: Package
Title: Speed Up Exploratory Data Analysis (EDA) with the Correlation Funnel
Version: 0.1.0
Authors@R: person("Matt", "Dancho", email = "mdancho@business-science.io", role = c("aut", "cre"))
Description: Speeds up exploratory data analysis (EDA) by providing a succinct workflow and interactive visualization tools for understanding which features have relationships to target (response). Uses binary correlation analysis to determine relationship. Default correlation method is the Pearson method. Lian Duan, W Nick Street, Yanchi Liu, Songhua Xu, and Brook Wu (2014) <doi:10.1145/2637484>.
URL: https://github.com/business-science/correlationfunnel
BugReports: https://github.com/business-science/correlationfunnel/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1)
Imports: ggplot2, rlang, recipes, magrittr, plotly, tibble, dplyr, tidyr, stats, utils, ggrepel, stringr, forcats, purrr, cli, crayon, rstudioapi
Suggests: scales, knitr, rmarkdown, covr, lubridate, testthat (>= 2.1.0)
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-05 19:40:15 UTC; mdancho
Author: Matt Dancho [aut, cre]
Maintainer: Matt Dancho <mdancho@business-science.io>
Repository: CRAN
Date/Publication: 2019-08-06 09:30:09 UTC

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New package cat.dt with initial version 0.1.0
Package: cat.dt
Type: Package
Title: Computerized Adaptive Testing and Decision Trees
Version: 0.1.0
Imports: Rglpk, Matrix
Authors@R: c(person("Javier", "Rodriguez-Cuadrado",, role = c("aut", "cre"), email = "javierro@est-econ.uc3m.es"), person("Juan C.", "Laria",, role = c("aut"), email = "juancarlos.laria@uc3m.es"), person("David", "Delgado-Gomez",, role = "aut", "ths"))
Description: Implements the Merged Tree-CAT method to generate Computerized Adaptive Tests (CATs) based on a decision tree. The tree growth is controlled by merging branches with similar trait distributions and estimations. This package has the necessary tools for creating CATs and estimate the subject's ability level. The Merged Tree-CAT method is an extension of the Tree-CAT method (see Delgado-Gómez et al., 2019 <doi:10.1016/j.eswa.2018.09.052>).
URL: https://github.com/jlaria/cat.dt
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-05 15:57:46 UTC; user
Author: Javier Rodriguez-Cuadrado [aut, cre], Juan C. Laria [aut], David Delgado-Gomez [aut]
Maintainer: Javier Rodriguez-Cuadrado <javierro@est-econ.uc3m.es>
Repository: CRAN
Date/Publication: 2019-08-06 09:00:08 UTC

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Mon, 05 Aug 2019

New package valueEQ5D with initial version 0.4.3
Package: valueEQ5D
Type: Package
Title: Scoring the EQ-5D Descriptive System
Version: 0.4.3
Authors@R: c(person("Sheeja", "Manchira Krishnan", , "sheejamk@gmail.com", c("aut", "cre")))
Maintainer: Sheeja Manchira Krishnan <sheejamk@gmail.com>
Depends: R (>= 2.10)
Description: EQ-5D is a standard instrument (<https://euroqol.org/eq-5d-instruments/>) that measures the quality of life often used in clinical and economic evaluations of health care technologies. Both adult versions of EQ-5D (EQ-5D-3L and EQ-5D-5L) contain a descriptive system and visual analog scale. The descriptive system measures the patient's health in 5 dimensions: the 5L versions has 5 levels and 3L version has 3 levels. The descriptive system scores are usually converted to index values using country specific values sets (that incorporates the country preferences). This package allows the calculation of both descriptive system scores to the index value scores. The value sets for EQ-5D-3L are from the references mentioned in the website <https://euroqol.org/eq-5d-instruments/eq-5d-3l-about/valuation/> The value sets for EQ-5D-3L for a total of 31 countries are used for the valuation (see the user guide for a complete list of references). The value sets for EQ-5D-5L are obtained from references mentioned in the <https://euroqol.org/eq-5d-instruments/eq-5d-5l-about/valuation-standard-value-sets/> and other sources. The value sets for EQ-5D-5L for a total of 17 countries are used for the valuation (see the user guide for a complete list of references). The package can also be used to map 5L scores to 3L index values for 10 countries: Denmark, France, Germany, Japan, Netherlands, Spain, Thailand, UK, USA, and Zimbabwe. The value set and method for mapping are obtained from Van Hout et al (2012) <doi: 10.1016/j.jval.2012.02.008>.
License: GNU General Public License
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: rstudioapi, testthat, utils, dplyr, stringr
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-05 15:07:44 UTC; smk543
Author: Sheeja Manchira Krishnan [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-05 16:10:03 UTC

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New package GillespieSSA2 with initial version 0.2.4
Package: GillespieSSA2
Type: Package
Title: Gillespie's Stochastic Simulation Algorithm for Impatient People
Version: 0.2.4
Authors@R: c( person( "Robrecht", "Cannoodt", email = "rcannood@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3641-729X") ) )
Description: A fast, scalable, and versatile framework for simulating large systems with Gillespie's Stochastic Simulation Algorithm ('SSA'). This package is the spiritual successor to the 'GillespieSSA' package originally written by Mario Pineda-Krch. Benefits of this package include major speed improvements (>100x), easier to understand documentation, and many unit tests that try to ensure the package works as intended.
License: GPL (>= 3)
LazyData: TRUE
Depends: R (>= 3.0)
Imports: assertthat, dplyr, dynutils, Matrix, methods, purrr, Rcpp (>= 0.12.3), readr, rlang, stringr, tidyr
Suggests: ggplot2, GillespieSSA, knitr, rmarkdown, testthat (>= 2.1.0)
LinkingTo: Rcpp
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-08-05 14:21:48 UTC; rcannood
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-05 16:20:02 UTC

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New package arrow with initial version 0.14.1
Package: arrow
Title: Integration to 'Apache' 'Arrow'
Version: 0.14.1
Authors@R: c( person("Romain", "Fran\u00e7ois", email = "romain@rstudio.com", role = c("aut"), comment = c(ORCID = "0000-0002-2444-4226")), person("Jeroen", "Ooms", email = "jeroen@berkeley.edu", role = c("aut")), person("Neal", "Richardson", email = "neal@ursalabs.org", role = c("aut", "cre")), person("Javier", "Luraschi", email = "javier@rstudio.com", role = c("ctb")), person("Jeffrey", "Wong", email = "jeffreyw@netflix.com", role = c("ctb")), person("Apache Arrow", email = "dev@arrow.apache.org", role = c("aut", "cph")) )
Description: 'Apache' 'Arrow' <https://arrow.apache.org/> is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. This package provides an interface to the 'Arrow C++' library.
Depends: R (>= 3.1)
License: Apache License (>= 2.0)
URL: https://github.com/apache/arrow/
BugReports: https://issues.apache.org/jira/projects/ARROW/issues
Encoding: UTF-8
Language: en-US
LazyData: true
SystemRequirements: C++11
Biarch: true
LinkingTo: Rcpp (>= 1.0.1)
Imports: assertthat, bit64, fs, purrr, R6, Rcpp (>= 1.0.1), rlang, tidyselect, utils
RoxygenNote: 6.1.1
Suggests: covr, hms, lubridate, pkgdown, rmarkdown, roxygen2, testthat, tibble, vctrs
Collate: 'enums.R' 'R6.R' 'ArrayData.R' 'ChunkedArray.R' 'Column.R' 'Field.R' 'List.R' 'RecordBatch.R' 'RecordBatchReader.R' 'RecordBatchWriter.R' 'Schema.R' 'Struct.R' 'Table.R' 'array.R' 'arrow-package.R' 'arrowExports.R' 'buffer.R' 'io.R' 'compression.R' 'compute.R' 'csv.R' 'dictionary.R' 'feather.R' 'install-arrow.R' 'json.R' 'memory_pool.R' 'message.R' 'parquet.R' 'read_record_batch.R' 'read_table.R' 'reexports-bit64.R' 'reexports-tidyselect.R' 'write_arrow.R'
NeedsCompilation: yes
Packaged: 2019-08-01 15:11:24 UTC; enpiar
Author: Romain François [aut] (<https://orcid.org/0000-0002-2444-4226>), Jeroen Ooms [aut], Neal Richardson [aut, cre], Javier Luraschi [ctb], Jeffrey Wong [ctb], Apache Arrow [aut, cph]
Maintainer: Neal Richardson <neal@ursalabs.org>
Repository: CRAN
Date/Publication: 2019-08-05 16:10:10 UTC

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New package rTorch with initial version 0.0.3
Package: rTorch
Title: R Bindings to 'PyTorch'
Version: 0.0.3
Authors@R: c( person("Alfonso R.", "Reyes", role = c("aut", "cre", "cph"), email = "alfonso.reyes@oilgainsanalytics.com"), person("Daniel", "Falbel", role = c("ctb", "cph"), email = "daniel@rstudio.com"), person("JJ", "Allaire", role = c("ctb", "cph")) )
Description: 'R' implementation and interface of the Machine Learning platform 'PyTorch' <https://pytorch.org/> developed in 'Python'. It requires a 'conda' environment with 'torch' and 'torchvision' to provide 'PyTorch' functions, methods and classes. The key object in 'PyTorch' is the tensor which is in essence a multidimensional array. These tensors are fairly flexible to perform calculations in CPUs as well as 'GPUs' to accelerate the process.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1)
Imports: logging, reticulate, jsonlite (>= 1.2), utils, methods, R6, rstudioapi (>= 0.7), data.table
Suggests: testthat, knitr, rmarkdown
SystemRequirements: PyTorch (https://pytorch.org/)
RoxygenNote: 6.1.1
URL: https://github.com/f0nzie/rTorch
NeedsCompilation: no
Packaged: 2019-08-02 18:18:38 UTC; msfz751
Author: Alfonso R. Reyes [aut, cre, cph], Daniel Falbel [ctb, cph], JJ Allaire [ctb, cph]
Maintainer: Alfonso R. Reyes <alfonso.reyes@oilgainsanalytics.com>
Repository: CRAN
Date/Publication: 2019-08-05 15:40:03 UTC

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New package projmgr with initial version 0.1.0
Package: projmgr
Title: Task Tracking and Project Management with GitHub
Version: 0.1.0
Authors@R: person(given = "Emily", family = "Riederer", role = c("cre", "aut"), email = "emilyriederer@gmail.com")
Description: Provides programmatic access to 'GitHub' API with a focus on project management. Key functionality includes setting up issues and milestones from R objects or 'YAML' configurations, querying outstanding or completed tasks, and generating progress updates in tables, charts, and RMarkdown reports. Useful for those using 'GitHub' in personal, professional, or academic settings with an emphasis on streamlining the workflow of data analysis projects.
License: MIT + file LICENSE
URL: https://github.com/emilyriederer/projmgr
BugReports: https://github.com/emilyriederer/projmgr/issues
Depends: R (>= 3.1.2)
Imports: gh, magrittr
Suggests: clipr, curl, dplyr, ggplot2, knitr, purrr, reprex, rmarkdown, testthat, tidyr, yaml, htmltools, httr, covr
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-20 19:12:56 UTC; emily
Author: Emily Riederer [cre, aut]
Maintainer: Emily Riederer <emilyriederer@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-05 15:40:06 UTC

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New package mlr3learners with initial version 0.1.1
Package: mlr3learners
Title: Recommended Learners for 'mlr3'
Version: 0.1.1
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 = "Quay", family = "Au", role = "aut", email = "quayau@gmail.com", comment = c(ORCID = "0000-0002-5252-8902")), person(given = "Stefan", family = "Coors", role = "aut", email = "mail@stefancoors.de", comment = c(ORCID = "0000-0002-7465-2146")))
Description: Recommended Learners for 'mlr3'. Extends 'mlr3' with interfaces to essential machine learning packages on CRAN. This includes, but is not limited to: (penalized) linear and logistic regression, linear and quadratic discriminant analysis, k-nearest neighbors, naive Bayes, support vector machines, and gradient boosting.
License: LGPL-3
URL: https://mlr3learners.mlr-org.com
BugReports: https://github.com/mlr-org/mlr3learners/issues
Depends: R (>= 3.1.0)
Imports: data.table, mlr3 (>= 0.1.1), mlr3misc, paradox, R6
Suggests: checkmate, DiceKriging, e1071, glmnet, kknn, lgr, MASS, ranger, testthat, withr, xgboost
Encoding: UTF-8
NeedsCompilation: no
RoxygenNote: 6.1.1
Packaged: 2019-07-29 07:57:47 UTC; lang
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Quay Au [aut] (<https://orcid.org/0000-0002-5252-8902>), Stefan Coors [aut] (<https://orcid.org/0000-0002-7465-2146>)
Maintainer: Michel Lang <michellang@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-05 15:30:02 UTC

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New package kStatistics with initial version 1.0
Package: kStatistics
Type: Package
Title: Unbiased Estimators for Cumulant Products
Version: 1.0
Date: 2019-07-20
Author: Elvira Di Nardo <elvira.dinardo@unito.it>, Giuseppe Guarino <giuseppe.guarino@rete.basilicata.it>
Maintainer: Giuseppe Guarino <giuseppe.guarino@rete.basilicata.it>
Description: Methods and tools for estimate (joint) cumulants of a given population distribution using (multivariate) k-statistics and (multivariate) polykays,symmetric unbiased estimators with minimum variance. For more details see Di Nardo E., Guarino G., Senato D. (2009) <arXiv:0807.5008>.
License: GPL
NeedsCompilation: no
Packaged: 2019-08-05 14:24:55 UTC; giuseppe.guarino
Repository: CRAN
Date/Publication: 2019-08-05 15:10:02 UTC

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New package importinegi with initial version 1.0.0
Package: importinegi
Title: Download and Manage Open Data from INEGI
Version: 1.0.0
Authors@R: person("Cesar", "Renteria", email = "crenteria@albany.edu", role = c("aut", "cre"))
Author: Cesar Renteria [aut, cre]
Maintainer: Cesar Renteria <crenteria@albany.edu>
Description: Download and manage data sets of statistical projects and geographic data created by Instituto Nacional de Estadistica y Geografia (INEGI). See <https://www.inegi.org.mx/>.
BugReports: https://github.com/crenteriam/importinegi/issues
Depends: R (>= 3.3.0)
License: CC0
Encoding: UTF-8
LazyData: true
Imports: foreign, dplyr, haven, rgdal, data.table
Suggests: tidyverse, knitr, rmarkdown, testthat (>= 2.1.0)
Language: es
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-04 17:29:17 UTC; rente
Repository: CRAN
Date/Publication: 2019-08-05 15:40:10 UTC

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New package golem with initial version 0.1
Package: golem
Title: A Framework for Robust Shiny Applications
Version: 0.1
Authors@R: c(person(given = "Vincent", family = "Guyader", role = c("cre", "aut"), email = "vincent@thinkr.fr", comment = c(ORCID = "0000-0003-0671-9270")), person(given = "Colin", family = "Fay", role = "aut", email = "contact@colinfay.me", comment = c(ORCID = "0000-0001-7343-1846")), person(given = "Sébastien", family = "Rochette", role = "aut", email = "sebastien@thinkr.fr", comment = c(ORCID = "0000-0002-1565-9313")), person(given = "Cervan", family = "Girard", role = "aut", email = "cervan@thinkr.fr", comment = c(ORCID = "0000-0002-4816-4624")), person(given = "ThinkR", role = "cph"))
Description: An opinionated framework for building a production-ready 'Shiny' application. This package contains a series of tools for building a robust 'Shiny' application from start to finish.
License: MIT + file LICENSE
URL: https://github.com/ThinkR-open/golem
BugReports: https://github.com/ThinkR-open/golem/issues
Depends: R (>= 3.0)
Imports: attempt, cli, crayon, desc, dockerfiler, DT, glue, htmltools, pkgload, processx, remotes, rlang, roxygen2, rsconnect, rstudioapi, shiny, stats, stringr, testthat, tools, usethis, utils, yesno
Suggests: covr, knitr, pkgdown, purrr, rcmdcheck, rmarkdown, withr
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-19 09:00:08 UTC; Vincent
Author: Vincent Guyader [cre, aut] (<https://orcid.org/0000-0003-0671-9270>), Colin Fay [aut] (<https://orcid.org/0000-0001-7343-1846>), Sébastien Rochette [aut] (<https://orcid.org/0000-0002-1565-9313>), Cervan Girard [aut] (<https://orcid.org/0000-0002-4816-4624>), ThinkR [cph]
Maintainer: Vincent Guyader <vincent@thinkr.fr>
Repository: CRAN
Date/Publication: 2019-08-05 15:50:02 UTC

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New package sccr with initial version 1.0
Package: sccr
Type: Package
Title: The Self-Consistent, Competing Risks (SC-CR) Algorithms
Version: 1.0
Date: 2019-07-23
Author: Peter Adamek, Alicja Wolny-Dominiak
Maintainer: Alicja Wolny-Dominiak<woali@ue.katowice.pl>
Description: An algorithm for producing fully non-parametric and self-consistent estimators of the cause-specific failure probabilities in the presence of interval-censoring data. See Adamic P., Caron S. (2014) <doi:10.1080/03461238.2012.693457>, Adamic P., Dixon S., Gillis D. (2010) <doi:10.1080/03461230903134780>, Turnbull B. (1976) <doi:10.1111/j.2517-6161.1976.tb01597.x>.
Imports: dplyr
License: GPL-2
NeedsCompilation: no
Packaged: 2019-08-05 11:06:50 UTC; Woali
Repository: CRAN
Date/Publication: 2019-08-05 14:50:02 UTC

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New package LPRelevance with initial version 1.0
Package: LPRelevance
Type: Package
Title: Relevance-Integrated Statistical Inference Engine
Version: 1.0
Date: 2019-07-08
Author: Subhadeep Mukhopadhyay, Kaijun Wang
Maintainer: Kaijun Wang <kaijunwang.19@gmail.com>
Description: A framework of methods to perform customized inference at individual level by taking contextual covariates into account. Three main functions are provided in this package: (i) LASER(): it generates specially-designed artificial relevant samples for a given case; (ii) g2l.proc(): computes customized fdr(z|x); and (iii) rEB.proc(): performs empirical Bayes inference based on LASERs. The details can be found in Mukhopadhyay, S., and Wang, K (2019, Technical Report).
Imports: leaps,locfdr,Bolstad2,reshape2,ggplot2,polynom
Depends: R (>= 3.5.0), stats, BayesGOF
License: GPL-2
NeedsCompilation: no
Packaged: 2019-08-04 03:44:15 UTC; AquinasUnit
Repository: CRAN
Date/Publication: 2019-08-05 14:10:09 UTC

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New package kofdata with initial version 0.1.3.3
Package: kofdata
Type: Package
Version: 0.1.3.3
Title: Get Data from the 'KOF Datenservice' API
Description: Read Swiss time series data from the 'KOF Datenservice' API, <https://datenservice.kof.ethz.ch>. The API provides macroeconomic survey data, business cycle and further macro economic time series about Switzerland. The package itself is a set of wrappers around the 'KOF Datenservice' API. The 'kofdata' package is able to consume public information as well as data that requires an API token.
Authors@R: c( person("Matthias", "Bannert", , "bannert@kof.ethz.ch", c("aut", "cre")), person("Severin", "Thoeni", , "thoenis@kof.ethz.ch", "aut"))
Depends: R (>= 3.0.0), jsonlite (>= 1.1), httr
Imports: xts, zoo
URL: https://github.com/KOF-ch/kofdata
BugReports: https://github.com/KOF-ch/kofdata/issues
Date: 2019-08-05
License: GPL-2
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-08-05 12:51:31 UTC; mbannert
Author: Matthias Bannert [aut, cre], Severin Thoeni [aut]
Maintainer: Matthias Bannert <bannert@kof.ethz.ch>
Repository: CRAN
Date/Publication: 2019-08-05 14:40:02 UTC

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New package wyz.code.testthat with initial version 1.1.5
Package: wyz.code.testthat
Type: Package
Title: Wizardry Code Offensive Programming Test Generation
Version: 1.1.5
Author: Fabien Gelineau <neonira@gmail.com>
Maintainer: Fabien Gelineau <neonira@gmail.com>
Description: Allows to generate automatically 'testthat' code files from offensive programming test cases. Generated test files are complete and ready to run. Using 'wyz.code.testthat' you will earn a lot of time, reduce the number of errors in test case production, be able to test immediately generated files without any need to view or modify them, and enter a zero time latency between code implementation and industrial testing. As with 'testthat', you may complete provided test cases according to your needs to push testing further, but this need is nearly void when using 'wyz.code.offensiveProgramming'. Refer to chapter 9 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 (>= 1.1.7)
Suggests: testthat, knitr, rmarkdown, DT (>= 0.5)
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-03 14:59:55 UTC; fgelineau
Repository: CRAN
Date/Publication: 2019-08-05 13:10:02 UTC

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New package tensorsparse with initial version 1.0
Package: tensorsparse
Type: Package
Title: Multiway Clustering via Tensor Block Models
Version: 1.0
Date: 2019-08-02
Author: Miaoyan Wang, Yuchen Zeng
Maintainer: Yuchen Zeng <yzeng58@wisc.edu>
Depends: glasso
Imports: fields, glmnet, rgl, reshape, mvtnorm, HDCI, clues, parallel, RColorBrewer, viridis, rTensor, methods
Description: Implements the multiway sparse clustering approach of Zeng and Wang (2019) <arXiv:1906.03807>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-08-04 01:06:40 UTC; cengyuchen
Repository: CRAN
Date/Publication: 2019-08-05 13:40:02 UTC
RoxygenNote: 6.1.1
Encoding: UTF-8

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New package slga with initial version 1.1.0
Package: slga
Type: Package
Title: Data Access Tools for the Soil and Landscape Grid of Australia
Version: 1.1.0
Date: 2019-08-03
Authors@R: c( person("Lauren", "O'Brien", email = "obrlsoilau@gmail.com", role = c('aut', 'cre')), person("Ross", "Searle", email = "ross.searle@csiro.au", role = c('ant')))
Description: Provides access to soil and landscape grid of Australia raster datasets via existing open geospatial consortium web coverage services. See <http://www.csiro.au/soil-and-landscape-grid>.
License: MIT + file LICENSE
Depends: R (>= 2.10)
Imports: httr, raster, sf, utils, xml2
Suggests: covr, knitr, pkgdown, rmarkdown, testthat
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/obrl-soil/slga
BugReports: https://github.com/obrl-soil/slga/issues
NeedsCompilation: no
Packaged: 2019-08-03 03:45:10 UTC; leobr
Author: Lauren O'Brien [aut, cre], Ross Searle [ant]
Maintainer: Lauren O'Brien <obrlsoilau@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-05 13:10:04 UTC

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New package MWright with initial version 0.3.0
Package: MWright
Type: Package
Title: Mainardi-Wright Family of Distributions
Version: 0.3.0
Author: Dexter Cahoy
Maintainer: Dexter Cahoy <dexter.cahoy@gmail.com>
Description: Implements random number generation, plotting, and estimation algorithms for the two-parameter one-sided and two-sided M-Wright (Mainardi-Wright) family. The M-Wright distributions naturally generalize widely used one-sided (Airy and half-normal or half-Gaussian) and symmetric (Airy and Gaussian or normal) models. These are widely studied in time-fractional differential equations. References: Cahoy and Minkabo (2017) <doi:10.3233/MAS-170388>; Cahoy (2012) <doi:10.1007/s00180-011-0269-x>; Cahoy (2012) <doi:10.1080/03610926.2010.543299>; Cahoy (2011); Mainardi, Mura, and Pagnini (2010) <doi:10.1155/2010/104505>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: stats, cubature
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-03 15:10:55 UTC; cahoyd
Repository: CRAN
Date/Publication: 2019-08-05 13:20:02 UTC

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New package imagefx with initial version 0.1.0
Package: imagefx
Type: Package
Title: Extract Features from Images
Version: 0.1.0
Author: Alex J.C. Witsil
Maintainer: Alex J.C. Witsil <alexjcwitsil@gmail.com>
Description: Synthesize images into characteristic features for time-series analysis or machine learning applications. The package was originally intended for monitoring volcanic eruptions in video data by highlighting and extracting regions above the vent associated with plume activity. However, the functions within are general and have wide applications for image processing, analyzing, filtering, and plotting.
Depends: R (>= 2.10)
Imports: moments
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-04 01:24:09 UTC; alex
Repository: CRAN
Date/Publication: 2019-08-05 13:40:05 UTC

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New package formulaic with initial version 0.0.1
Package: formulaic
Title: Create Formula
Version: 0.0.1
Authors@R: c( person("David", "Shilane", , "david.shilane@columbia.edu", c("aut")), person("Caffrey", "Lee", , "cl3802@columbia.edu", c("ctb")), person("Zichen", "Huang", , "zh2380@columbia.edu", c("ctb")), person("Anderson", "Nelson", , "an2908@columbia.edu", c("ctb","cre")) )
Description: Create a dynamic formula with multiple features. It not only diminishes the time required for modeling and implementing, but also enriches the quality of the result. Many statistical models and analyses in 'R' are implemented through formula objects. The 'formulaic' package creates a unified approach for programmatically and dynamically generating formula objects in 'R'. Users may specify the inputs and outcomes of a model directly, search for variables to include based upon naming patterns, and identify variables to exclude. A wide range of quality checks are implemented to identify issues such as misspecified variables, duplication, a lack of contrast in the inputs, and a large number of levels in categorical data. These issues are documented and reported in a manner that provides greater accountability and useful information to guide an investigators choices in selecting features.
Depends: R (>= 3.6.0)
URL: https://github.com/dachosen1/formulaic
BugReports: https://github.com/dachosen1/formulaic/issues
License: GPL-3
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 6.1.1
Imports: data.table, stats, DT
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-03 17:09:47 UTC; ander
Author: David Shilane [aut], Caffrey Lee [ctb], Zichen Huang [ctb], Anderson Nelson [ctb, cre]
Maintainer: Anderson Nelson <an2908@columbia.edu>
Repository: CRAN
Date/Publication: 2019-08-05 13:30:02 UTC

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New package FCSlib with initial version 1.0.0
Package: FCSlib
Type: Package
Title: A Collection of Fluorescence Fluctuation Spectroscopy Methods
Version: 1.0.0
Date: 2019-07-30
Author: Raul Pinto Camara, Adan Guerrero.
Maintainer: Raul Pinto Camara <vasto.lorde.rp@gmail.com>
Description: A set of tools for fluorescence fluctuation spectroscopy data analysis performance is provided in this package. It includes techniques such as single-point fluorescence correlation spectroscopy, autocorrelation and pair correlation functions, number & brightness (raster line scan) and a novel method recently developed by Hinde and co-workers, pair correlation of molecular brightness. A set of simulations and real experimental data is used for the examples of each function provided in this package. For an in-depth description of the basics behind each function here included and a detailed step-by-step guide on how to use them on your own data, please refer to the Supplementary Material file provided at (<https://github.com/RPintoC/FCSlib_Sup>). R.A. Migueles-Ramirez, A.G. Velasco-Felix, R. Pinto-Camara, C.D. Wood, A. Guerrero (2017, ISBN-13:978-84-942134-9-6). Hinde, E., Pandzic, E., Yang, Z., Ng, I. H., Jans, D. A., Bogoyevitch, M. A., Gratton, E. & Gaus, K. (2016) <doi:10.1038/ncomms11047>.
License: GPL-3
Depends: R(>= 3.5.0), tiff
Suggests: fields
RoxygenNote: 6.1.1
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-08-03 12:43:49 UTC; raul_
Repository: CRAN
Date/Publication: 2019-08-05 13:10:08 UTC

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New package seqgendiff with initial version 1.1.0
Package: seqgendiff
Type: Package
Title: RNA-Seq Generation/Modification for Simulation
Version: 1.1.0
Authors@R: person("David", "Gerard", email = "gerard.1787@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9450-5023"))
Description: Generates/modifies RNA-seq data for use in simulations. We provide a suite of functions that will add a known amount of signal to a real RNA-seq dataset. The advantage of using this approach over simulating under a theoretical distribution is that common/annoying aspects of the data are more preserved, giving a more realistic evaluation of your method. The main functions are select_counts(), thin_diff(), thin_lib(), thin_gene(), thin_2group(), thin_all(), and effective_cor().
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/dcgerard/seqgendiff
BugReports: http://github.com/dcgerard/seqgendiff/issues
RoxygenNote: 6.1.1
Suggests: covr, testthat, SummarizedExperiment, DESeq2, knitr, rmarkdown, airway, limma, qvalue, edgeR, optmatch
Imports: assertthat, irlba, sva, pdist, matchingR, clue, cate
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-02 15:20:00 UTC; dgerard
Author: David Gerard [aut, cre] (<https://orcid.org/0000-0001-9450-5023>)
Maintainer: David Gerard <gerard.1787@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-05 12:20:02 UTC

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New package sensemakr with initial version 0.1.2
Package: sensemakr
Type: Package
Title: Sensitivity Analysis Tools for OLS
Date: 2019-07-26
Version: 0.1.2
Authors@R: c( person("Carlos", "Cinelli", role = c("aut", "cre"), email = "carloscinelli@hotmail.com"), person("Chad", "Hazlett", role = "aut"), person("Aaron", "Rudkin", role = "ctb") )
Author: Carlos Cinelli [aut, cre], Chad Hazlett [aut], Aaron Rudkin [ctb]
Maintainer: Carlos Cinelli <carloscinelli@hotmail.com>
Description: Implements a suite of sensitivity analysis tools that extends the traditional omitted variable bias framework and makes it easier to understand the impact of omitted variables in regression models, as discussed in Cinelli and Hazlett (2018) <https://www.researchgate.net/publication/322509816_Making_Sense_of_Sensitivity_Extending_Omitted_Variable_Bias>.
URL: https://github.com/chadhazlett/sensemakr
BugReports: https://github.com/chadhazlett/sensemakr/issues
License: GPL-3
Depends: R (>= 3.1.0)
Encoding: UTF-8
RoxygenNote: 6.1.1
Suggests: testthat, covr
LazyData: true
NeedsCompilation: no
Packaged: 2019-08-02 21:42:38 UTC; carloscinelli
Repository: CRAN
Date/Publication: 2019-08-05 12:50:02 UTC

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New package SemNeT with initial version 1.0.0
Package: SemNeT
Title: Methods and Measures for Semantic Network Analysis
Version: 1.0.0
Date: 2019-07-31
Authors@R: c(person("Alexander P.", "Christensen", email = "alexpaulchristensen@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9798-7037")), person("Yoed N.", "Kenett", role = c("aut", "ctb"), comment = c(ORCID = "0000-0003-3872-7689")))
Maintainer: Alexander P. Christensen <alexpaulchristensen@gmail.com>
Description: Implements several functions for the analysis of semantic networks including partial node bootstrapping (Kenett, Anaki, & Faust, 2014 <doi:10.3389/fnhum.2014.00407>), random walk simulation (Kenett & Austerweil, 2016 <http://alab.psych.wisc.edu/papers/files/Kenett16CreativityRW.pdf>), and a function to compute global network measures. Significance tests and plotting features are also implemented.
Depends: R (>= 3.5.0)
License: GPL (>= 3.0)
Encoding: UTF-8
LazyData: true
Imports: lsa, foreach, parallel, doParallel, pbapply, NetworkToolbox, SemNetCleaner, dplyr, plyr, RColorBrewer, purrr, magrittr, ggplot2, grid, igraph, qgraph, networktools
URL: https://github.com/AlexChristensen/SemNeT
BugReports: https://github.com/AlexChristensen/SemNeT/issues
NeedsCompilation: no
RoxygenNote: 6.1.1
Packaged: 2019-08-02 18:25:21 UTC; APCHRIST
Author: Alexander P. Christensen [aut, cre] (<https://orcid.org/0000-0002-9798-7037>), Yoed N. Kenett [aut, ctb] (<https://orcid.org/0000-0003-3872-7689>)
Repository: CRAN
Date/Publication: 2019-08-05 12:20:06 UTC

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New package dssd with initial version 0.1.0
Package: dssd
Imports: sf, plot3D, methods
Suggests: knitr, rmarkdown, tibble, testthat
VignetteBuilder: knitr
Type: Package
Title: Distance Sampling Survey Design
Version: 0.1.0
Author: Laura Marshall <lhm@st-andrews.ac.uk>
Maintainer: Laura Marshall <lhm@st-andrews.ac.uk>
Description: Creates survey designs for distance sampling surveys. These designs can be assessed for various effort and coverage statistics. Once the user is satisfied with the design characteristics they can generate a set of transects to use in their distance sampling survey. Many of the designs implemented in this R package were first made available in our 'Distance' for Windows software and are detailed in Chapter 7 of Advanced Distance Sampling, Buckland et. al. (2008, ISBN-13: 978-0199225873). Find out more about estimating animal/plant abundance with distance sampling at <http://distancesampling.org/>.
BugReports: https://github.com/DistanceDevelopment/dssd/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Collate: 'Class.Constructors.R' 'Coverage.Grid.R' 'Transect.R' 'Region.R' 'generic.functions.R' 'Survey.Design.R' 'Line.Transect.Design.R' 'Line.Transect.R' 'Point.Transect.Design.R' 'Point.Transect.R' 'calc.region.width.R' 'calculate.trackline.pl.R' 'calculate.trackline.zz.R' 'calculate.trackline.zzcom.R' 'check.line.design.R' 'check.point.design.R' 'check.shape.R' 'generate.eqspace.zigzags.R' 'generate.parallel.lines.R' 'generate.random.points.R' 'generate.systematic.points.R' 'get.intersection.points.R' 'run.coverage.R' 'write.transects.R'
NeedsCompilation: no
Packaged: 2019-08-02 22:14:36 UTC; lhm
Repository: CRAN
Date/Publication: 2019-08-05 13:00:02 UTC

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New package DRAFT with initial version 0.3.0
Package: DRAFT
Type: Package
Title: Disease Rapid Analysis and Forecasting Tool
Version: 0.3.0
Authors@R: c(person(given="Michal", family="Ben-Nun", email="mbennun@predsci.com", role="aut"), person(given="James", family="Turtle", email="jturtle@predsci.com", role="cre"), person(given="Pete", family="Riley", email="pete@predsci.com", role="ctb"))
Author: Michal Ben-Nun [aut], James Turtle [cre], Pete Riley [ctb]
Maintainer: James Turtle <jturtle@predsci.com>
Description: Fits epidemic data to and generates stochastic profiles of a model with constant or time-dependent behavior modification parameters. Two parameters, p and q, describe the effect of reduced contact rate of susceptible and infectious populations, respectively as described by Brauer (2011, ISSN:1471-2458). In the absence of behavior modification, p=q=1, we recover the familiar compartmental Susceptible-Infectious-Recovered (SIR) equations. 'DRAFT' supports both constant values for p and q and a time-dependent form which smoothly changes p and q from their initial, pre-epidemic value of 1.0 to the user chosen values that are between 0 and 1. The start and transient time of behavior change are set by the user. 'DRAFT' can be used to compare forecasts of epidemic incidence with and without behavior modification. Additional parameters and data fitting methods are explained in Ben-Nun et al (2019) <doi:10.1371/journal.pcbi.1007013>.
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Imports: stats, utils, tools, coda, gridExtra, ggplot2, reshape, lubridate (>= 1.7.0)
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Packaged: 2019-08-02 23:46:24 UTC; turtle
Repository: CRAN
Date/Publication: 2019-08-05 13:00:05 UTC

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New package BayesPostEst with initial version 0.0.1
Package: BayesPostEst
Type: Package
Title: Generate Postestimation Quantities for Bayesian MCMC Estimation
Version: 0.0.1
Date: 2019-08-01
Authors@R: c(person("Johannes", "Karreth", email = "jkarreth@ursinus.edu", role = c("aut")), person("Shana", "Scogin", email = "shanarscogin@gmail.com", role = c("aut", "cre")), person("Andreas", "Beger", email = "adbeger@gmail.com", role = c("aut")), person("Myunghee", "Lee", email = "mlq38@mail.missouri.edu", role = c("ctb")), person("Neil", "Williams", email = "snpwill@uga.edu", role = c("ctb")))
Description: An implementation of functions to generate and plot postestimation quantities after estimating Bayesian regression models using Markov chain Monte Carlo (MCMC). Functionality includes the estimation of the Precision-Recall curves (see Beger, 2016 <doi:10.2139/ssrn.2765419>), the implementation of the observed values method of calculating predicted probabilities by Hanmer and Kalkan (2013) <doi:10.1111/j.1540-5907.2012.00602.x>, the implementation of the average value method of calculating predicted probabilities (see King, Tomz, and Wittenberg, 2000 <doi:10.2307/2669316>), and the generation and plotting of first differences to summarize typical effects across covariates (see Long 1997, ISBN:9780803973749; King, Tomz, and Wittenberg, 2000 <doi:10.2307/2669316>). This package can be used with MCMC output generated by any Bayesian estimation tool including 'JAGS', 'BUGS', 'MCMCpack', and 'Stan'.
URL: https://github.com/ShanaScogin/BayesPostEst
BugReports: https://github.com/ShanaScogin/BayesPostEst/issues
License: GPL-3
Imports: carData, caTools, coda (>= 0.13), dplyr (>= 0.5.0), ggmcmc, ggplot2, ggridges, R2jags, reshape2, rlang, ROCR, stats, tidyr (>= 0.5.1)
Depends: R (>= 2.14.0)
Encoding: UTF-8
LazyData: TRUE
LazyLoad: TRUE
Suggests: knitr, MCMCpack, rmarkdown, rstan (>= 2.10.1), rstanarm, testthat
VignetteBuilder: knitr
RoxygenNote: 6.1.1
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
NeedsCompilation: no
Packaged: 2019-08-02 21:10:33 UTC; shanascogin
Author: Johannes Karreth [aut], Shana Scogin [aut, cre], Andreas Beger [aut], Myunghee Lee [ctb], Neil Williams [ctb]
Maintainer: Shana Scogin <shanarscogin@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-05 12:20:09 UTC

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New package RISCA with initial version 0.8
Package: RISCA
Type: Package
Title: Causal Inference and Prediction in Cohort-Based Analyses
Version: 0.8
Depends: R (>= 3.6.0), splines, survival, relsurv, riskRegression
Imports: date, graphics, nlme, MASS, mvtnorm, statmod
Authors@R: c( person("Yohann", "Foucher", email = "Yohann.Foucher@univ-nantes.fr", role = c("aut", "cre")), person("Florent", "Le Borgne", email = "fleborgne@idbc.fr", role = "aut"), person("Etienne", "Dantan", email = "Etienne.Dantan@univ-nantes.fr", role = "aut"), person("Florence", "Gillaizeau", email = "Florence.Gillaizeau@univ-nantes.fr", role = "aut"), person("Arthur", "Chatton", email = "arthur.chatton@etu.univ-nantes.fr", role = "aut"), person("Christophe", "Combescure", email = "christophe.combescure@hcuge.ch", role = "aut"))
Description: We propose numerous functions for cohort-based analyses, either for prediction or causal inference. For causal inference, it includes Inverse Probability Weighting and G-computation for marginal estimation of an exposure effect when confounders are expected. We deal with binary outcomes, times-to-events (Le Borgne, 2016, <doi:10.1002/sim.6777>), competing events (Trebern-Launay, 2018, <doi: 10.1007/s10654-017-0322-3>), and multi-state data (Gillaizeau, 2018, <doi: 10.1002/sim.7550>). For multistate data, semi-Markov model with interval censoring (Foucher, 2008, <doi: 10.1177/0962280208093889>) may be considered and we propose the possibility to consider the excess of mortality related to the disease compared to reference lifetime tables (Gillaizeau, 2017, <doi: 10.1177/0962280215586456>). For predictive studies, we propose a set of functions to estimate time-dependent receiver operating characteristic (ROC) curves with the possible consideration of right-censoring times-to-events or the presence of confounders (Le Borgne, 2018, <doi: 10.1177/0962280217702416>). Finally, several functions are available to assess time-dependant ROC curves (Combescure, 2017, <doi: 10.1177/0962280212464542>) or survival curves (Combescure, 2014, <doi: 10.1002/sim.6111>) from aggregated data.
License: GPL (>= 2)
LazyLoad: yes
URL: www.labcom-risca.com
NeedsCompilation: no
Packaged: 2019-08-02 14:34:25 UTC; foucher-y
Author: Yohann Foucher [aut, cre], Florent Le Borgne [aut], Etienne Dantan [aut], Florence Gillaizeau [aut], Arthur Chatton [aut], Christophe Combescure [aut]
Maintainer: Yohann Foucher <Yohann.Foucher@univ-nantes.fr>
Repository: CRAN
Date/Publication: 2019-08-05 11:00:05 UTC

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New package geobr with initial version 1.0
Type: Package
Package: geobr
Title: Loads Shapefiles of Official Spatial Data Sets of Brazil
Version: 1.0
Authors@R: c(person(given="Rafael H. M.", family="Pereira", email="rafa.pereira.br@gmail.com", role=c("aut", "cre"), comment = c(ORCID = "0000-0003-2125-7465")), person(given="Caio", family="Nogueira Goncalves", role=c("aut")), person(given="Guilherme", family="Duarte Carvalho", role=c("aut")), person(given="Paulo Henrique", family="Fernandes de Araujo", role=c("aut")), person(given="Rodrigo", family="Almeida de Arruda", role=c("aut")), person(given="Igor", family="Nascimento", role="aut"), person("Ipea - Institue for Applied Economic Research", role = c("cph", "fnd")))
Date: 2019-07-28
URL: https://github.com/ipeaGIT/geobr
BugReports: https://github.com/ipeaGIT/geobr/issues
Description: Easy access to shapefiles of the Brazilian Institute of Geography and Statistics (IBGE) <https://www.ibge.gov.br/> and other official spatial data sets of Brazil as 'sf' objects in R. The package includes a wide range of geographic datasets available at various geographic scales and for various years.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.4.0)
Suggests: ggplot2, mapview, knitr, rio, rmarkdown
Imports: dplyr, httr, readr, sf, utils
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-02 14:29:10 UTC; rafa
Author: Rafael H. M. Pereira [aut, cre] (<https://orcid.org/0000-0003-2125-7465>), Caio Nogueira Goncalves [aut], Guilherme Duarte Carvalho [aut], Paulo Henrique Fernandes de Araujo [aut], Rodrigo Almeida de Arruda [aut], Igor Nascimento [aut], Ipea - Institue for Applied Economic Research [cph, fnd]
Maintainer: Rafael H. M. Pereira <rafa.pereira.br@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-05 11:00:02 UTC

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Sun, 04 Aug 2019

New package genderizeR with initial version 2.1.1
Package: genderizeR
Type: Package
Title: Gender Prediction Based on First Names
Version: 2.1.1
Authors@R: c( person(given = "Kamil", family = "Wais", email = "kamil.wais@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4062-055X") ), person("Nathan", "VanHoudnos", role = "ctb"), person("John", "Ramey", role = "ctb"), person("Thomas", "Klebel", role = "ctb") )
Description: Utilizes the 'genderize.io' Application Programming Interface to predict gender from first names extracted from a text vector. The accuracy of prediction could be controlled by two parameters: counts of a first name in the database and probability of prediction.
License: MIT + file LICENSE
URL: https://github.com/kalimu/genderizeR#readme, https://kalimu.github.io/project/genderizer/
BugReports: https://github.com/kalimu/genderizeR/issues
Imports: stringr (>= 1.0.0), httr (>= 1.1.0), tm (>= 0.6-2), data.table (>= 1.9.6), magrittr, parallel (>= 3.3.0), utils
Depends: R (>= 3.3.0)
Encoding: UTF-8
LazyData: true
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-04 08:04:20 UTC; Kamil Wais
Author: Kamil Wais [aut, cre] (<https://orcid.org/0000-0002-4062-055X>), Nathan VanHoudnos [ctb], John Ramey [ctb], Thomas Klebel [ctb]
Maintainer: Kamil Wais <kamil.wais@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-04 14:20:06 UTC

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Sat, 03 Aug 2019

New package foreSIGHT with initial version 0.9.8
Package: foreSIGHT
Version: 0.9.8
Depends: R (>= 3.3.0),GA (>= 3.0.2), zoo
Imports: doParallel, ggplot2 (>= 3.0.0), directlabels, cowplot, stats, graphics, grDevices, utils, moments
Suggests: knitr (>= 1.8)
Title: Systems Insights from Generation of Hydroclimatic Timeseries
Authors@R: c(person("Bree", "Bennett", role=c("aut","cre"),email="bree.bennett@adelaide.edu.au", comment = c(ORCID = "0000-0002-2131-088X")), person("Sam", "Culley", role=c("aut"),email="sam.culley@adelaide.edu.au", comment = c(ORCID = "0000-0003-4798-8522")), person("Seth", "Westra", role=("aut"), email="seth.westra@adelaide.edu.au", comment = c(ORCID = "0000-0003-4023-6061")), person("Danlu", "Guo", role=("ctb"), email="danlu.guo@adelaide.edu.au", comment = c(ORCID = "0000-0003-1083-1214")), person("Holger", "Maier", role=("ths"), email="holger.maier@adelaide.edu.au", comment = c(ORCID = "0000-0002-0277-6887")))
Author: Bree Bennett [aut, cre] (<https://orcid.org/0000-0002-2131-088X>), Sam Culley [aut] (<https://orcid.org/0000-0003-4798-8522>), Seth Westra [aut] (<https://orcid.org/0000-0003-4023-6061>), Danlu Guo [ctb] (<https://orcid.org/0000-0003-1083-1214>), Holger Maier [ths] (<https://orcid.org/0000-0002-0277-6887>)
Maintainer: Bree Bennett <bree.bennett@adelaide.edu.au>
Description: A tool to create hydroclimate scenarios, stress test systems and visualize system performance in scenario-neutral climate change impact assessments. Scenario-neutral approaches 'stress-test' the performance of a modelled system by applying a wide range of plausible hydroclimate conditions (see Brown & Wilby (2012) <doi:10.1029/2012EO410001> and Prudhomme et al. (2010) <doi:10.1016/j.jhydrol.2010.06.043>). These approaches allow the identification of hydroclimatic variables that affect the vulnerability of a system to hydroclimate variation and change. This tool enables the generation of perturbed time series using a range of approaches including simple scaling of observed time series (e.g. Culley et al. (2016) <doi:10.1002/2015WR018253>) and stochastic simulation of perturbed time series via an inverse approach (see Guo et al. (2018) <doi:10.1016/j.jhydrol.2016.03.025>). It incorporates a number of stochastic weather models to generate hydroclimate variables on a daily basis (e.g. precipitation, temperature, potential evapotranspiration) and allows a variety of different hydroclimate variable properties, herein called attributes, to be perturbed. Options are included for the easy integration of existing system models both internally in R and externally for seamless 'stress-testing'. A suite of visualization options for the results of a scenario-neutral analysis (e.g. plotting performance spaces and overlaying climate projection information) are also included. As further developments in scenario-neutral approaches occur the tool will be updated to incorporate these advances.
License: GPL-3
NeedsCompilation: no
VignetteBuilder: knitr
Packaged: 2019-08-03 07:57:00 UTC; a1160755
Repository: CRAN
Date/Publication: 2019-08-03 23:10:02 UTC

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New package RMixtCompIO with initial version 4.0.0
Package: RMixtCompIO
Type: Package
Title: Mixture Models with Heterogeneous and (Partially) Missing Data
Version: 4.0.0
Date: 2019-08-02
Authors@R: c(person("Vincent", "Kubicki", role = "aut"), person("Christophe", "Biernacki", role = "aut"), person("Quentin", "Grimonprez", role = c("aut", "cre"), email = "quentin.grimonprez@inria.fr"), person("Serge", "Iovleff", role = "ctb"), person("Matthieu", "Marbac-Lourdelle", role = "ctb"), person("Étienne", "Goffinet", role = "ctb"), person("Patrick", "Patrick Wieschollek", role = "ctb", comment = "for CppOptimizationLibrary"), person("Tobias", "Wood", role = "ctb", comment = "for CppOptimizationLibrary"))
Copyright: Inria - Université de Lille - CNRS; Patrick Wieschollek, Tobias Wood & the respective contributors for CppOptimizationLibrary
License: AGPL-3
Description: Mixture Composer <https://github.com/modal-inria/MixtComp> is a project to build mixture models with heterogeneous data sets and partially missing data management. It includes models for real, categorical, counting, functional and ranking data. This package contains the minimal R interface of the C++ 'MixtComp' library.
URL: https://github.com/modal-inria/MixtComp, https://massiccc.lille.inria.fr/
BugReports: https://github.com/modal-inria/MixtComp/issues
Imports: Rcpp, doParallel, foreach
Suggests: Rmixmod, blockcluster, testthat, RInside, xml2
LinkingTo: Rcpp, RcppEigen, BH
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-08-02 16:05:47 UTC; grimonprez
Author: Vincent Kubicki [aut], Christophe Biernacki [aut], Quentin Grimonprez [aut, cre], Serge Iovleff [ctb], Matthieu Marbac-Lourdelle [ctb], Étienne Goffinet [ctb], Patrick Patrick Wieschollek [ctb] (for CppOptimizationLibrary), Tobias Wood [ctb] (for CppOptimizationLibrary)
Maintainer: Quentin Grimonprez <quentin.grimonprez@inria.fr>
Repository: CRAN
Date/Publication: 2019-08-03 08:10:02 UTC

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New package RMaCzek with initial version 1.0.0
Package: RMaCzek
Type: Package
Title: Czekanowski's Diagrams
Version: 1.0.0
Date: 2019-08-02
Author: Albin Vasterlund <abbe--93@hotmail.com>
Maintainer: Krzysztof Bartoszek <krzbar@protonmail.ch>
Description: Allows for production of Czekanowski's Diagrams. See A. Vasterlund (2019) Master thesis, Linkoping University.
Depends: R(>= 3.4)
Imports: GA(>= 3.2), graphics, methods, seriation, stats
License: GPL-3
Collate: czek_matrix.R dot_functions.R plot.czek_matrix.R register_seriate_ga.R RMaCzek.R seriate_ga.R Um_factor.R
LazyLoad: yes
LazyData: true
NeedsCompilation: no
Repository: CRAN
Packaged: 2019-08-02 18:03:26 UTC; bart
Date/Publication: 2019-08-03 08:30:02 UTC

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New package ktaucenters with initial version 0.1.0
Package: ktaucenters
Type: Package
Title: Robust Clustering Procedures
Version: 0.1.0
Author: Juan Domingo Gonzalez [cre, aut], Victor J. Yohai [aut], Ruben H. Zamar [aut]
Authors@R: c(person("Juan Domingo", "Gonzalez", email = "juanrst@hotmail.com", role = c("cre","aut")), person("Victor J.", "Yohai", email = "victoryohai@gmail.com", role = "aut"), person("Ruben H.", "Zamar", email = "ruben@stat.ubc.ca", role = "aut") )
Maintainer: Juan Domingo Gonzalez <juanrst@hotmail.com>
Description: A clustering algorithm similar to K-Means is implemented, it has two main advantages, namely (a) The estimator is resistant to outliers, that means that results of estimator are still correct when there are atypical values in the sample and (b) The estimator is efficient, roughly speaking, if there are no outliers in the sample, results will be similar than those obtained by a classic algorithm (K-Means). Clustering procedure is carried out by minimizing the overall robust scale so-called tau scale. (see Gonzalez, Yohai and Zamar (2019) <arxiv:1906.08198>).
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 2.10), MASS, methods, dplyr, dbscan, stats, GSE
LazyData: true
RoxygenNote: 6.1.1
Suggests: jpeg, tclust, knitr
NeedsCompilation: no
Packaged: 2019-08-02 16:37:50 UTC; juan
Repository: CRAN
Date/Publication: 2019-08-03 08:20:02 UTC

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New package rmdplugr with initial version 0.4.0
Package: rmdplugr
Title: Plugins for R Markdown Formats
Version: 0.4.0
Authors@R: person(given = "Johan", family = "Larsson", role = c("aut", "cre"), email = "johanlarsson@outlook.com", comment = c(ORCID = "0000-0002-4029-5945"))
Description: Formats for R Markdown that undo modifications by 'pandoc' and 'rmarkdown' to original 'latex' templates, such as smaller margins, paragraph spacing, and compact titles. In addition, enhancements such as author blocks with affiliations and headers and footers are introduced. All of this functionality is built around plugins that modify the default 'pandoc' template without relying on custom templates.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: rmarkdown, bookdown
Suggests: testthat (>= 2.1.0), covr, spelling, knitr
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-02 15:33:32 UTC; johan
Author: Johan Larsson [aut, cre] (<https://orcid.org/0000-0002-4029-5945>)
Maintainer: Johan Larsson <johanlarsson@outlook.com>
Repository: CRAN
Date/Publication: 2019-08-03 07:50:02 UTC

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New package intsurv with initial version 0.2.0
Package: intsurv
Title: Integrative Survival Modeling
Version: 0.2.0
Date: 2019-08-02
Authors@R: c( person(given = "Wenjie", family = "Wang", email = "wenjie.2.wang@uconn.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0363-3180")), person(given = "Kun", family = "Chen", role = "ctb", comment = c(ORCID = "0000-0003-3579-5467")), person(given = "Jun", family = "Yan", role = "ctb", comment = c(ORCID = "0000-0003-4401-7296")) )
Description: Contains implementations of integrative survival analysis routines, including regular Cox cure rate model proposed by Kuk and Chen (1992) <doi:10.1093/biomet/79.3.531> via an EM algorithm proposed by Sy and Taylor (2000) <doi:10.1111/j.0006-341X.2000.00227.x>, regularized Cox cure rate model with elastic net penalty following Masud et al. (2018) <doi:10.1177/0962280216677748>, and Zou and Hastie (2005) <doi:10.1111/j.1467-9868.2005.00503.x>, and weighted concordance index for cure models proposed by Asano and Hirakawa (2017) <doi:10.1080/10543406.2017.1293082>.
Depends: R (>= 3.2.3)
Imports: Rcpp (>= 0.12.0), methods, stats,
LinkingTo: Rcpp, RcppArmadillo
License: GPL (>= 3)
LazyData: true
Collate: 'RcppExports.R' 'class.R' 'Survi.R' 'assessment.R' 'bootSe.R' 'coef.R' 'cox_cure.R' 'cox_cure_net.R' 'iCoxph.R' 'intsurv.R' 'misc.R' 'prep_model.R' 'print.R' 'show.R' 'simData4cure.R' 'simData4iCoxph.R' 'summary.R'
URL: https://github.com/wenjie2wang/intsurv
BugReports: https://github.com/wenjie2wang/intsurv/issues
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-08-02 15:32:07 UTC; wenjie
Author: Wenjie Wang [aut, cre] (<https://orcid.org/0000-0003-0363-3180>), Kun Chen [ctb] (<https://orcid.org/0000-0003-3579-5467>), Jun Yan [ctb] (<https://orcid.org/0000-0003-4401-7296>)
Maintainer: Wenjie Wang <wenjie.2.wang@uconn.edu>
Repository: CRAN
Date/Publication: 2019-08-03 07:50:05 UTC

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New package hdfqlr with initial version 0.6-0
Package: hdfqlr
Title: Interface to 'HDFql' API
Version: 0.6-0
Authors@R: person("Michael", "Koohafkan", email = "michael.koohafkan@gmail.com", role = c("aut", "cre"))
Description: Provides an interface to 'HDFql' <http://www.hdfql.com/> and helper functions for reading data from and writing data to 'HDF5' files. 'HDFql' provides a high-level language for managing 'HDF5' data that is platform independent. For more information, see the reference manual <http://www.hdfql.com/resources/HDFqlReferenceManual.pdf>.
Depends: R (>= 3.4)
Imports: utils, methods
Suggests: bit64 (>= 0.9), knitr (>= 1.22), ggplot2 (>= 3.2), testthat (>= 2.1.0)
SystemRequirements: HDFql (>= 2.1.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-02 15:06:30 UTC; mkoohafk
Author: Michael Koohafkan [aut, cre]
Maintainer: Michael Koohafkan <michael.koohafkan@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-03 07:40:02 UTC

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New package cder with initial version 0.1-0
Package: cder
Title: Interface to the California Data Exchange Center
Version: 0.1-0
Authors@R: person(given = "Michael", family = "Koohafkan", role = c("aut", "cre"), email = "michael.koohafkan@gmail.com")
Description: Connect to the California Data Exchange Center (CDEC) Web Service <http://cdec.water.ca.gov/>. 'CDEC' provides a centralized database to store, process, and exchange real-time hydrologic information gathered by various cooperators throughout California. The 'CDEC' Web Service <http://cdec.water.ca.gov/dynamicapp/wsSensorData> provides a data download service for accessing historical records.
License: GPL (>= 3)
URL: https://github.com/mkoohafkan/cder
BugReports: https://github.com/mkoohafkan/cder/issues
Depends: R (>= 3.4)
Imports: curl (>= 3.3), glue (>= 1.3), stringr (>= 1.3), tibble (>= 2.0), dplyr (>= 0.7), readr (>= 1.3), rlang (>= 0.3), lubridate (>= 1.7)
Encoding: UTF-8
LazyData: true
Suggests: knitr (>= 1.21), rmarkdown (>= 1.11)
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-02 15:23:48 UTC; mkoohafk
Author: Michael Koohafkan [aut, cre]
Maintainer: Michael Koohafkan <michael.koohafkan@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-03 07:50:09 UTC

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New package CAWaR with initial version 0.0.1
Package: CAWaR
Type: Package
Title: CAWa Project Tools
Version: 0.0.1
Date: 2019-07-30
Authors@R: person("Ruben", "Remelgado", role = c("aut", "cre"), email="remelgado.ruben@gmail.com")
URL: https://github.com/RRemelgado/fieldRS/
BugReports: https://github.com/RRemelgado/fieldRS/issues/
Maintainer: Ruben Remelgado <remelgado.ruben@gmail.com>
Description: Tools to process ground-truth data on crop types and perform a phenology based crop type classification. These tools were developed in the scope of the CAWa project and extend on the work of Conrad et al. (2011) <doi:10.1080/01431161.2010.550647>. Moreover, they introduce an innovative classification and validation scheme that utilizes spatially independent samples as proposed by Remelgado et al. (2017) <doi:10.1002/rse2.70>.
LazyData: TRUE
Encoding: UTF-8
Imports: raster, sp, rgdal, ggplot2, grDevices, spatialEco, rgeos, lubridate, RStoolbox, fieldRS, rsMove
RoxygenNote: 6.1.1
License: GPL (>= 3)
Suggests: knitr, rmarkdown, kableExtra, imager, lattice
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-02 15:01:36 UTC; rr70wedu
Author: Ruben Remelgado [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-03 07:40:04 UTC

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New package trackdf with initial version 0.2.0
Package: trackdf
Type: Package
Title: Data Frame Class for Tracking Data
Version: 0.2.0
Authors@R: c( person("Simon", "Garnier", email = "garnier@njit.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3886-3974")) )
Maintainer: Simon Garnier <garnier@njit.edu>
Description: Data frame class for storing collective movement data (e.g. fish schools, ungulate herds, baboon troops) collected from GPS trackers or computer vision tracking software.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.5.0)
Imports: tibble, data.table, rgdal, sp, lubridate, methods
Suggests: readr, dplyr, ggplot2, knitr, rmarkdown, adehabitatLT, move, moveVis, ctmm, moveHMM, mapproj
VignetteBuilder: knitr
URL: https://swarm-lab.github.io/trackdf/, https://github.com/swarm-lab/trackdf
BugReports: https://github.com/swarm-lab/trackdf/issues
NeedsCompilation: no
Packaged: 2019-08-02 13:37:23 UTC; simon
Author: Simon Garnier [aut, cre] (<https://orcid.org/0000-0002-3886-3974>)
Repository: CRAN
Date/Publication: 2019-08-03 07:00:02 UTC

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New package SHAPforxgboost with initial version 0.0.1
Package: SHAPforxgboost
Title: SHAP Plots for 'XGBoost'
Version: 0.0.1
Authors@R: c( person(given = "Yang", family = "Liu", role = c("aut", "cre"), email = "lyhello@gmail.com", comment = c(ORCID = "0000-0001-6557-6439")), person(given = "Allan", family = "Just", role = c("ctb"), email = "allan.just@mssm.edu", comment = c(ORCID = "0000-0003-4312-5957")) )
Description: The aim of 'SHAPforxgboost' is to aid in visual data investigations using SHAP (SHapley Additive exPlanation) visualization plots for 'XGBoost'. It provides summary plot, dependence plot, interaction plot, and force plot. It relies on the 'dmlc/xgboost' package to produce SHAP values. Please refer to 'slundberg/shap' for the original implementation of SHAP in 'Python'.
License: MIT + file LICENSE
URL: https://github.com/liuyanguu/SHAPforxgboost
BugReports: https://github.com/liuyanguu/SHAPforxgboost/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3.0)
Imports: ggplot2 (>= 3.0.0), xgboost (>= 0.81.0.0), data.table (>= 1.12.0), ggforce (>= 0.2.1.9000), ggExtra (>= 0.8), RColorBrewer (>= 1.1.2), parallel
Suggests: gridExtra (>= 2.3), here
RoxygenNote: 6.1.1.9000
NeedsCompilation: no
Packaged: 2019-08-02 13:22:33 UTC; lyhel
Author: Yang Liu [aut, cre] (<https://orcid.org/0000-0001-6557-6439>), Allan Just [ctb] (<https://orcid.org/0000-0003-4312-5957>)
Maintainer: Yang Liu <lyhello@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-03 07:00:06 UTC

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New package NHSRdatasets with initial version 0.1.1
Package: NHSRdatasets
Type: Package
Title: NHS and Healthcare Related Data for Education and Training
Version: 0.1.1
Authors@R: c( person("Chris", "Mainey", ,"chris.mainey@uhb.nhs.uk", c("aut", "cre"), comment = c(ORCID ="0000-0002-3018-6171")), person("NHS-R community", role = "cph") )
Maintainer: Chris Mainey <chris.mainey@uhb.nhs.uk>
Description: Free United Kingdom National Health Service (NHS) and other healthcare, or population health-related data for education and training purposes. This package currently contains a single simulated hospital dataset for teaching regression methods, with the addition of more datasets planned for future releases. This package exists to support skills development in the NHS-R community: <https://nhsrcommunity.com/>.
License: CC0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.5.0)
BugReports: https://github.com/nhs-r-community/NHSRdatasets/issues
Suggests: dplyr, ggplot2, lme4, MASS, ModelMetrics, lmtest, testthat (>= 2.1.0), covr, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-02 12:35:24 UTC; Christopher
Author: Chris Mainey [aut, cre] (<https://orcid.org/0000-0002-3018-6171>), NHS-R community [cph]
Repository: CRAN
Date/Publication: 2019-08-03 06:40:06 UTC

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New package NewmanOmics with initial version 1.0.2
Package: NewmanOmics
Type: Package
LazyData: true
Title: Extending the Newman Studentized Range Statistic to Transcriptomics
Version: 1.0.2
Date: 2019-08-02
Author: Zachary Abrams, Greg Gershkowitz, Anoushka Joglekar, Chao Liu, Kevin R. Coombes
Maintainer: Kevin R. Coombes <krc@silicovore.com>
Description: Extends the classical Newman studentized range statistic in various ways that can be applied to genome-scale transcriptomic or other expression data.
License: Apache License (== 2.0)
Depends: R (>= 3.5.0)
Imports: methods, stats, graphics, grDevices, oompaBase
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
URL: http://oompa.r-forge.r-project.org/
NeedsCompilation: no
Packaged: 2019-08-02 13:02:34 UTC; Kevin
Repository: CRAN
Date/Publication: 2019-08-03 06:50:05 UTC

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New package joinet with initial version 0.0.1
Package: joinet
Version: 0.0.1
Title: Multivariate Regression
Description: Implements high-dimensional multivariate regression by stacked generalisation (Wolpert 1992 <doi:10.1016/S0893-6080(05)80023-1>). For positively correlated outcomes, a single multivariate regression is typically more predictive than multiple univariate regressions. Includes functions for model fitting, extracting coefficients, outcome prediction, and performance measurement.
Depends: R (>= 3.0.0)
Imports: glmnet, palasso, cornet
Suggests: knitr, testthat, MASS
Enhances: RColorBrewer, spls, SiER, MRCE
Authors@R: person("Armin","Rauschenberger",email="a.rauschenberger@vumc.nl",role=c("aut","cre"))
VignetteBuilder: knitr
License: GPL-3
LazyData: true
Language: en-GB
RoxygenNote: 6.1.1
URL: https://github.com/rauschenberger/mixnet
BugReports: https://github.com/rauschenberger/mixnet/issues
NeedsCompilation: no
Packaged: 2019-08-02 12:55:53 UTC; armin.rauschenberger
Author: Armin Rauschenberger [aut, cre]
Maintainer: Armin Rauschenberger <a.rauschenberger@vumc.nl>
Repository: CRAN
Date/Publication: 2019-08-03 06:50:02 UTC

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New package hmlasso with initial version 0.0.1
Package: hmlasso
Type: Package
Title: Lasso with High Missing Rate
Version: 0.0.1
Description: A simple implementation of HMLasso (Lasso with High Missing rate). Takada, M., Fujisawa, H., & Nishikawa, T. (2019) <arXiv:1811.00255>.
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, BH
Imports: Rcpp, MASS, Matrix, RSpectra
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Authors@R: c( person("Masaaki", "Takada", role = c("aut", "cre"), email = "masaaki1.takada@toshiba.co.jp"), person("Toshiba", role = c("aut", "cph")) )
NeedsCompilation: yes
Packaged: 2019-08-02 11:20:55 UTC; takada
Author: Masaaki Takada [aut, cre], Toshiba [aut, cph]
Maintainer: Masaaki Takada <masaaki1.takada@toshiba.co.jp>
Repository: CRAN
Date/Publication: 2019-08-03 06:30:02 UTC

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New package exdex with initial version 1.0.0
Package: exdex
Type: Package
Title: Estimation of the Extremal Index
Version: 1.0.0
Date: 2019-08-02
Authors@R: c( person(c("Paul", "J."), "Northrop", email = "p.northrop@ucl.ac.uk", role = c("aut", "cre", "cph")), person("Constantinos", "Christodoulides", role = c("aut", "cph")) )
Description: Performs frequentist inference for the extremal index of a stationary time series. Two types of methodology are used. One type is based on a model that relates the distribution of block maxima to the marginal distribution of series and leads to the semiparametric maxima estimators described in Northrop (2015) <doi:10.1007/s10687-015-0221-5> and Berghaus and Bucher (2018) <doi:10.1214/17-AOS1621>. Sliding block maxima are used to increase precision of estimation. The other type of methodology uses a model for the distribution of threshold inter-exceedance times (Ferro and Segers (2003) <doi:10.1111/1467-9868.00401>). Two versions of this type of approach are provided, following Suveges (2007) <doi:10.1007/s10687-007-0034-2> and Suveges and Davison (2010) <doi:10.1214/09-AOAS292>.
Imports: chandwich, graphics, methods, Rcpp, RcppRoll, stats
License: GPL (>= 2)
Depends: R (>= 3.3.0)
Suggests: knitr, revdbayes, rmarkdown, testthat, zoo (>= 1.6.4)
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.1
VignetteBuilder: knitr
URL: http://github.com/paulnorthrop/exdex
BugReports: http://github.com/paulnorthrop/exdex/issues
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2019-08-02 12:46:15 UTC; paul
Author: Paul J. Northrop [aut, cre, cph], Constantinos Christodoulides [aut, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>
Repository: CRAN
Date/Publication: 2019-08-03 06:40:03 UTC

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Fri, 02 Aug 2019

New package bigKRLS with initial version 3.0.5.1
Package: bigKRLS
Type: Package
Title: Optimized Kernel Regularized Least Squares
Version: 3.0.5.1
Authors@R: c(person("Pete", "Mohanty", role = c("aut", "cre"), email = "pete.mohanty@gmail.com", comment = c(ORCID = "0000-0001-8531-3345")), person("Robert", "Shaffer", role = "aut", email = "shafferr@upenn.edu", comment = c(ORCID = "0000-0002-2081-2407")))
Description: Functions for Kernel-Regularized Least Squares optimized for speed and memory usage are provided along with visualization tools. For working papers, sample code, and recent presentations visit <https://sites.google.com/site/petemohanty/software/>. bigKRLS, as well its dependencies, require current versions of R and its compilers (and RStudio if used). For details, see <https://github.com/rdrr1990/bigKRLS/blob/master/INSTALL.md>.
License: GPL (>= 2)
Imports: bigalgebra, biganalytics, ggplot2, parallel, Rcpp (>= 0.12.4), shiny
LinkingTo: bigmemory, BH, Rcpp, RcppArmadillo
Depends: R (>= 3.3.0), bigmemory
URL: https://github.com/rdrr1990/bigKRLS
BugReports: https://github.com/rdrr1990/bigKRLS/issues
RoxygenNote: 6.1.1
Suggests: covr, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-08-02 18:35:18 UTC; rbshaffer
Maintainer: Pete Mohanty <pete.mohanty@gmail.com>
Repository: CRAN
Encoding: UTF-8
Author: Pete Mohanty [aut, cre] (<https://orcid.org/0000-0001-8531-3345>), Robert Shaffer [aut] (<https://orcid.org/0000-0002-2081-2407>)
Date/Publication: 2019-08-02 22:10:07 UTC

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New package BMSC with initial version 0.2.1
Package: BMSC
Title: Bayesian Model Selection under Constraints
Version: 0.2.1
Authors@R: c( person("Marcus", "Groß", email = "marcus.gross@inwt-statistics.de", role = c("aut", "cre")), person("Ricardo", "Fernandes", email = "ldv1452@gmail.com", role = c("aut")), person("Mira Celine", "Klein", email = "mira.klein@inwt-statistics.de", role = c("ctb")) )
Description: A Bayesian regression package supporting constrained coefficient estimation and variable selection using Stan. This includes a robust variable selection algorithm by a horseshoe prior (<doi:10.1093/biomet/asq017>) that finds the optimal model considering main effects, interactions as well as powers of given variables under potential parameter constraints.
Depends: R (>= 3.4.0), Rcpp (>= 0.12.0), methods
Imports: dplyr (>= 0.7.4), ggplot2 (>= 2.2.1), loo (>= 2.0.0), rstan (>= 2.18.1), rstantools (>= 1.5.1), R.utils (>= 2.6.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
LinkingTo: StanHeaders (>= 2.18.1), rstan (>= 2.19.2), BH (>= 1.69.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0)
Suggests: lintr, testthat
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-07-24 09:41:12 UTC; mgross
Author: Marcus Groß [aut, cre], Ricardo Fernandes [aut], Mira Celine Klein [ctb]
Maintainer: Marcus Groß <marcus.gross@inwt-statistics.de>
Repository: CRAN
Date/Publication: 2019-08-02 15:00:05 UTC

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New package whoa with initial version 0.0.1
Package: whoa
Type: Package
Title: Evaluation of Genotyping Error in Genotype-by-Sequencing Data
Version: 0.0.1
Authors@R: c( person(given = c("Eric", "C."), family = "Anderson", email = "eric.anderson@noaa.gov", role = c("aut", "cre")) )
Maintainer: Eric C. Anderson <eric.anderson@noaa.gov>
Description: This is a small, lightweight package that lets users investigate the distribution of genotypes in genotype-by-sequencing (GBS) data where they expect (by and large) Hardy-Weinberg equilibrium, in order to assess rates of genotyping errors and the dependence of those rates on read depth. It implements a Markov chain Monte Carlo (MCMC) sampler using 'Rcpp' to compute a Bayesian estimate of what we call the heterozygote miscall rate for restriction-associated digest (RAD) sequencing data and other types of reduced representation GBS data. It also provides functions to generate plots of expected and observed genotype frequencies. Some background on these topics can be found in a recent paper "Recent advances in conservation and population genomics data analysis" by Hendricks et al. (2018) <doi:10.1111/eva.12659>, and another paper describing the MCMC approach is in preparation with Gordon Luikart and Thierry Gosselin.
License: CC0
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.3.0)
Imports: dplyr, magrittr, tibble, tidyr, Rcpp (>= 0.12.16), vcfR, viridis, ggplot2
LinkingTo: Rcpp
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-08-02 00:16:07 UTC; eriq
Author: Eric C. Anderson [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-02 11:20:02 UTC

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New package rQCC with initial version 0.19.8.2
Package: rQCC
Title: Robust Quality Control Chart
Version: 0.19.8.2
Date: 2019-08-02
Authors@R: c(person(given="Chanseok", family="Park", role = c("aut", "cre"), email="statpnu@gmail.com"), person(given="Min", family="Wang", role = "ctb", email="Min.Wang@ttu.edu") )
Author: Chanseok Park [aut, cre], Min Wang [ctb]
Maintainer: Chanseok Park <statpnu@gmail.com>
Depends: R (>= 3.2.3)
Description: Constructs robust quality control chart based on the median and Hodges-Lehmann estimators (location) and the median absolute deviation (MAD) and Shamos estimators (scale) which are unbiased with a sample of finite size. For more details, see Park, Kim and Wang (2019)<arXiv:1908.00462>. This work was partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (No. NRF-2017R1A2B4004169).
License: GPL-2 | GPL-3
URL: https://github.com/AppliedStat/R
BugReports: https://github.com/AppliedStat/R/issues
LazyData: yes
NeedsCompilation: no
Packaged: 2019-08-02 09:42:26 UTC; cp
Repository: CRAN
Date/Publication: 2019-08-02 11:20:05 UTC

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New package Mercator with initial version 0.8.8
Package: Mercator
Version: 0.8.8
Date: 2019-08-01
Title: Clustering and Visualizing Distance Matrices
Author: Kevin R. Coombes, Caitlin E. Coombes
Maintainer: Kevin R. Coombes <krc@silicovore.com>
Description: Defines the classes used to explore, cluster and visualize distance matrices, especially those arising from binary data.
Depends: R (>= 3.1), Thresher (>= 1.1)
Imports: methods, stats, graphics, utils, cluster, Rtsne, igraph, Polychrome, dendextend
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
License: Apache License (== 2.0)
biocViews: Clustering
URL: http://oompa.r-forge.r-project.org/
NeedsCompilation: no
Packaged: 2019-08-01 18:04:01 UTC; Kevin
Repository: CRAN
Date/Publication: 2019-08-02 11:20:08 UTC

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New package describedata with initial version 0.1.0
Package: describedata
Title: Miscellaneous Descriptive Functions
Version: 0.1.0
Authors@R: person("Craig", "McGowan", email = "mcgowan.cj@gmail.com", role = c("aut", "cre"))
Description: Helper functions for descriptive tasks such as making print-friendly bivariate tables, sample size flow counts, and visualizing sample distributions. Also contains 'R' approximations of some common 'SAS' and 'Stata' functions such as 'PROC MEANS' from 'SAS' and 'ladder', 'gladder', and 'pwcorr' from 'Stata'.
Imports: dplyr (>= 0.7), forcats, tibble, tidyr, purrr, broom, stringr, haven, ggplot2, lmtest, rlang
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-08-02 11:14:37 UTC; craigmcgowan
Author: Craig McGowan [aut, cre]
Maintainer: Craig McGowan <mcgowan.cj@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-02 11:50:02 UTC

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New package cpcens with initial version 0.1.0
Package: cpcens
Type: Package
Title: Changepoint Analysis using Censored Time Series Data
Version: 0.1.0
Date: 2019-07-01
Author: Hajra Siddiqa<hajrasiddiqa92@gmail.com>, Sajid Ali<sajidali@qau.edu.pk>, Ismail Shah<ishah@qau.edu.pk>
Maintainer: Sajid Ali<sajidali@qau.edu.pk>
Depends: R (>= 2.10)
Description: To detect the changepoint, this package uses most recent changepoint, double cumulative sum binary segmentation, multiple changepoints in multivariate time series, analyzing each series in the panel independently, and analyzing aggregated data methods. This package is useful to simulate censored time series to detect the most recent changepoint in censored panel data as well as to assess prediction accuracy.
LazyLoad: yes
LazyData: yes
License: GPL (>= 2)
Imports: stats, utils, Rdpack, cents, tbart
RdMacros: Rdpack
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2019-08-02 11:40:02 UTC
RoxygenNote: 6.1.1
Encoding: UTF-8
Suggests: testthat
Packaged: 2019-08-01 16:18:48 UTC; Khan

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New package bayest with initial version 1.0
Package: bayest
Type: Package
Title: Bayesian t-Test
Version: 1.0
Date: 2019-07-26
Author: Riko Kelter
Maintainer: Riko Kelter <riko.kelter@uni-siegen.de>
Description: Provides an Markov-Chain-Monte-Carlo algorithm for Bayesian t-tests on the effect size. The underlying Gibbs sampler is based on a two-component Gaussian mixture and approximates the posterior distributions of the effect size, the difference of means and difference of standard deviations. A posterior analysis of the effect size via the region of practical equivalence is provided, too. For more details about the Gibbs sampler see Kelter (2019) <arXiv:1906.07524>.
Suggests: MCMCpack, coda, MASS
License: GPL-2
NeedsCompilation: no
Packaged: 2019-08-02 08:43:09 UTC; riko
Repository: CRAN
Date/Publication: 2019-08-02 11:10:08 UTC

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New package TSplotly with initial version 1.1.1
Package: TSplotly
Type: Package
Title: Create Interactive Plots on Time Series Dataset
Version: 1.1.1
Authors@R: c(person("Yongkai", "Qiu", role = c("aut", "cre"),email = "yongkai@umich.edu"), person("Zhe", "Yin", role = "aut"), person("Ivo","Dinov",role = "aut"), person("SOCR","team",role = "aut"))
URL: http://socr.umich.edu/people/
Maintainer: Yongkai Qiu <yongkai@umich.edu>
Description: To better visualize time-series dataset, 'TSplotly' package provides an effective mechanism to utilize the powerful 'plotly' package for graphing time series data. It contains 5 core functions: TSplot(): create interactive plot on time series data or fitted ARIMA(X) models. ADDline(): add lines on existing 'TSplot()' objects, as needed. GGtoPY(): create a convenient way to transform (reformat) 'ggplot2' datasets into a format that can work on 'plot_ly()'. GTSplot(): create multiple 'plot_ly()' lines (time-series) based on data frames containing multiple time-series data. TSplot_gen(): a more general version of function 'TSplot()' that can work on any time format.
Depends: R (>= 3.4.0)
Imports: forecast, plotly, zoo, ggplot2, dcemriS4, prettydoc
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-01 20:09:15 UTC; qyk02
Author: Yongkai Qiu [aut, cre], Zhe Yin [aut], Ivo Dinov [aut], SOCR team [aut]
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Repository: CRAN
Date/Publication: 2019-08-02 11:00:08 UTC

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New package topoDistance with initial version 1.0.1
Package: topoDistance
Type: Package
Title: Calculating Topographic Paths and Distances
Version: 1.0.1
Authors@R: person("Ian", "Wang", email = "ianwang@berkeley.edu", role = c("aut", "cre"))
Description: A toolkit for calculating topographic distances and identifying and plotting topographic paths. Topographic distances can be calculated along shortest topographic paths (Wang (2009) <doi:10.1111/j.1365-294X.2009.04338.x>), weighted topographic paths (Zhan et al. (1993) <doi:10.1007/3-540-57207-4_29>), and topographic least cost paths (Wang and Summers (2010) <doi:10.1111/j.1365-294X.2009.04465.x>). Functions can map topographic paths on colored or hill shade maps and plot topographic cross sections (elevation profiles) for the paths.
Depends: R (>= 3.1.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: igraph, gdistance, plotly, raster, RColorBrewer, scales, sp
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-01 21:06:28 UTC; Ian
Author: Ian Wang [aut, cre]
Maintainer: Ian Wang <ianwang@berkeley.edu>
Repository: CRAN
Date/Publication: 2019-08-02 11:00:02 UTC

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New package sharpData with initial version 1.1
Package: sharpData
Title: Data Sharpening
Version: 1.1
Author: W.J. Braun
Description: Functions and data sets inspired by data sharpening - data perturbation to achieve improved performance in nonparametric estimation, as described in Choi, E., Hall, P. and Rousson, V. (2000) <doi:10.1214/aos/1015957396>. Capabilities for enhanced local linear regression function and derivative estimation are included, as well as an asymptotically correct iterated data sharpening estimator for any degree of local polynomial regression estimation. A cross-validation-based bandwidth selector is included which, in concert with the iterated sharpener, will often provide superior performance, according to a median integrated squared error criterion. Sample data sets are provided to illustrate function usage.
Maintainer: W.J. Braun <john.braun@ubc.ca>
LazyLoad: true
LazyData: true
Depends: R (>= 2.0.1), KernSmooth, stats
ZipData: no
License: Unlimited
NeedsCompilation: no
Packaged: 2019-08-01 22:45:29 UTC; braun
Repository: CRAN
Date/Publication: 2019-08-02 10:50:02 UTC

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New package ROpenCVLite with initial version 0.3.410
Package: ROpenCVLite
Type: Package
Title: Install 'OpenCV'
Version: 0.3.410
Authors@R: c( person("Simon", "Garnier", email = "garnier@njit.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3886-3974")), person("Muschelli", "John", email = "muschellij2@gmail.com", role = c("ctb")) )
Maintainer: Simon Garnier <garnier@njit.edu>
Description: Installs 'OpenCV' for use by other packages. 'OpenCV' <https://opencv.org/> is library of programming functions mainly aimed at real-time computer vision. This 'Lite' version contains the stable base version of 'OpenCV' and does not contain any of its externally contributed modules.
License: GPL-3
LazyData: TRUE
Imports: utils, devtools, pkgbuild, parallel
SystemRequirements: cmake, C++11
NeedsCompilation: yes
RoxygenNote: 6.1.1
Biarch: true
Encoding: UTF-8
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://swarm-lab.github.io/ROpenCVLite/, https://github.com/swarm-lab/ROpenCVLite
BugReports: https://github.com/swarm-lab/ROpenCVLite/issues
Packaged: 2019-08-01 22:07:17 UTC; simon
Author: Simon Garnier [aut, cre] (<https://orcid.org/0000-0002-3886-3974>), Muschelli John [ctb]
Repository: CRAN
Date/Publication: 2019-08-02 10:50:08 UTC

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New package phenModel with initial version 1.0
Package: phenModel
Type: Package
Title: Insect Phenology Model Evaluation Based on Daily Temperatures
Version: 1.0
Date: 2019-08-01
Authors@R: c(person("Rafael", "de Andrade Moral", role = c("aut", "cre"), email = "rafael.deandrademoral@mu.ie"), person("Rowan", "Fealy", role = "aut"))
Author: Rafael de Andrade Moral [aut, cre], Rowan Fealy [aut]
Maintainer: Rafael de Andrade Moral <rafael.deandrademoral@mu.ie>
Depends: R (>= 3.0.0), ggplot2, dplyr, reshape, grid
Description: Generates predicted stage change days for an insect, based on daily temperatures and development rate parameters, as developed by Pollard (2014) <http://mural.maynoothuniversity.ie/view/ethesisauthor/Pollard=3ACiaran_P=2E=3A=3A.html>. A few example datasets are included and implemented for P. vulgatissima, the blue willow beetle, but the approach can be readily applied to other species that display similar behaviour.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-08-01 12:35:04 UTC; rafael
Repository: CRAN
Date/Publication: 2019-08-02 10:40:02 UTC

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New package mlmi with initial version 1.0.0
Package: mlmi
Type: Package
Title: Maximum Likelihood Multiple Imputation
Version: 1.0.0
Author: Jonathan Bartlett
Maintainer: Jonathan Bartlett <j.w.bartlett@bath.ac.uk>
Description: Implements so called Maximum Likelihood Multiple Imputation as described by von Hippel (2018) <arXiv:1210.0870v9>. A number of different imputations are available, by utilising the 'norm', 'cat' and 'mix' packages. Inferences can be performed either using combination rules similar to Rubin's or using a likelihood score based approach based on theory by Wang and Robins (1998) <doi:10.1093/biomet/85.4.935>.
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: MASS, gsl, norm, cat, mix, Matrix, stats, utils
Suggests: bootImpute, testthat
NeedsCompilation: no
Packaged: 2019-08-01 15:53:12 UTC; jwb67
Repository: CRAN
Date/Publication: 2019-08-02 10:20:05 UTC

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New package iCellR with initial version 1.0.0
Package: iCellR
Type: Package
Title: Analyzing High-Throughput Single Cell Sequencing Data
Version: 1.0.0
Author: Alireza Khodadadi-Jamayran, Joseph Pucella, Hua Zhou, Nicole Doudican, John Carucci, Adriana Heguy, Boris Reizis, Aristotelis Tsirigos
Maintainer: Alireza Khodadadi-Jamayran <alireza.khodadadi.j@gmail.com>
Description: A toolkit that allows scientists to work with data from single cell sequencing technologies such as scRNA-seq, scVDJ-seq and CITE-Seq. Single (i) Cell R package ('iCellR') provides unprecedented flexibility at every step of the analysis pipeline, including normalization, clustering, dimensionality reduction, imputation, visualization, and so on. Users can design both unsupervised and supervised models to best suit their research. In addition, the toolkit provides 2D and 3D interactive visualizations, differential expression analysis, filters based on cells, genes and clusters, data merging, normalizing for dropouts, data imputation methods, correcting for batch differences, pathway analysis, tools to find marker genes for clusters and conditions, predict cell types and pseudotime analysis.
Depends: R (>= 3.3.0), ggplot2, plotly
Imports: Matrix, Rtsne, gridExtra, ggrepel, ggpubr, scatterplot3d, RColorBrewer, knitr, NbClust, shiny, umap, pheatmap, ape, ggdendro, plyr, reshape, Hmisc, htmlwidgets, methods
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/rezakj/iCellR
Suggests: phateR, Rmagic, Seurat
NeedsCompilation: no
Packaged: 2019-08-01 19:16:42 UTC; khodaa01
Repository: CRAN
Date/Publication: 2019-08-02 10:50:04 UTC

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New package GeneralisedCovarianceMeasure with initial version 0.1.0
Package: GeneralisedCovarianceMeasure
Type: Package
Title: Test for Conditional Independence Based on the Generalized Covariance Measure (GCM)
Version: 0.1.0
Author: Jonas Peters and Rajen D. Shah
Maintainer: Jonas Peters <jonas.peters@math.ku.dk>
Description: A statistical hypothesis test for conditional independence. It performs nonlinear regressions on the conditioning variable and then tests for a vanishing covariance between the resulting residuals. It can be applied to both univariate random variables and multivariate random vectors. Details of the method can be found in Rajen D. Shah and Jonas Peters (2018) <arXiv:1804.07203>.
License: GPL-2
Encoding: UTF-8
Imports: CVST, graphics, kernlab, mgcv, stats, xgboost
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-01 10:00:09 UTC; jonas
Repository: CRAN
Date/Publication: 2019-08-02 10:40:05 UTC

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New package tokenizers.bpe with initial version 0.1.0
Package: tokenizers.bpe
Type: Package
Title: Byte Pair Encoding Text Tokenization
Version: 0.1.0
Authors@R: c(person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'jwijffels@bnosac.be', comment = "R wrapper"), person('BNOSAC', role = 'cph', comment = "R wrapper"), person('VK.com', role = 'cph'), person('Gregory Popovitch', role = c('ctb', 'cph'), comment = "Files at src/parallel_hashmap (Apache License, Version 2.0"), person('The Abseil Authors', role = c('ctb', 'cph'), comment = "Files at src/parallel_hashmap (Apache License, Version 2.0"), person('Ivan Belonogov', role = c('ctb', 'cph'), email = 'xbelonogov@gmail.com', comment = "Files at src/youtokentome (MIT License)"))
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Description: Unsupervised text tokenizer focused on computational efficiency. Wraps the 'YouTokenToMe' library <https://github.com/VKCOM/YouTokenToMe> which is an implementation of fast Byte Pair Encoding (BPE) <https://www.aclweb.org/anthology/P16-1162>.
URL: https://github.com/bnosac/tokenizers.bpe
License: MPL-2.0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Imports: Rcpp (>= 0.11.5)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2019-07-31 21:02:18 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), VK.com [cph], Gregory Popovitch [ctb, cph] (Files at src/parallel_hashmap (Apache License, Version 2.0), The Abseil Authors [ctb, cph] (Files at src/parallel_hashmap (Apache License, Version 2.0), Ivan Belonogov [ctb, cph] (Files at src/youtokentome (MIT License))
Repository: CRAN
Date/Publication: 2019-08-02 09:40:02 UTC

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New package simExam with initial version 1.0.0
Package: simExam
Type: Package
Title: Generate Simulated Data for IRT-Enabled Exams
Version: 1.0.0
Author: Waldir Leoncio <waldir.leoncio@gmail.com>
Maintainer: Waldir Leoncio <waldir.leoncio@gmail.com>
Description: Generates binary test data based on Item Response Theory using the two-parameter logistic model (Lord, 1980 <doi:10.4324/9780203056615>). Useful functions for test equating are included, e.g. functions for generating internal and external common items between test forms and a function to create a linkage plans between those forms. Ancillary functions for generating true item and person parameters as well as for calculating the probability of a person correctly answering an item are also included.
Imports: stats, Matrix, msm
BugReports: https://github.com/wleoncio/simExam/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-31 13:12:27 UTC; wleoncio
Repository: CRAN
Date/Publication: 2019-08-02 09:20:02 UTC

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New package GWASinspector with initial version 1.1.2
Package: GWASinspector
Type: Package
Title: Comprehensive and Easy to Use Quality Control of GWAS Results
Version: 1.1.2
Date: 2019-07-30
Author: Alireza Ani [aut, cre], Peter J. van der Most [aut], Ahmad Vaez [aut], Ilja M. Nolte [aut]
Maintainer: Alireza Ani <a.ani@umcg.nl>
Depends: R (>= 3.2)
Imports: ini (>= 0.3), futile.logger (>= 1.4), data.table (>= 1.10), hash (>= 2.2), tools (>= 3.0), ggplot2 (>= 3.0), knitr (>= 1.1), rmarkdown (>= 0.9), gridExtra, grid, RSQLite, kableExtra (>= 0.8)
Suggests: xlsx (>= 0.5), parallel (>= 3.0)
VignetteBuilder: knitr
URL: http://GWASinspector.com
Description: When evaluating the results of a genome-wide association study (GWAS), it is important to perform a quality control to ensure that the results are valid, complete, correctly formatted, and, in case of meta-analysis, consistent with other studies that have applied the same analysis. This package was developed to facilitate and streamline this process and provide the user with a comprehensive report.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-31 05:05:02 UTC; Alireza
Repository: CRAN
Date/Publication: 2019-08-02 09:20:08 UTC

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New package Ghat with initial version 0.1.0
Package: Ghat
Title: Quantifying Evolution and Selection on Complex Traits
Version: 0.1.0
Authors@R: c( person("Medhat", "Mahmoud", role = c("aut", "cre"), email = "medhat.mahmoud@gwdg.de"), person("Ngoc-Thuy", "Ha" , role = "aut", email = "nha@gwdg.de"), person("Timothy", "Beissinger", role = "aut", email = "beissinger@gwdg.de") )
Description: Functions are provided for quantifying evolution and selection on complex traits. The package implements effective handling and analysis algorithms scaled for genome-wide data and calculates a composite statistic, denoted Ghat, which is used to test for selection on a trait. The package provides a number of simple examples for handling and analysing the genome data and visualising the output and results. Beissinger et al., (2018) <doi:10.1534/genetics.118.300857>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.0.0)
URL: https://www.genetics.org/content/209/1/321
BugReports: https://github.com/Medhat86/Ghat/issues
Suggests: knitr, rmarkdown
Imports: rrBLUP
NeedsCompilation: no
Packaged: 2019-07-31 09:00:46 UTC; mahmoud1
Author: Medhat Mahmoud [aut, cre], Ngoc-Thuy Ha [aut], Timothy Beissinger [aut]
Maintainer: Medhat Mahmoud <medhat.mahmoud@gwdg.de>
Repository: CRAN
Date/Publication: 2019-08-02 10:00:05 UTC

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New package DTDA.cif with initial version 1.0
Package: DTDA.cif
Title: Doubly Truncated Data Analysis, Cumulative Incidence Functions
Version: 1.0
Authors@R: c( person("Jacobo", "de Uña Álvarez", email = "jacobo@uvigo.es", role = "aut"), person("José Carlos", "Soage González", email = "jsoage@uvigo.es", role = "cre"))
Maintainer: José Carlos Soage González <jsoage@uvigo.es>
Description: Nonparametric estimator of the cumulative incidences of competing risks under double truncation. The estimator generalizes the Efron-Petrosian NPMLE (Non-Parametric Maximun Likelihood Estimator) to the competing risks setting. Efron, B. and Petrosian, V. (1999) <doi:10.2307/2669997>.
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
Imports: doParallel, foreach, Rcpp
LinkingTo: Rcpp
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-07-31 17:01:54 UTC; UVIGO1
Author: Jacobo de Uña Álvarez [aut], José Carlos Soage González [cre]
Repository: CRAN
Date/Publication: 2019-08-02 09:30:02 UTC

More information about DTDA.cif at CRAN
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New package datrProfile with initial version 0.1.0
Package: datrProfile
Type: Package
Title: Column Profile for Tables and Datasets
Version: 0.1.0
Authors@R: person("Arnaldo", "Vitaliano", email = "vitaliano@gmail.com", role = c("aut", "cre"))
Description: Profiles datasets (collecting statistics and informative summaries about that data) on data frames and 'ODBC' tables: maximum, minimum, mean, standard deviation, nulls, distinct values, data patterns, data/format frequencies.
License: GPL-3 | file LICENSE
URL: https://github.com/avitaliano/datrProfile
BugReports: https://github.com/avitaliano/datrProfile/issues
Encoding: UTF-8
LazyData: true
Suggests: testthat
Imports: odbc, dplyr, RSQLite
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-31 13:07:41 UTC; deinf.arnaldo
Author: Arnaldo Vitaliano [aut, cre]
Maintainer: Arnaldo Vitaliano <vitaliano@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-02 09:20:05 UTC

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New package bpgmm with initial version 1.0.5
Package: bpgmm
Type: Package
Title: Bayesian Model Selection Approach for Parsimonious Gaussian Mixture Models
Version: 1.0.5
Date: 2019-07-15
Depends: R(>= 3.1.0)
Imports: methods (>= 3.5.1), mcmcse (>= 1.3-2), pgmm (>= 1.2.3), mvtnorm (>= 1.0-10), MASS (>= 7.3-51.1), Rcpp (>= 1.0.1), gtools (>= 3.8.1), label.switching (>= 1.8)
Author: Xiang Lu <Xiang_Lu at urmc.rochester.edu>, Yaoxiang Li <yl814 at georgetown.edu>, Tanzy Love <tanzy_love at urmc.rochester.edu>
Maintainer: Yaoxiang Li <yl814@georgetown.edu>
Description: Model-based clustering using Bayesian parsimonious Gaussian mixture models. MCMC (Markov chain Monte Carlo) are used for parameter estimation. The RJMCMC (Reversible-jump Markov chain Monte Carlo) is used for model selection. GREEN et al. (1995) <doi:10.1093/biomet/82.4.711>.
SystemRequirements: C++11
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2019-07-31 22:46:03 UTC; bach
Repository: CRAN
Date/Publication: 2019-08-02 10:00:02 UTC

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New package sociome with initial version 1.0.0
Type: Package
Package: sociome
Title: Operationalizing Social Determinants of Health Data for Researchers
Version: 1.0.0
Authors@R: c(person(given = "Nik", family = "Krieger", role = c("aut", "cre"), email = "nk@case.edu"), person(given = "Jarrod", family = "Dalton", role = "aut", email = "daltonj@ccf.org"), person(given = "Cindy", family = "Wang", role = "aut", email = "lxw384@case.edu"), person(given = "Adam", family = "Perzynski", role = "aut", email = "adam.perzynski@case.edu"), person(given = "National Institutes of Health/National Institute on Aging", role = "fnd", comment = "The development of this software package was supported by a research grant from the National Institutes of Health/National Institute on Aging, (Principal Investigators: Jarrod E. Dalton, PhD and Adam T. Perzynski, PhD; Grant Number: 5R01AG055480-02). All of its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH."))
Maintainer: Nik Krieger <nk@case.edu>
Description: Accesses raw data via API and calculates social determinants of health measures for user-specified locations in the US, returning them in tidyverse- and sf-compatible data frames.
License: MIT + file LICENSE
BugReports: https://github.com/NikKrieger/sociome/issues
Depends: R (>= 3.3.0)
Imports: dplyr (>= 0.8.1), magrittr (>= 1.5), methods, mice (>= 3.5.0), psych (>= 1.8.12), purrr (>= 0.3.2), rlang (>= 0.4.0), stringr (>= 1.4.0), tibble (>= 2.1.3), tidycensus (>= 0.9.2), tidyr (>= 0.8.3)
Suggests: ggplot2 (>= 3.2.0), sf (>= 0.7.4), testthat (>= 2.1.1)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-30 18:21:16 UTC; kriegen
Author: Nik Krieger [aut, cre], Jarrod Dalton [aut], Cindy Wang [aut], Adam Perzynski [aut], National Institutes of Health/National Institute on Aging [fnd] (The development of this software package was supported by a research grant from the National Institutes of Health/National Institute on Aging, (Principal Investigators: Jarrod E. Dalton, PhD and Adam T. Perzynski, PhD; Grant Number: 5R01AG055480-02). All of its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.)
Repository: CRAN
Date/Publication: 2019-08-02 08:20:02 UTC

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New package RcppHungarian with initial version 0.1
Package: RcppHungarian
Type: Package
Title: Solves Minimum Cost Bipartite Matching Problems
Version: 0.1
Date: 2019-07-16
Authors@R: c(person("Justin", "Silverman", role=c("aut", "cre"), email = "Justin.Silverman@duke.edu"), person("Cong", "Ma", role=c("ctb", "cph")), person("Markus", "Buehren", role=c("ctb", "cph")))
Maintainer: Justin Silverman <Justin.Silverman@duke.edu>
Copyright: See file COPYRIGHT for details
Description: Header library and R functions to solve minimum cost bipartite matching problem using Huhn-Munkres algorithm (Hungarian algorithm; <https://en.wikipedia.org/wiki/Hungarian_algorithm>; Kuhn (1955) doi:10.1002/nav.3800020109). This is a repackaging of code written by Cong Ma in the GitHub repo <https://github.com/mcximing/hungarian-algorithm-cpp>.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.1)
LinkingTo: Rcpp
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, ggplot2
RoxygenNote: 6.1.1
VignetteBuilder: knitr
URL: https://github.com/jsilve24/RcppHungarian
NeedsCompilation: yes
Packaged: 2019-07-30 13:38:09 UTC; Justin
Author: Justin Silverman [aut, cre], Cong Ma [ctb, cph], Markus Buehren [ctb, cph]
Repository: CRAN
Date/Publication: 2019-08-02 07:20:02 UTC

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New package fillr with initial version 0.1.1
Package: fillr
Title: Fill Missing Values in Vectors
Version: 0.1.1
Authors@R: person(given = "Jelger", family = "van Zaane", role = c("aut", "cre"), email = "j.d.van.zaane@vu.nl")
Description: Edit vectors to fill missing values, based on the vector itself.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: testthat
RoxygenNote: 6.1.1
URL: https://github.com/jelger12/fillr
BugReports: https://github.com/jelger12/fillr/issues
NeedsCompilation: no
Packaged: 2019-07-30 14:31:20 UTC; jze370
Author: Jelger van Zaane [aut, cre]
Maintainer: Jelger van Zaane <j.d.van.zaane@vu.nl>
Repository: CRAN
Date/Publication: 2019-08-02 07:40:02 UTC

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Thu, 01 Aug 2019

New package bnpa with initial version 0.3.0
Package: bnpa
Type: Package
Title: Bayesian Networks & Path Analysis
Version: 0.3.0
Imports: bnlearn, fastDummies, lavaan, Rgraphviz, semPlot, xlsx
Author: Elias Carvalho, Joao R N Vissoci, Luciano Andrade, Wagner Machado, Emerson P Cabrera, Julio C Nievola
Maintainer: Elias Carvalho <ecacarva@gmail.com>
Description: This project aims to enable the method of Path Analysis to infer causalities from data. For this we propose a hybrid approach, which uses Bayesian network structure learning algorithms from data to create the input file for creation of a PA model. The process is performed in a semi-automatic way by our intermediate algorithm, allowing novice researchers to create and evaluate their own PA models from a data set. The references used for this project are: Koller, D., & Friedman, N. (2009). Probabilistic graphical models: principles and techniques. MIT press. <doi:10.1017/S0269888910000275>. Nagarajan, R., Scutari, M., & Lèbre, S. (2013). Bayesian networks in r. Springer, 122, 125-127. Scutari, M., & Denis, J. B. <doi:10.1007/978-1-4614-6446-4>. Scutari M (2010). Bayesian networks: with examples in R. Chapman and Hall/CRC. <doi:10.1201/b17065>. Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1 - 36. <doi:10.18637/jss.v048.i02>.
URL: https://sites.google.com/site/bnparp/.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-01 01:57:45 UTC; elias
Repository: CRAN
Date/Publication: 2019-08-01 23:20:02 UTC

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New package SECFISH with initial version 0.1.4
Package: SECFISH
Type: Package
Title: Disaggregate Variable Costs
Version: 0.1.4
Author: Isabella Bitetto (COISPA), Loretta Malvarosa (NISEA), Maria Teresa Spedicato (COISPA), Ralf Doering (THUENEN), Joerg Berkenhagen (THUENEN)
Maintainer: Isabella Bitetto <bitetto@coispa.it>
Description: These functions were developed within SECFISH project (Strengthening regional cooperation in the area of fisheries data collection-Socio-economic data collection for fisheries, aquaculture and the processing industry at EU level). They are aimed at identifying correlations between costs and transversal variables by metier using individual vessel data and for disaggregating variable costs from fleet segment to metier level.
License: GPL-2
Depends: R (>= 3.5)
Imports: ggplot2, Hmisc, optimization
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-08-01 13:57:44 UTC; Bitetto Isabella
Repository: CRAN
Date/Publication: 2019-08-01 16:40:19 UTC

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New package nltm with initial version 1.4.2
Package: nltm
Version: 1.4.2
Date: 2019-08-01
Title: Non-Linear Transformation Models
Author: Gilda Garibotti, Alexander Tsodikov, Mark Clements
Maintainer: Mark Clements <mark.clements@ki.se>
Depends: survival, R (>= 2.8.1)
Description: Fits a non-linear transformation model ('nltm') for analyzing survival data, see Tsodikov (2003) <doi:10.1111/1467-9868.00414>. The class of 'nltm' includes the following currently supported models: Cox proportional hazard, proportional hazard cure, proportional odds, proportional hazard - proportional hazard cure, proportional hazard - proportional odds cure, Gamma frailty, and proportional hazard - proportional odds.
License: GPL-2
URL: http://github.com/mclements/nltm
BugReports: http://github.com/mclements/nltm/issues
LazyLoad: No
LazyData: No
NeedsCompilation: yes
Packaged: 2019-08-01 14:50:46 UTC; marcle
Repository: CRAN
Date/Publication: 2019-08-01 17:00:06 UTC

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New package zFactor with initial version 0.1.9
Package: zFactor
Type: Package
Title: Calculate the Compressibility Factor 'z' for Hydrocarbon Gases
Version: 0.1.9
Authors@R: person("Alfonso R.", "Reyes", role = c("aut", "cre", "cph"), email = "alfonso.reyes@oilgainsanalytics.com")
Maintainer: Alfonso R. Reyes <alfonso.reyes@oilgainsanalytics.com>
Description: Computational algorithms to solve equations and find the 'compressibility' factor `z` of hydrocarbon gases. Correlations available: 'Hall-Yarborough', 'Dranchuk-AbuKassem', 'Dranchuk-Purvis-Robinson', 'Beggs-Brill', 'Papp', Shell and an Artificial Neural Network correlation (Ann10) by 'Kamyab' 'et al'. The package uses the original 'Standing-Katz' chart for statistical comparison and plotting. Applicable to sweet hydrocarbon gases for now.
Imports: logging, dplyr, rootSolve, tidyr, ggplot2, data.table, tibble, knitcitations, covr
Suggests: knitr, rmarkdown, testthat
Depends: R (>= 3.4)
License: GPL-2
Encoding: UTF-8
LazyData: true
URL: https://github.com/f0nzie/zFactor
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-31 21:39:37 UTC; msfz751
Author: Alfonso R. Reyes [aut, cre, cph]
Repository: CRAN
Date/Publication: 2019-08-01 14:00:03 UTC

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New package obfuscatoR with initial version 0.2.0
Package: obfuscatoR
Type: Package
Title: Obfuscation Game Designs
Version: 0.2.0
Author: Erlend Dancke Sandorf [aut, cre], Caspar Chorus [aut], Sander van Cranenburgh [aut]
Maintainer: Erlend Dancke Sandorf <esandorf@gmail.com>
Description: When people make decisions, they may do so using a wide variety of decision rules. The package allows users to easily create obfuscation games to test the obfuscation hypothesis. It provides an easy to use interface and multiple options designed to vary the difficulty of the game and tailor it to the user's needs.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.0)
Imports: Rfast, stats, matrixStats, stringr, readr, tibble, crayon
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-18 12:36:30 UTC; esandorf
Repository: CRAN
Date/Publication: 2019-08-01 14:00:06 UTC

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New package GeneBook with initial version 1.0
Package: GeneBook
Type: Package
Title: Multi-Types Gene ID Converting/Annotating
Version: 1.0
Date: 2019-07-28
Author: Li Xu, Zhang Wen, Siyan Chen, Hans Bibiko, Will Lowe
Maintainer: Siyan Chen <siyanc123@gmail.com>
Description: An implementation of the advanced gene search in R. This package has basic annotation information. Also, it contains a relative intact gene database which was obtained from the Human Gene Database <https://www.genecards.org>. It allows users to search gene symbol or alias and convert gene interested to the consistent gene symbols. It also provides users with gene WIKI introduction.
NeedsCompilation: no
Depends: R (>= 3.5.0)
Imports: dplyr, stringr, svDialogs, repmis
License: GPL (>= 3.0)
LazyData: true
Packaged: 2019-07-30 08:54:26 UTC; siyanchen
RoxygenNote: 6.1.1
Repository: CRAN
Date/Publication: 2019-08-01 13:30:05 UTC

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New package wikifacts with initial version 0.1.0
Package: wikifacts
Type: Package
Title: Generates Messages with Facts Sourced from the Wikipedia Main Page
Version: 0.1.0
Authors@R: person("Keith", "McNulty", email = "keith.mcnulty@gmail.com", role = c("aut", "cre"))
Description: Creates messages containing random facts from the Wikipedia homepage. Intended to keep users interested during long waiting periods.
License: CC0
Encoding: UTF-8
LazyData: true
Imports: magrittr, rvest, xml2
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-21 23:54:57 UTC; keithmcnulty
Author: Keith McNulty [aut, cre]
Maintainer: Keith McNulty <keith.mcnulty@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-01 12:20:02 UTC

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New package lifecycle with initial version 0.1.0
Package: lifecycle
Title: Manage the Life Cycle of your Package Functions
Version: 0.1.0
Authors@R: c( person(given = "Lionel", family = "Henry", role = c("aut", "cre"), email = "lionel@rstudio.com"), person(given = "RStudio", role = "cph") )
Description: Manage the life cycle of your exported functions with shared conventions, documentation badges, and non-invasive deprecation warnings. The 'lifecycle' package defines four development stages (experimental, maturing, stable, and questioning) and three deprecation stages (soft-deprecated, deprecated, and defunct). It makes it easy to insert badges corresponding to these stages in your documentation. Usage of deprecated functions are signalled with increasing levels of non-invasive verbosity.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2)
Imports: glue, rlang (>= 0.4.0)
Suggests: covr, crayon, knitr, rmarkdown, testthat (>= 2.1.0)
RoxygenNote: 6.1.1
URL: https://github.com/r-lib/lifecycle
BugReports: https://github.com/r-lib/lifecycle/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-27 07:28:35 UTC; lionel
Author: Lionel Henry [aut, cre], RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>
Repository: CRAN
Date/Publication: 2019-08-01 12:50:05 UTC

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New package LDlinkR with initial version 1.0.0
Package: LDlinkR
Type: Package
Title: Access LDlink API with R
Version: 1.0.0
Authors@R: c(person(given = "Timothy A.", family = "Myers", role = "cre", email = "myersta@mail.nih.gov"), person(given = "Mitchell J.", family = "Machiela", role = "aut", email = "mitchell.machiela@nih.gov"))
Maintainer: Timothy A. Myers <myersta@mail.nih.gov>
Description: Provides access to the LDlink API (<https://ldlink.nci.nih.gov/?tab=apiaccess>) using the R console. This programmatic access facilitates researchers who are interested in performing batch queries in 1000 Genomes Project data using LDlink.
License: GPL (>= 2)
URL: https://ldlink.nci.nih.gov
Encoding: UTF-8
LazyData: true
Imports: httr (>= 1.4.0), utils (>= 3.5.2)
Suggests: testthat
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-01 11:20:01 UTC; myersta
Author: Timothy A. Myers [cre], Mitchell J. Machiela [aut]
Repository: CRAN
Date/Publication: 2019-08-01 12:50:17 UTC

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New package censusxy with initial version 0.1.1
Package: censusxy
Title: Access the U.S. Census Bureau Geocoder
Version: 0.1.1
Authors@R: c( person("Christopher", "Prener", ,"chris.prener@slu.edu", c("aut", "cre"), comment = c(ORCID = "0000-0002-4310-9888")), person("Branson", "Fox", ,"branson.fox@slu.edu", c("aut"), comment = c(ORCID = "0000-0002-4361-2811")) )
Description: Provides access to the U.S. Census Bureau's API for batch geocoding American street addresses (<https://geocoding.geo.census.gov/geocoder>). The package offers a batch solution for address geocoding, as opposed to geocoding a single address at a time. It has also been developed specifically with large data sets in mind - only unique addresses are passed to the API for geocoding. If a data set exceeds 1,000 unique addresses, it will be automatically subset into appropriately sized API calls, geocoded, and then put back together so that a single object is returned.
Depends: R (>= 3.3)
License: GPL-3
URL: https://github.com/slu-openGIS/censusxy
BugReports: https://github.com/slu-openGIS/censusxy/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: dplyr, httr, readr, rlang, sf, tibble, tidyr
Suggests: covr, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-22 19:34:34 UTC; chris
Author: Christopher Prener [aut, cre] (<https://orcid.org/0000-0002-4310-9888>), Branson Fox [aut] (<https://orcid.org/0000-0002-4361-2811>)
Maintainer: Christopher Prener <chris.prener@slu.edu>
Repository: CRAN
Date/Publication: 2019-08-01 12:30:02 UTC

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New package tfCox with initial version 0.1.0
Package: tfCox
Type: Package
Title: Fits Piecewise Polynomial with Data-Adaptive Knots in Cox Model
Version: 0.1.0
Date: 2019-07-29
Authors@R: c(person("Jiacheng","Wu",email="wujiacheng1992@gmail.com", role=c("aut","cre")), person("Daniela","Witten",role=c("aut")), person("Taylor","Arnold",role=c("ctb")), person("Veeranjaneyulu", "Sadhanala", role=c("ctb")), person("Ryan", "Tibshirani", role=c("ctb")))
Description: In Cox's proportional hazard model, covariates are modeled as linear function and may not be flexible. This package implements additive trend filtering Cox proportional hazards model as proposed in Jiacheng Wu & Daniela Witten (2019) "Flexible and Interpretable Models for Survival Data", Journal of Computational and Graphical Statistics, <DOI:10.1080/10618600.2019.1592758>. The fitted functions are piecewise polynomial with adaptively chosen knots.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.14), survival, stats
LinkingTo: Rcpp
NeedsCompilation: yes
Author: Jiacheng Wu [aut, cre], Daniela Witten [aut], Taylor Arnold [ctb], Veeranjaneyulu Sadhanala [ctb], Ryan Tibshirani [ctb]
Maintainer: Jiacheng Wu <wujiacheng1992@gmail.com>
Repository: CRAN
Packaged: 2019-07-30 04:37:35 UTC; wujiacheng
Date/Publication: 2019-08-01 11:50:03 UTC

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New package baggr with initial version 0.1.0
Package: baggr
Type: Package
Title: Bayesian Aggregate Treatment Effects
Version: 0.1.0
Authors@R: c(person("Witold", "Wiecek", email = "witold.wiecek@gmail.com", role = c("cre", "aut")), person("Rachael", "Meager", role="aut"), person("Trustees of", "Columbia University", role = "cph", comment = "tools/make_cc.R"))
Maintainer: Witold Wiecek <witold.wiecek@gmail.com>
Description: Running and comparing meta-analyses of data with hierarchical Bayesian models in Stan, including convenience functions for formatting data, plotting and pooling measures specific to meta-analysis.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 3.5.0), Rcpp (>= 0.12.17), methods
Imports: rstan (>= 2.18.1), rstantools (>= 1.5.0), bayesplot, crayon, ggplot2, gridExtra, utils, stats
LinkingTo: StanHeaders (>= 2.18.1), rstan (>= 2.18.1), BH (>= 1.66.0-1), Rcpp (>= 0.12.17), RcppEigen (>= 0.3.3.4.0)
SystemRequirements: GNU make
NeedsCompilation: yes
RoxygenNote: 6.1.1
Suggests: testthat, knitr
VignetteBuilder: knitr
URL: https://github.com/wwiecek/baggr
BugReports: https://github.com/wwiecek/baggr/issues
Language: en-GB
Packaged: 2019-07-29 21:38:47 UTC; wwiecek
Author: Witold Wiecek [cre, aut], Rachael Meager [aut], Trustees of Columbia University [cph] (tools/make_cc.R)
Repository: CRAN
Date/Publication: 2019-08-01 11:30:02 UTC

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New package tidypmc with initial version 1.7
Package: tidypmc
Type: Package
Title: Parse Full Text XML Documents from PubMed Central
Version: 1.7
Authors@R: person("Chris", "Stubben", role = c("aut", "cre"), email = "chris.stubben@hci.utah.edu")
Description: Parse XML documents from the Open Access subset of Europe PubMed Central <https://europepmc.org> including section paragraphs, tables, captions and references.
URL: https://github.com/cstubben/tidypmc
BugReports: https://github.com/ropensci/tidypmc/issues
License: GPL-3
Encoding: UTF-8
VignetteBuilder: knitr
Imports: xml2, tokenizers, stringr, tibble, dplyr, readr
Suggests: europepmc, tidytext, rmarkdown, knitr, testthat, covr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-29 17:41:47 UTC; chrisstubben
Author: Chris Stubben [aut, cre]
Maintainer: Chris Stubben <chris.stubben@hci.utah.edu>
Repository: CRAN
Date/Publication: 2019-08-01 10:40:02 UTC

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New package mlr3db with initial version 0.1.1
Package: mlr3db
Title: Data Base Backend for 'mlr3'
Version: 0.1.1
Authors@R: person(given = "Michel", family = "Lang", role = c("cre", "aut"), email = "michellang@gmail.com", comment = c(ORCID = "0000-0001-9754-0393"))
Description: Extends the 'mlr3' package with a backend to transparently work with data bases. Internally relies on the abstraction of package 'dbplyr' to interact with one of the many supported data base management systems (DBMS).
License: LGPL-3
URL: https:///mlr3db.mlr-org.com
BugReports: https://github.com/mlr-org/mlr3db/issues
Depends: R (>= 3.1.0)
Imports: checkmate, data.table, digest, dplyr, mlr3 (>= 0.1.1), R6
Suggests: DBI, dbplyr, lgr, RSQLite, testthat, tibble
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-29 08:38:08 UTC; lang
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>)
Maintainer: Michel Lang <michellang@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-01 10:10:02 UTC

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New package exactextractr with initial version 0.1.0
Package: exactextractr
Title: Fast Extraction from Raster Datasets using Polygons
Version: 0.1.0
Authors@R: c( person("Daniel Baston", email = "dbaston@isciences.com", role = c("aut", "cre")), person("ISciences, LLC", role="cph"))
Description: Provides a replacement for the 'extract' function from the 'raster' package that is suitable for extracting raster values using 'sf' polygons.
Depends: R (>= 3.4.0)
License: Apache License (== 2.0)
Imports: Rcpp (>= 0.12.12), methods, raster, sf,
LinkingTo: Rcpp
Suggests: testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-07-29 18:43:00 UTC; dbaston
Author: Daniel Baston [aut, cre], ISciences, LLC [cph]
Maintainer: Daniel Baston <dbaston@isciences.com>
Repository: CRAN
Date/Publication: 2019-08-01 11:00:03 UTC

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New package DGLMExtPois with initial version 0.1.0
Package: DGLMExtPois
Type: Package
Title: Double Generalized Linear Models Extending Poisson Regression
Version: 0.1.0
Authors@R: c( person("Antonio Jose", "Saez-Castillo", role = c("aut"), email = "ajsaez@ujaen.es"), person("Antonio", "Conde-Sanchez", role = c("aut"), email = "aconde@ujaen.es"), person("Francisco", "Martinez", role = c("aut", "cre"), email = "fmartin@ujaen.es"))
Maintainer: Francisco Martinez <fmartin@ujaen.es>
Description: Model estimation, dispersion testing and diagnosis of hyper-Poisson Saez-Castillo, A.J. and Conde-Sanchez, A. (2013) <doi:10.1016/j.csda.2012.12.009> and Conway-Maxwell-Poisson Huang, A. (2017) <doi:10.1177/1471082X17697749> regression models.
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: compoisson, nloptr (>= 1.2.1), COMPoissonReg, progress
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-29 10:48:47 UTC; Paco
Author: Antonio Jose Saez-Castillo [aut], Antonio Conde-Sanchez [aut], Francisco Martinez [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-01 10:10:05 UTC

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New package ClustImpute with initial version 0.1.3
Package: ClustImpute
Type: Package
Title: K-means clustering with build-in missing data imputation
Version: 0.1.3
Author: Oliver Pfaffel
Maintainer: Oliver Pfaffel <opfaffel@gmail.com>
Description: This clustering algorithm deals with missing data via weights that are imposed on missings and succesively increased. See the vignette for details.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: ClusterR, copula, dplyr, magrittr, rlang
Suggests: psych, ggplot2, knitr, rmarkdown, testthat (>= 2.1.0), tidyr, Hmisc, tictoc, spelling, corrplot, covr
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Language: en-US
NeedsCompilation: no
Packaged: 2019-07-28 17:52:58 UTC; opfaf
Repository: CRAN
Date/Publication: 2019-08-01 10:50:02 UTC

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New package tdigest with initial version 0.3.0
Package: tdigest
Type: Package
Title: Wicked Fast, Accurate Quantiles Using t-Digests
Version: 0.3.0
Date: 2019-07-25
Authors@R: c( person("Bob", "Rudis", email = "bob@rud.is", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5670-2640")), person("Ted", "Dunning", role = "aut", comment = "t-Digest algorithm; <https://github.com/tdunning/t-digest/>"), person("Andrew", "Werner", role = "aut", comment = "Original C+ code; <https://github.com/ajwerner/tdigest>") )
Description: The t-Digest construction algorithm, by Dunning et al., (2019) <arXiv:1902.04023v1>, uses a variant of 1-dimensional k-means clustering to produce a very compact data structure that allows accurate estimation of quantiles. This t-Digest data structure can be used to estimate quantiles, compute other rank statistics or even to estimate related measures like trimmed means. The advantage of the t-Digest over previous digests for this purpose is that the t-Digest handles data with full floating point resolution. The accuracy of quantile estimates produced by t-Digests can be orders of magnitude more accurate than those produced by previous digest algorithms. Methods are provided to create and update t-Digests and retrieve quantiles from the accumulated distributions.
URL: https://gitlab.com/hrbrmstr/tdigest
BugReports: https://gitlab.com/hrbrmstr/tdigest/issues
Copyright: file inst/COPYRIGHTS
Encoding: UTF-8
License: MIT + file LICENSE
Suggests: testthat, covr, spelling
Depends: R (>= 3.5.0)
Imports: magrittr, stats
RoxygenNote: 6.1.1
Language: en-US
NeedsCompilation: yes
Packaged: 2019-07-28 11:39:55 UTC; bob
Author: Bob Rudis [aut, cre] (<https://orcid.org/0000-0001-5670-2640>), Ted Dunning [aut] (t-Digest algorithm; <https://github.com/tdunning/t-digest/>), Andrew Werner [aut] (Original C+ code; <https://github.com/ajwerner/tdigest>)
Maintainer: Bob Rudis <bob@rud.is>
Repository: CRAN
Date/Publication: 2019-08-01 09:10:02 UTC

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New package rbart with initial version 1.0
Package: rbart
Type: Package
Title: Bayesian Trees for Conditional Mean and Variance
Version: 1.0
Date: 2019-07-28
Authors@R: c(person('Robert', 'McCulloch', role=c('aut','cre','cph'),email='robert.e.mcculloch@gmail.com'), person('Matthew', 'Pratola', role=c('aut','cph')), person('Hugh','Chipman',role=c('aut','cph')))
Description: A model of the form Y = f(x) + s(x) Z is fit where functions f and s are modeled with ensembles of trees and Z is standard normal. This model is developed in the paper 'Heteroscedastic BART Via Multiplicative Regression Trees' (Pratola, Chipman, George, and McCulloch, 2019, <arXiv:1709.07542v2>). BART refers to Bayesian Additive Regression Trees. See the R-package 'BART'. The predictor vector x may be high dimensional. A Markov Chain Monte Carlo (MCMC) algorithm provides Bayesian posterior uncertainty for both f and s. The MCMC uses the recent innovations in Efficient Metropolis--Hastings proposal mechanisms for Bayesian regression tree models (Pratola, 2015, Bayesian Analysis, <doi:10.1214/16-BA999>).
License: GPL (>= 2)
Depends: R (>= 2.10)
Imports: Rcpp (>= 0.12.3)
Suggests: knitr, rmarkdown, MASS, nnet
LinkingTo: Rcpp
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2019-07-28 16:17:05 UTC; rob
Author: Robert McCulloch [aut, cre, cph], Matthew Pratola [aut, cph], Hugh Chipman [aut, cph]
Maintainer: Robert McCulloch <robert.e.mcculloch@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-01 09:20:02 UTC

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New package LDATS with initial version 0.2.4
Package: LDATS
Title: Latent Dirichlet Allocation Coupled with Time Series Analyses
Version: 0.2.4
Authors@R: c( person(c("Juniper", "L."), "Simonis", email = "juniper.simonis@weecology.org", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9798-0460")), person(c("Erica", "M."), "Christensen", role = c("aut"), comment = c(ORCID = "0000-0002-5635-2502")), person(c("David", "J."), "Harris", role = c("aut"), comment = c(ORCID = "0000-0003-3332-9307")), person(c("Renata", "M."), "Diaz", role = c("aut"), comment = c(ORCID = "0000-0003-0803-4734")), person("Hao", "Ye", role = c("aut"), comment = c(ORCID = "0000-0002-8630-1458")), person(c("Ethan", "P."), "White", role = c("aut"), comment = c(ORCID = "0000-0001-6728-7745")), person(c("S.K.", "Morgan"), "Ernest", role = c("aut"), comment = c(ORCID = "0000-0002-6026-8530")), person(c("Weecology"), role = "cph"))
Description: Combines Latent Dirichlet Allocation (LDA) and Bayesian multinomial time series methods in a two-stage analysis to quantify dynamics in high-dimensional temporal data. LDA decomposes multivariate data into lower-dimension latent groupings, whose relative proportions are modeled using generalized Bayesian time series models that include abrupt changepoints and smooth dynamics. The methods are described in Blei et al. (2003) <doi:10.1162/jmlr.2003.3.4-5.993>, Western and Kleykamp (2004) <doi:10.1093/pan/mph023>, Venables and Ripley (2002, ISBN-13:978-0387954578), and Christensen et al. (2018) <doi:10.1002/ecy.2373>.
URL: https://weecology.github.io/LDATS, https://github.com/weecology/LDATS
BugReports: https://github.com/weecology/LDATS/issues
Depends: R (>= 3.2.3)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: coda, digest, dplyr, extraDistr, graphics, grDevices, here, lubridate, magrittr, memoise, methods, mvtnorm, nnet, progress, reshape, stats, topicmodels, viridis
Suggests: knitr, pkgdown, rmarkdown, testthat, vdiffr, clue, RCurl, tidyr
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-29 04:12:17 UTC; UF
Author: Juniper L. Simonis [aut, cre] (<https://orcid.org/0000-0001-9798-0460>), Erica M. Christensen [aut] (<https://orcid.org/0000-0002-5635-2502>), David J. Harris [aut] (<https://orcid.org/0000-0003-3332-9307>), Renata M. Diaz [aut] (<https://orcid.org/0000-0003-0803-4734>), Hao Ye [aut] (<https://orcid.org/0000-0002-8630-1458>), Ethan P. White [aut] (<https://orcid.org/0000-0001-6728-7745>), S.K. Morgan Ernest [aut] (<https://orcid.org/0000-0002-6026-8530>), Weecology [cph]
Maintainer: Juniper L. Simonis <juniper.simonis@weecology.org>
Repository: CRAN
Date/Publication: 2019-08-01 09:50:02 UTC

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New package idmodelr with initial version 0.3.0
Package: idmodelr
Type: Package
Version: 0.3.0
Title: Infectious Disease Model Library and Utilities
Authors@R: person(given = "Sam Abbott", role = c("aut", "cre"), email = "contact@samabbott.co.uk", comment = c(ORCID = "0000-0001-8057-8037"))
Description: Explore a range of infectious disease models in a consistent framework. The primary aim of 'idmodelr' is to provide a library of infectious disease models for researchers, students, and other interested individuals. These models can be used to understand the underlying dynamics and as a reference point when developing models for research. 'idmodelr' also provides a range of utilities. These include: plotting functionality; a simulation wrapper; scenario analysis tooling; an interactive dashboard; tools for handling mult-dimensional models; and both model and parameter look up tables. Unlike other modelling packages such as 'pomp' (<https://kingaa.github.io/pomp/>), 'libbi' (<http://libbi.org>) and 'EpiModel' (<http://www.epimodel.or>), 'idmodelr' serves primarily as an educational resource. It is most comparable to epirecipes (<http://epirecip.es/epicookbook/chapters/simple>) but provides a more consistent framework, an R based workflow, and additional utility tooling. After users have explored model dynamics with 'idmodelr' they may then implement their model using one of these packages in order to utilise the model fitting tools they provide. For newer modellers, this package reduces the barrier to entry by containing multiple infectious disease models, providing a consistent framework for simulation and visualisation, and signposting towards other, more research focussed, resources.
License: GPL-3
Depends: R (>= 3.3.0)
Imports: dplyr (>= 0.8.3), rlang (>= 0.4.0), ggplot2 (>= 3.2.0), viridis (>= 0.5.1), magrittr (>= 1.5), purrr (>= 0.3.2), future (>= 1.14.0), furrr (>= 0.1.0), stringr (>= 1.4.0), tibble (>= 2.1.3), tidyr (>= 0.8.3), deSolve (>= 1.24)
Suggests: testthat (>= 2.1.1), rmarkdown (>= 1.14), knitr (>= 1.23), pkgnet (>= 0.4.0), DT (>= 0.7), vdiffr (>= 0.3.1)
VignetteBuilder: knitr
URL: http://www.samabbott.co.uk/idmodelr, https://github.com/seabbs/idmodelr
BugReports: https://github.com/seabbs/idmodelr/issues
Encoding: UTF-8
RoxygenNote: 6.1.1
LazyData: true
Language: en-GB
NeedsCompilation: no
Packaged: 2019-07-28 17:54:34 UTC; seabbs
Author: Sam Abbott [aut, cre] (<https://orcid.org/0000-0001-8057-8037>)
Maintainer: Sam Abbott <contact@samabbott.co.uk>
Repository: CRAN
Date/Publication: 2019-08-01 09:20:05 UTC

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New package aaSEA with initial version 1.0.0
Package: aaSEA
Type: Package
Title: Amino Acid Substitution Effect Analyser
Version: 1.0.0
Author: Raja Sekhara Reddy D.M
Maintainer: Raja Sekhara Reddy D.M <raja.duvvuru@gmail.com>
Description: Given a protein multiple sequence alignment, it is daunting task to assess the effects of substitutions along sequence length. 'aaSEA' package is intended to help researchers to rapidly analyse property changes caused by single, multiple and correlated amino acid substitutions in proteins. Methods for identification of co-evolving positions from multiple sequence alignment are as described in : Pelé et al., (2017) <doi:10.4172/2379-1764.1000250>.
Depends: R(>= 3.4.0)
Imports: DT(>= 0.4), networkD3(>= 0.4), shiny(>= 1.0.5), shinydashboard(>= 0.7.0), magrittr(>= 1.5), Bios2cor(>= 1.2), seqinr(>= 3.4-5), plotly(>= 4.7.1), Hmisc(>= 4.1-1)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-28 14:50:25 UTC; sai
Repository: CRAN
Date/Publication: 2019-08-01 09:10:06 UTC

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New package poismf with initial version 0.1.1
Package: poismf
Type: Package
Title: Factorization of Sparse Counts Matrices Through Poisson Likelihood
Version: 0.1.1
Date: 2019-07-25
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>
Description: Creates a low-rank factorization of a sparse counts matrix by maximizing Poisson likelihood with l1/l2 regularization with all non-negative latent factors (e.g. for recommender systems or topic modeling) (Cortes, David, 2018, <arXiv:1811.01908>). Similar to hierarchical Poisson factorization, but follows an optimization-based approach with regularization instead of a hierarchical structure, and is fit through either proximal gradient or conjugate gradient instead of variational inference.
License: BSD_2_clause + file LICENSE
Imports: Rcpp (>= 0.12.19), Matrix, SparseM, methods, nonneg.cg
LinkingTo: Rcpp
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-07-28 10:11:58 UTC; david
Repository: CRAN
Date/Publication: 2019-08-01 09:00:03 UTC

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Wed, 31 Jul 2019

New package nlr with initial version 0.1-3
Package: nlr
Type: Package
Title: Nonlinear Regression Modelling using Robust Methods
Version: 0.1-3
Date: 2019-07-30
Author: Hossein Riazoshams
Maintainer: Hossein Riazoshams <riazihosein@gmail.com>
Description: Non-Linear Robust package is developed to handle the problem of outliers in nonlinear regression, using robust statistics. It covers classic methods in nonlinear regression as well. It has facilities to fit models in the case of auto correlated and heterogeneous variance cases, while it include tools to detecting outliers in nonlinear regression. (Riazoshams H, Midi H, and Ghilagaber G, (2018, ISBN:978-1-118-73806-1). Robust Nonlinear Regression, with Application using R, John Wiley and Sons.)
License: GPL-2
LazyData: yes
Imports: MASS,nlme, robcor, TSA,tseries,stats, GA, quantreg
Depends: R (>= 3.6.0), methods
URL: http://www.riazoshams.com/nlr/
NeedsCompilation: no
Packaged: 2019-07-30 18:26:33 UTC; HRIAZ
Repository: CRAN
Date/Publication: 2019-07-31 12:40:02 UTC

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New package RJafroc with initial version 1.2.0
Package: RJafroc
Type: Package
Title: Analyzing Diagnostic Observer Performance Studies
Version: 1.2.0
Date: 2019-07-21
Authors@R: c(person("Dev", "Chakraborty", role = c("cre","aut","cph"), email = "dpc10ster@gmail.com"), person("Peter", "Philips", role = c("aut"), email = "peter.phillips@cumbria.ac.uk"), person("Xuetong", "Zhai", role = c("aut"), email = "xuetong.zhai@gmail.com"), person("Lucy","D'Agostino McGowan", role = c("ctb"), email = "ld.mcgowan@vanderbilt.edu"), person("Alejandro","RodriguezRuiz", role = c("ctb"), email = "Alejandro.RodriguezRuiz@radboudumc.nl"))
Depends: R (>= 3.5.0)
Imports: bbmle, binom, dplyr, ggplot2, mvtnorm, numDeriv, openxlsx, Rcpp, stats, stringr, tools, utils
Suggests: testthat, knitr, rmarkdown
LinkingTo: Rcpp
Description: Tools for quantitative assessment of medical imaging systems, radiologists or computer aided detection ('CAD') algorithms. Implements methods described in the book: 'Chakraborty' (2017) <ISBN:978-1482214840>. Data collection paradigms include receiver operating characteristic ('ROC') and a location specific extension, namely free-response 'ROC' ('FROC'). 'ROC' data consists of a single rating per image, where the rating is the perceived confidence level the image is of a diseased patient. 'FROC' data consists of a variable number (including zero) of mark-rating pairs per image, where a mark is the location of a clinically relevant suspicious region and the rating is the corresponding confidence level that it is a true lesion. The name 'RJafroc' is derived from it being an enhanced R version of original Windows 'JAFROC' <http://www.devchakraborty.com>. Implemented are a number of figures of merit quantifying performance, functions for visualizing operating characteristics and three ROC ratings data curve-fitting algorithms: the 'binormal' model ('BM'), the contaminated 'binormal' model ('CBM') and the 'radiological' search model ('RSM') 'Chakraborty' (2006) <{doi:10.1088/0031-9155/51/14/012}> . Also implemented is maximum likelihood fitting of paired ROC data, utilizing the correlated 'CBM' model ('CORCBM') model. Unlike the 'BM', which predicts 'improper' ROC curves, 'CBM', 'CORCBM' and the 'RSM' predict proper ROC curves that do not cross the chance diagonal. 'RSM' fitting yields measures of search and lesion-classification performances, in addition to the usual case-classification performance measured by the area under the 'ROC' curve. Search performance is the ability to find lesions while avoiding finding non-lesions. Lesion-classification performance is the ability to discriminate between found lesions and non-lesions. A number of significance testing algorithms are implement. For fully-crossed factorial study designs, termed multiple-reader multiple-case, significance testing of reader-averaged figure-of-merit differences between 'modalities' is implemented using either 'pseudovalue'-based or figure of merit-based methods. Single treatment analysis allows comparison of performance of a group of radiologists to a specified value, or comparison of 'CAD' performance to a group of radiologists interpreting the same cases. Sample size estimation tools are provided for 'ROC' and 'FROC' studies that allow estimation of relevant variances from a pilot study, in order to predict required numbers of readers and cases in a pivotal study. Utility and data file manipulation functions allow data to be read in any of the currently used input formats, including Excel, and the results of the analysis can be viewed in text or Excel output files.
VignetteBuilder: knitr
License: GPL-3
LazyData: true
URL: https://dpc10ster.github.io/RJafroc/
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-07-31 01:29:07 UTC; Dev
Author: Dev Chakraborty [cre, aut, cph], Peter Philips [aut], Xuetong Zhai [aut], Lucy D'Agostino McGowan [ctb], Alejandro RodriguezRuiz [ctb]
Maintainer: Dev Chakraborty <dpc10ster@gmail.com>
Repository: CRAN
Date/Publication: 2019-07-31 11:20:02 UTC

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New package GOFShiny with initial version 0.1.0
Package: GOFShiny
Type: Package
Title: Interactive Document for Working with Goodness of Fit Analysis
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive document on the topic of goodness of fit analysis using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at <https://predanalyticssessions1.shinyapps.io/ChiSquareGOF/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,rmarkdown,stats,rhandsontable
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-27 18:02:09 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-07-31 09:30:03 UTC

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New package outliertree with initial version 1.0
Package: outliertree
Type: Package
Title: Explainable Outlier Detection Through Decision Tree Conditioning
Version: 1.0
Date: 2019-07-23
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>
URL: https://github.com/david-cortes/outliertree
BugReports: https://github.com/david-cortes/outliertree/issues
Description: Will try to fit decision trees that try to "predict" values for each column based on the values of each other column. Along the way, each time a split is evaluated, it will take the observations that fall into each branch as a homogeneous cluster in which it will search for outliers in the 1-d distribution of the column being predicted. Outliers are determined according to confidence intervals on this 1-d distribution, and need to have a large gap with respect to the next observation in sorted order to be flagged as outliers. Since outliers are searched for in a decision tree branch, it will know the conditions that make it a rare observation compared to others that meet the same conditions, and the conditions will always be correlated with the target variable (as it's being predicted from them). Loosely based on the 'GritBot' <https://www.rulequest.com/gritbot-info.html> software.
License: GPL (>= 3)
Imports: Rcpp (>= 1.0.1)
Depends: R (>= 3.5.0)
LinkingTo: Rcpp, Rcereal
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-07-27 10:23:24 UTC; david
Repository: CRAN
Date/Publication: 2019-07-31 08:30:02 UTC

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New package segRDA with initial version 1.0.2
Package: segRDA
Version: 1.0.2
Date: 2019-07-06
Title: Modeling Non-Continuous Linear Responses of Ecological Data
Author: Danilo C Vieira <vieiradc@yahoo.com.br>, Gustavo Fonseca <gfonseca.unifesp@gmail.com>, and Fabio Cop Ferreira <fabiocferreira.unifesp@gmail.com>, with contributions from Marco Colossi Brustolin.
Maintainer: Danilo C Vieira <vieiradc@yahoo.com.br>
Description: Tools for modeling non-continuous linear responses of ecological communities to environmental data. The package is straightforward through three steps: (1) data ordering (function OrdData()), (2) split-moving-window analysis (function SMW()) and (3) piecewise redundancy analysis (function pwRDA()). Relevant references include Cornelius and Reynolds (1991) <doi:10.2307/1941559> and Legendre and Legendre (2012, ISBN: 9780444538697).
Depends: R (>= 2.15), vegan (>= 2.4)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
URL: https://github.com/DaniloCVieira/segRDA
BugReports: https://github.com/DaniloCVieira/segRDA/issues
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2019-07-26 20:06:34 UTC; Danilo
Repository: CRAN
Date/Publication: 2019-07-31 07:30:02 UTC

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New package activityCounts with initial version 0.1.2
Package: activityCounts
Type: Package
Title: Generate ActiLife Counts
Version: 0.1.2
Authors@R: c( person("Ruben", "Brondeel", role = "aut"), person("Javad", "Rahimipour Anaraki", role = "aut"), person("SeyedJavad", "KhataeiPour", role = c("aut", "cre"), email = "skhataeipour@mun.ca"), person("Daniel", "Fuller", role = c("aut", "cph")), person(family = "Beap Lab", role = "cph") )
Description: ActiLife software generates activity counts from data collected by Actigraph accelerometers <https://s3.amazonaws.com/actigraphcorp.com/wp-content/uploads/2017/11/26205758/ActiGraph-White-Paper_What-is-a-Count_.pdf>. Actigraph is one of the most common research-grade accelerometers. There is considerable research validating and developing algorithms for human activity using ActiLife counts. Unfortunately, ActiLife counts are proprietary and difficult to implement if researchers use different accelerometer brands. The code creates ActiLife counts from raw acceleration data for different accelerometer brands and it is developed based on the study done by Brond and others (2017) <doi:10.1249/MSS.0000000000001344>.
URL: https://github.com/walkabillylab/activityCounts, https://github.com/jbrond/ActigraphCounts
BugReports: https://github.com/walkabillylab/activityCounts/issues
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
Imports: seewave, signal, tibble, lubridate, magrittr
NeedsCompilation: no
Packaged: 2019-07-26 14:41:51 UTC; dfuller
Author: Ruben Brondeel [aut], Javad Rahimipour Anaraki [aut], SeyedJavad KhataeiPour [aut, cre], Daniel Fuller [aut, cph], Beap Lab [cph]
Maintainer: SeyedJavad KhataeiPour <skhataeipour@mun.ca>
Repository: CRAN
Date/Publication: 2019-07-31 07:30:04 UTC

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Tue, 30 Jul 2019

New package shinyML with initial version 0.1.0
Package: shinyML
Type: Package
Title: Compare H20 or Spark Supervised Regression Models Using Shiny App
Version: 0.1.0
Author: Jean Bertin
Maintainer: Jean Bertin <jean.bertin@gadz.org>
Description: Implementation of a shiny app to easily compare supervised regression model performances. You provide the data and configure each model parameter directly on the shiny app. Four main supervised learning algorithms can be tested either on Spark or H2O frameworks to suit your regression problem on a given time series. Implementation of these time series forecasting methods on R has been done by Shmueli and Lichtendahl (2015, ISBN:0991576632).
License: GPL-3
Encoding: UTF-8
Imports: shiny(>= 1.0.3), shinydashboard, h2o, shinyWidgets, dygraphs, plotly, sparklyr, tidyr, DT, ggplot2, shinycssloaders
Suggests: knitr, rmarkdown, covr, testthat
Depends: dplyr, data.table
LazyData: True
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-26 13:33:46 UTC; BERTIN
Repository: CRAN
Date/Publication: 2019-07-30 08:40:02 UTC

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New package MVTests with initial version 1.1
Package: MVTests
Type: Package
Title: Multivariate Hypothesis Tests
Version: 1.1
Date: 2019-07-30
Author: Hasan Bulut
Maintainer: Hasan Bulut <hasan.bulut@omu.edu.tr>
Description: Multivariate hypothesis tests and the confidence intervals. This package can be used for hypothesis tests which are The Hotelling T Square Tests (One-Sample, Two Independent Samples, Paired Samples), The One Way MANOVA,The Multivariate Shapiro-Wilk Test for Multivariate Normality Test, The Bartlett Test for One Sample Covariance Matrix, The Box-M Test and The Bartlett's Sphericity Test. For this package, we have benefited the studies Rencher (2003), Nel and Merwe (1986) <DOI: 10.1080/03610928608829342>, Tatlidil (1996), James (1994) <DOI: 10.2307/2333003>, Tsagris (2014), Villasenor Alva and Estrada (2009) <DOI: 10.1080/03610920802474465>.
Depends: R (>= 2.0), stats, matrixcalc
LazyData: true
License: GPL-3
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-30 06:42:11 UTC; user
Repository: CRAN
Date/Publication: 2019-07-30 08:30:04 UTC

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New package onelogin with initial version 0.1.0
Package: onelogin
Type: Package
Title: Interact with the 'OneLogin' API
Version: 0.1.0
Authors@R: c(person("Alex", "Gold", email = "alexkgold@gmail.com", role = c("aut", "cre")), person("Cole", "Arendt", email = "cole.arendt@rstudio.com", role = "ctb"))
Description: The identity provider ['OneLogin']<http://onelogin.com> is used for authentication via Single Sign On (SSO). This package provides an R interface to their API.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: R6, glue, safer
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-26 13:53:12 UTC; alexkgold
Author: Alex Gold [aut, cre], Cole Arendt [ctb]
Maintainer: Alex Gold <alexkgold@gmail.com>
Repository: CRAN
Date/Publication: 2019-07-30 08:00:02 UTC

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Mon, 29 Jul 2019

New package MSEtool with initial version 1.2.1
Package: MSEtool
Type: Package
Title: Management Strategy Evaluation Toolkit
Version: 1.2.1
Authors@R: c(person("Quang", "Huynh", email = "q.huynh@oceans.ubc.ca", role = "aut"), person("Tom", "Carruthers", email = "t.carruthers@oceans.ubc.ca", role = c("aut", "cre")), person("Adrian", "Hordyk", email = "a.hordyk@oceans.ubc.ca", role = "aut"), person("Chris", "Grandin", rol = "ctb", comment = "iSCAM functions"))
Date: 2019-07-29
Maintainer: Tom Carruthers <t.carruthers@oceans.ubc.ca>
Description: Simulation tools for management strategy evaluation are provided for the 'DLMtool' operating model to inform data-rich fisheries. 'MSEtool' provides complementary assessment models of varying complexity with standardized reporting, diagnostic tools for evaluating assessment models within closed-loop simulation, and helper functions for building more complex operating models and management procedures.
License: GPL-3
Depends: R (>= 3.3.0), DLMtool (>= 5.3.1)
Imports: MASS, TMB, coda, corpcor, gplots, grDevices, graphics, methods, mvtnorm, pryr, reshape2, snowfall, stats, utils, abind, rmarkdown
LinkingTo: TMB, RcppEigen
LazyData: yes
LazyLoad: yes
RoxygenNote: 6.1.1
Suggests: knitr, testthat, r4ss, shiny
VignetteBuilder: knitr
URL: http://www.datalimitedtoolkit.org
BugReports: https://github.com/tcarruth/MSEtool/issues
NeedsCompilation: yes
Packaged: 2019-07-29 21:26:04 UTC; qhuynh
Author: Quang Huynh [aut], Tom Carruthers [aut, cre], Adrian Hordyk [aut], Chris Grandin [ctb] (iSCAM functions)
Repository: CRAN
Date/Publication: 2019-07-29 23:10:02 UTC

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New package fieldRS with initial version 0.2.2
Package: fieldRS
Type: Package
Title: Remote Sensing Field Work Tools
Version: 0.2.2
Date: 2019-07-29
Authors@R: person("Ruben", "Remelgado", role = c("aut", "cre"), email="remelgado.ruben@gmail.com")
URL: https://github.com/RRemelgado/fieldRS/
BugReports: https://github.com/RRemelgado/fieldRS/issues/
Maintainer: Ruben Remelgado <remelgado.ruben@gmail.com>
Description: In remote sensing, designing a field campaign to collect ground-truth data can be a challenging task. We need to collect representative samples while accounting for issues such as budget constraints and limited accessibility created by e.g. poor infrastructure. As suggested by Olofsson et al. (2014) <doi:10.1016/j.rse.2014.02.015>, this demands the establishment of best-practices to collect ground-truth data that avoid the waste of time and funds. 'fieldRS' addresses this issue by helping scientists and practitioners design field campaigns through the identification of priority sampling sites, the extraction of potential sampling plots and the conversion of plots into consistent training and validation samples that can be used in e.g. land cover classification.
Encoding: UTF-8
LazyData: TRUE
Imports: raster, sp, caret, ggplot2, grDevices, spatialEco, rgeos, stringdist, concaveman
RoxygenNote: 6.1.1
License: GPL (>= 3)
Suggests: knitr, rmarkdown, kableExtra, imager, randomForest, rgdal, RStoolbox
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-29 15:32:33 UTC; rr70wedu
Author: Ruben Remelgado [aut, cre]
Repository: CRAN
Date/Publication: 2019-07-29 18:30:02 UTC

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New package gitignore with initial version 0.1.3
Type: Package
Package: gitignore
Title: Create Useful .gitignore Files for your Project
Version: 0.1.3
Authors@R: c(person(given = "Philippe", family = "Massicotte", role = c("aut", "cre"), email = "pmassicotte@hotmail.com", comment = c(ORCID = "0000-0002-5919-4116")), person(given = "Amanda", family = "Dobbyn", role = "rev", email = "amanda.e.dobbyn@gmail.com"), person(given = "Mauro", family = "Lepore", role = "rev", email = "maurolepore@gmail.com", comment = c(ORCID = "0000-0002-1986-7988")))
Description: Simple interface to query gitignore.io to fetch gitignore templates that can be included in the .gitignore file. More than 450 templates are currently available.
License: GPL-3
URL: https://github.com/ropensci/gitignore
BugReports: https://github.com/ropensci/gitignore/issues
Imports: clipr, clisymbols, crayon, curl, glue, here, jsonlite, purrr, xfun
Suggests: covr, knitr, rmarkdown, spelling, testthat (>= 2.1.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-19 18:26:37 UTC; pmassicotte
Author: Philippe Massicotte [aut, cre] (<https://orcid.org/0000-0002-5919-4116>), Amanda Dobbyn [rev], Mauro Lepore [rev] (<https://orcid.org/0000-0002-1986-7988>)
Maintainer: Philippe Massicotte <pmassicotte@hotmail.com>
Repository: CRAN
Date/Publication: 2019-07-29 14:20:02 UTC

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New package mixmeta with initial version 0.2.2
Package: mixmeta
Type: Package
Version: 0.2.2
Date: 2019-07-25
Title: An Extended Mixed-Effects Framework for Meta-Analysis
Description: A collection of functions to perform various meta-analytical models through a unified mixed-effects framework, including standard univariate fixed and random-effects meta-analysis and meta-regression, and non-standard extensions such as multivariate, multilevel, longitudinal, and dose-response models.
Author: Antonio Gasparrini [aut, cre], Francesco Sera [aut]
Maintainer: Antonio Gasparrini <antonio.gasparrini@lshtm.ac.uk>
Authors@R: c( person("Antonio","Gasparrini",role=c("aut","cre"),email="antonio.gasparrini@lshtm.ac.uk"), person("Francesco","Sera",role="aut",email="francesco.sera@lshtm.ac.uk"))
Imports: stats, graphics, grDevices, utils
Depends: R (>= 3.5.0)
Suggests: metafor, meta, rmeta, dosresmeta, nlme, MASS, dlnm
URL: https://github.com/gasparrini/mixmeta, http://www.ag-myresearch.com/package-mixmeta
License: GPL (>= 2)
LazyData: yes
NeedsCompilation: no
Packaged: 2019-07-25 23:14:09 UTC; gaspa
Repository: CRAN
Date/Publication: 2019-07-29 12:40:02 UTC

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New package tricolore with initial version 1.2.1
Package: tricolore
Type: Package
Title: A Flexible Color Scale for Ternary Compositions
Version: 1.2.1
Author: Jonas Schöley, Ilya Kashnitsky
Maintainer: Jonas Schöley <jschoeley@gmail.com>
Description: A flexible color scale for ternary compositions with options for discretization, centering and scaling.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: grDevices, ggplot2 (>= 3.0.0), ggtern (>= 3.0.0), shiny, assertthat
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, sf, leaflet, httpuv, dplyr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-19 10:18:46 UTC; jon
Repository: CRAN
Date/Publication: 2019-07-29 11:00:02 UTC

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Sun, 28 Jul 2019

New package rsleep with initial version 1.0.1
Package: rsleep
Type: Package
Title: Analysis of Sleep Data
Version: 1.0.1
Author: Paul Bouchequet <paul.bouchequet@frenchkpi.com>
Maintainer: Paul Bouchequet <paul.bouchequet@frenchkpi.com>
Description: Provides users functions for sleep data management and analysis such as European Data Format (EDF) to Morpheo Data Format (MDF) conversion: P.Bouchequet, D.Jin, G.Solelhac, M.Chennaoui, D.Leger (2018) <doi:10.1016/j.msom.2018.01.130> "Morpheo Data Format (MDF), un nouveau format de donnees simple, robuste et performant pour stocker et analyser les enregistrements de sommeil". Provides hypnogram statistics computing and visualisation functions from the American Academy of Sleep Medicine (AASM) manual "The AASM Manual for the Scoring of Sleep and Associated Events" <https://aasm.org/clinical-resources/scoring-manual/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: edfReader, jsonlite, ggplot2, signal, phonTools
Suggests: testthat
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-07-26 11:26:16 UTC; paul
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-07-28 11:10:02 UTC

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New package metadynminer3d with initial version 0.0.1
Package: metadynminer3d
Type: Package
Title: Tools to Read, Analyze and Visualize Metadynamics 3D HILLS Files from 'Plumed'
Version: 0.0.1
Date: 2019-07-22
Authors@R: person("Vojtech", "Spiwok", email = "spiwokv@vscht.cz", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8108-2033"))
Depends: R (>= 3.3.0), metadynminer, rgl
LinkingTo: Rcpp
Description: Metadynamics is a state of the art biomolecular simulation technique. 'Plumed' Tribello, G.A. et al. (2014) <doi:10.1016/j.cpc.2013.09.018> program makes it possible to perform metadynamics using various simulation codes. The results of metadynamics done in 'Plumed' can be analyzed by 'metadynminer'. The package 'metadynminer' reads 1D and 2D metadynamics hills files from 'Plumed' package. As an addendum, 'metadynaminer3d' is used to visualize 3D hills. It uses a fast algorithm by Hosek, P. and Spiwok, V. (2016) <doi:10.1016/j.cpc.2015.08.037> to calculate a free energy surface from hills. Minima can be located and plotted on the free energy surface. Free energy surfaces and minima can be plotted to produce publication quality images.
LazyData: true
License: GPL-3
RoxygenNote: 6.1.0
Imports: Rcpp, misc3d
Suggests: testthat
URL: http://www.metadynamics.cz/metadynminer3d
NeedsCompilation: yes
Packaged: 2019-07-26 12:19:52 UTC; spiwokv
Author: Vojtech Spiwok [aut, cre] (<https://orcid.org/0000-0001-8108-2033>)
Maintainer: Vojtech Spiwok <spiwokv@vscht.cz>
Repository: CRAN
Date/Publication: 2019-07-28 11:10:04 UTC

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New package longclust with initial version 1.2.3
Package: longclust
Type: Package
Title: Model-Based Clustering and Classification for Longitudinal Data
Version: 1.2.3
Date: 2019-07-23
Authors@R: c(person("Paul D.", "McNicholas", role = c("aut", "cre"), email = "mcnicholas@math.mcmaster.ca"), person("K. Raju", "Jampani", role = "aut", comment = "May to Dec 2012"), person("Sanjeena", "Subedi", role = "aut"))
Author: Paul D. McNicholas [aut, cre], K. Raju Jampani [aut] (May to Dec 2012), Sanjeena Subedi [aut]
Maintainer: Paul D. McNicholas <mcnicholas@math.mcmaster.ca>
Suggests: mvtnorm
Description: Clustering or classification of longitudinal data based on a mixture of multivariate t or Gaussian distributions with a Cholesky-decomposed covariance structure. Details in McNicholas and Murphy (2010) <doi:10.1002/cjs.10047> and McNicholas and Subedi (2012) <doi:10.1016/j.jspi.2011.11.026>.
License: GPL (>= 2)
LazyLoad: yes
Repository: CRAN
NeedsCompilation: yes
Packaged: 2019-07-26 11:57:55 UTC; paul
Date/Publication: 2019-07-28 11:10:06 UTC

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New package IMAGE with initial version 1.0
Package: IMAGE
Title: Integrated Methylation QTL Mapping and Allele-Specific Analysis
Version: 1.0
Date: 2019-06-30
Authors@R: c( person(given = "Xiang", family = "Zhou", role = c("aut"), email = "xzhousph@umich.edu"), person(given = "Shiquan", family = "Sun", role = c("aut")), person(given = "Yue", family = "Fan", role = c("aut"), email = "yuef@umich.edu"), person(given = "Michael", family = "Kleinsasser", role = c("cre"), email = "mkleinsa@umich.edu"))
Description: Performs mQTL (methylation quantitative-trait locus) mapping in bisulfite sequencing studies by fitting a binomial mixed model and then incorporating the allelic-specific methylation pattern. Based on Fan, Yue; Vilgalys, Tauras P.; Sun, Shiquan; Peng, Qinke; Tung, Jenny; Zhou, Xiang (2019) <doi:10.1101/615039>.
License: GPL-2
Imports: Rcpp (>= 0.12.19), foreach, doParallel, parallel, Matrix
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/umich-biostatistics/IMAGE/issues
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-07-26 12:46:21 UTC; mkleinsa
Author: Xiang Zhou [aut], Shiquan Sun [aut], Yue Fan [aut], Michael Kleinsasser [cre]
Maintainer: Michael Kleinsasser <mkleinsa@umich.edu>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-07-28 11:10:08 UTC

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New package rvkstat with initial version 2.6.2
Package: rvkstat
Type: Package
Title: Interface to API 'vk.com'
Version: 2.6.2
Date: 2019-07-26
Author: Alexey Seleznev
Maintainer: Alexey Seleznev <selesnow@gmail.com>
Description: Load data from vk.com api about your communiti users and views, ads performance, post on user wall and etc. For more detail see <https://vk.com/dev/first_guide>.
License: GPL-2
Depends: R (>= 3.5.0)
Imports: RCurl, jsonlite, httr, tidyr
Language: ru
Encoding: UTF-8
BugReports: https://github.com/selesnow/rvkstat/issues
URL: http://selesnow.github.io/rvkstat
NeedsCompilation: no
Packaged: 2019-07-26 11:04:02 UTC; Alsey
Repository: CRAN
Date/Publication: 2019-07-28 11:00:02 UTC

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New package rnbp with initial version 0.1.0
Package: rnbp
Title: Wrapper for the National Bank of Poland API
Version: 0.1.0
Authors@R: person(given = "Ryszard", family = "Szymanski", role = c("aut", "cre"), email = "ryszard.szymanski@outlook.com")
Maintainer: Ryszard Szymanski <ryszard.szymanski@outlook.com>
Description: Use the <http://api.nbp.pl/> API through R. Retrieve currency exchange rates and gold prices data published by the National Bank of Poland in form of convenient R objects.
License: GPL-3
BugReports: https://github.com/szymanskir/rnbp/issues
Encoding: UTF-8
LazyData: true
Imports: curl, httr, jsonlite, utils
Suggests: covr, httptest, testthat (>= 2.1.0), knitr, rmarkdown, ggplot2
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-26 10:38:48 UTC; szymanskir
Author: Ryszard Szymanski [aut, cre]
Repository: CRAN
Date/Publication: 2019-07-28 11:00:04 UTC

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New package samurais with initial version 0.1.0
Type: Package
Package: samurais
Title: Statistical Models for the Unsupervised Segmentation of Time-Series ('SaMUraiS')
Version: 0.1.0
Authors@R: c(person("Faicel", "Chamroukhi", role = c("aut"), email = "faicel.chamroukhi@unicaen.fr", comment = c(ORCID = "0000-0002-5894-3103")), person("Marius", "Bartcus", role = c("aut"), email = "marius.bartcus@gmail.com"), person("Florian", "Lecocq", role = c("aut", "cre"), email = "florian.lecocq@outlook.com"))
Description: Provides a variety of original and flexible user-friendly statistical latent variable models and unsupervised learning algorithms to segment and represent time-series data (univariate or multivariate), and more generally, longitudinal data, which include regime changes. 'samurais' is built upon the following packages, each of them is an autonomous time-series segmentation approach: Regression with Hidden Logistic Process ('RHLP'), Hidden Markov Model Regression ('HMMR'), Multivariate 'RHLP' ('MRHLP'), Multivariate 'HMMR' ('MHMMR'), Piece-Wise regression ('PWR'). For the advantages/differences of each of them, the user is referred to our mentioned paper references.
URL: https://github.com/fchamroukhi/SaMUraiS
License: GPL (>= 3)
Depends: R (>= 2.10)
Imports: methods, stats, MASS, Rcpp
Suggests: knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
Collate: samurais-package.R RcppExports.R utils.R dynamicProg.R fitPWRFisher.R mkStochastic.R hmmProcess.R MData.R ParamHMMR.R ParamMHMMR.R ParamMRHLP.R ParamPWR.R ParamRHLP.R StatHMMR.R StatMHMMR.R StatMRHLP.R StatPWR.R StatRHLP.R ModelHMMR.R ModelMHMMR.R ModelMRHLP.R ModelPWR.R ModelRHLP.R emHMMR.R emMHMMR.R emMRHLP.R emRHLP.R selectHMMR.R selectMHMMR.R selectMRHLP.R selectRHLP.R data-multivrealdataset.R data-multivtoydataset.R data-univrealdataset.R data-univtoydataset.R
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-07-25 16:23:38 UTC; lecocq191
Author: Faicel Chamroukhi [aut] (<https://orcid.org/0000-0002-5894-3103>), Marius Bartcus [aut], Florian Lecocq [aut, cre]
Maintainer: Florian Lecocq <florian.lecocq@outlook.com>
Repository: CRAN
Date/Publication: 2019-07-28 09:50:02 UTC

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