Thu, 30 Apr 2020

New package mokken with initial version 3.0.2
Package: mokken
Version: 3.0.2
Date: 2020-04-27
Title: Conducts Mokken Scale Analysis
Authors@R: c(person("L. Andries", "van der Ark", role = c("aut", "cre"), email = "L.A.vanderArk@uva.nl"), person("Letty", "Koopman", role = "aut"), person("J. Hendrik", "Straat", role = "ctb"), person("Don", "van den Bergh", role = "ctb"))
Author: L. Andries van der Ark [aut, cre], Letty Koopman [aut], J. Hendrik Straat [ctb], Don van den Bergh [ctb]
Maintainer: L. Andries van der Ark <L.A.vanderArk@uva.nl>
Depends: R (>= 3.5.0), graphics, poLCA
Suggests: MASS
Description: Contains functions for performing Mokken scale analysis on test and questionnaire data (e.g., Sijtsma and Van der Ark, 2017, <doi:10.1111/bmsp.12078>). It includes an automated item selection algorithm, and various checks of model assumptions.
License: GPL (>= 2)
URL: https://sites.google.com/a/tilburguniversity.edu/avdrark/mokken
LinkingTo: Rcpp
Imports: Rcpp
NeedsCompilation: yes
Packaged: 2020-04-30 10:58:52 UTC; lvdark1
Repository: CRAN
Date/Publication: 2020-04-30 23:10:02 UTC

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Package jquerylib updated to version 0.1.1 with previous version 0.1 dated 2020-03-19

Title: Obtain 'jQuery' as an HTML Dependency Object
Description: Obtain any major version of 'jQuery' (<https://code.jquery.com/>) and use it in any webpage generated by 'htmltools' (e.g. 'shiny', 'htmlwidgets', and 'rmarkdown'). Most R users don't need to use this package directly, but other R packages (e.g. 'shiny', 'rmarkdown', etc.) depend on this package to avoid bundling redundant copies of 'jQuery'.
Author: Carson Sievert [aut, cre] (<https://orcid.org/0000-0002-4958-2844>), Joe Cheng [aut], RStudio [cph], jQuery Foundation [cph] (jQuery library and jQuery UI library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/lib/jquery-AUTHORS.txt)
Maintainer: Carson Sievert <carson@rstudio.com>

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Package ipumsr updated to version 0.4.3 with previous version 0.4.2 dated 2019-06-04

Title: Read 'IPUMS' Extract Files
Description: An easy way to import census, survey and geographic data provided by 'IPUMS' into R plus tools to help use the associated metadata to make analysis easier. 'IPUMS' data describing 1.4 billion individuals drawn from over 750 censuses and surveys is available free of charge from our website <https://ipums.org>.
Author: Greg Freedman Ellis [aut], Derek Burk [aut, cre], Joe Grover [ctb], Minnesota Population Center [cph]
Maintainer: Derek Burk <ipums+cran@umn.edu>

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Package idiogramFISH updated to version 1.14.11 with previous version 1.14.7 dated 2020-03-28

Title: Idiograms with Marks and Karyotype Indices
Description: Plot idiograms of karyotypes, plasmids, circular chr. having a set of data.frames for chromosome data and optionally mark data. Supports micrometers, cM and Mb. Seven styles of marks are available: square, dots, cM, cMLeft, cenStyle, upArrow, downArrow; its legend (label) can be drawn inline or to the right of karyotypes. Idiograms can also be plotted in concentric circles. It is possible to calculate chromosome indices by Levan et al. (1964) <doi:10.1111/j.1601-5223.1964.tb01953.x>, karyotype indices of Watanabe et al. (1999) <doi:10.1007/PL00013869> and Romero-Zarco (1986) <doi:10.2307/1221906> and classify chromosomes by morphology Guerra (1986) and Levan et al. (1964).
Author: Fernando Roa [aut, cre], Mariana PC Telles [ctb]
Maintainer: Fernando Roa <froao@unal.edu.co>

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Package esvis updated to version 0.3.1 with previous version 0.3.0 dated 2020-02-28

Title: Visualization and Estimation of Effect Sizes
Description: A variety of methods are provided to estimate and visualize distributional differences in terms of effect sizes. Particular emphasis is upon evaluating differences between two or more distributions across the entire scale, rather than at a single point (e.g., differences in means). For example, Probability-Probability (PP) plots display the difference between two or more distributions, matched by their empirical CDFs (see Ho and Reardon, 2012; <doi:10.3102/1076998611411918>), allowing for examinations of where on the scale distributional differences are largest or smallest. The area under the PP curve (AUC) is an effect-size metric, corresponding to the probability that a randomly selected observation from the x-axis distribution will have a higher value than a randomly selected observation from the y-axis distribution. Binned effect size plots are also available, in which the distributions are split into bins (set by the user) and separate effect sizes (Cohen's d) are produced for each bin - again providing a means to evaluate the consistency (or lack thereof) of the difference between two or more distributions at different points on the scale. Evaluation of empirical CDFs is also provided, with built-in arguments for providing annotations to help evaluate distributional differences at specific points (e.g., semi-transparent shading). All function take a consistent argument structure. Calculation of specific effect sizes is also possible. The following effect sizes are estimable: (a) Cohen's d, (b) Hedges' g, (c) percentage above a cut, (d) transformed (normalized) percentage above a cut, (e) area under the PP curve, and (f) the V statistic (see Ho, 2009; <doi:10.3102/1076998609332755>), which essentially transforms the area under the curve to standard deviation units. By default, effect sizes are calculated for all possible pairwise comparisons, but a reference group (distribution) can be specified.
Author: Daniel Anderson [aut, cre]
Maintainer: Daniel Anderson <daniela@uoregon.edu>

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Package estudy2 updated to version 0.9.2 with previous version 0.9.1 dated 2019-12-16

Title: An Implementation of Parametric and Nonparametric Event Study
Description: An implementation of a most commonly used event study methodology, including both parametric and nonparametric tests. It contains variety aspects of the rate of return estimation (the core calculation is done in C++), as well as three classical for event study market models: mean adjusted returns, market adjusted returns and single-index market models. There are 6 parametric and 6 nonparametric tests provided, which examine cross-sectional daily abnormal return (see the documentation of the functions for more information). Parametric tests include tests proposed by Brown and Warner (1980) <DOI:10.1016/0304-405X(80)90002-1>, Brown and Warner (1985) <DOI:10.1016/0304-405X(85)90042-X>, Boehmer et al. (1991) <DOI:10.1016/0304-405X(91)90032-F>, Patell (1976) <DOI:10.2307/2490543>, and Lamb (1995) <DOI:10.2307/253695>. Nonparametric tests covered in estudy2 are tests described in Corrado and Zivney (1992) <DOI:10.2307/2331331>, McConnell and Muscarella (1985) <DOI:10.1016/0304-405X(85)90006-6>, Boehmer et al. (1991) <DOI:10.1016/0304-405X(91)90032-F>, Cowan (1992) <DOI:10.1007/BF00939016>, Corrado (1989) <DOI:10.1016/0304-405X(89)90064-0>, Campbell and Wasley (1993) <DOI:10.1016/0304-405X(93)90025-7>, Savickas (2003) <DOI:10.1111/1475-6803.00052>, Kolari and Pynnonen (2010) <DOI:10.1093/rfs/hhq072>. Furthermore, tests for the cumulative abnormal returns proposed by Brown and Warner (1985) <DOI:10.1016/0304-405X(85)90042-X> and Lamb (1995) <DOI:10.2307/253695> are included.
Author: Iegor Rudnytskyi [aut, cre]
Maintainer: Iegor Rudnytskyi <iegor.rudnytskyi@gmail.com>

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Package BsMD updated to version 2020.4.30 with previous version 2013.0718-1 dated 2018-02-01

Title: Bayes Screening and Model Discrimination
Description: Bayes screening and model discrimination follow-up designs.
Author: Ernesto Barrios based on Daniel Meyer's code.
Maintainer: Ernesto Barrios <ebarrios@itam.mx>

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Package utile.tools updated to version 0.2.5 with previous version 0.2.4 dated 2020-03-14

Title: Summarize Data for Publication
Description: A set of tools for preparing and summarizing data for publication purposes. Includes functions for tabulating models, means to produce human-readable summary statistics from raw data, macros for calculating duration of time, and simplistic hypothesis testing tools.
Author: Eric Finnesgard [aut, cre]
Maintainer: Eric Finnesgard <efinite@outlook.com>

Diff between utile.tools versions 0.2.4 dated 2020-03-14 and 0.2.5 dated 2020-04-30

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Package tvReg updated to version 0.5.2 with previous version 0.5.1 dated 2020-04-16

Title: Time-Varying Coefficient Linear Regression for Single and Multi-Equations
Description: Fitting time-varying coefficient models both for single and multi-equation regressions, using kernel smoothing techniques.
Author: Isabel Casas [aut, cre], Ruben Fernandez-Casal [aut]
Maintainer: Isabel Casas <casasis@gmail.com>

Diff between tvReg versions 0.5.1 dated 2020-04-16 and 0.5.2 dated 2020-04-30

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Package StatCharrms updated to version 0.90.95 with previous version 0.90.94 dated 2020-01-15

Title: Statistical Analysis of Chemistry, Histopathology, and Reproduction Endpoints Including Repeated Measures and Multi-Generation Studies
Description: A front end for the statistical analyses involved in the tier II endocrine disruptor screening program. The analyses available to this package are: Rao-Scott adjusted Cochran-Armitage test for trend By Slices (RSCABS), a Standard Cochran-Armitage test for trend By Slices (SCABS), mixed effects Cox proportional model, Jonckheere-Terpstra step down trend test Dunn test, one way ANOVA, weighted ANOVA, mixed effects ANOVA, repeated measures ANOVA, and Dunnett test.
Author: Joe Swintek [aut, cre], Kevin Flynn [ctb], Jon Haselman [ctb], Maki Sakurai [ctb]
Maintainer: Joe Swintek <swintek.joe@epa.gov>

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New package spup with initial version 1.3-2
Package: spup
Type: Package
Title: Spatial Uncertainty Propagation Analysis
Version: 1.3-2
Date: 2020-03-31
Authors@R: c(person("Kasia", "Sawicka", email = "katwic55@ceh.ac.uk", role = c("aut", "cre")), person("Gerard", "Heuvelink", email = "gerard.heuvelink@wur.nl", role = c("aut")), person("Dennis", "Walvoort", email = "dennis.walvoort@wur.nl", role = c("aut")), person("Stefan", "van Dam", email = "stefan.vandam@wur.nl", role = c("ctb")), person("Damiano", "Luzzi", email = "damiano.luzzi@wur.nl", role = c("ctb")) )
Description: Uncertainty propagation analysis in spatial environmental modelling following methodology described in Heuvelink et al. (2007) <doi:10.1080/13658810601063951> and Brown and Heuvelink (2007) <doi:10.1016/j.cageo.2006.06.015>. The package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model outputs. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques. Uncertain variables are described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is accommodated for. The MC realizations may be used as input to the environmental models called from R, or externally.
Depends: R (>= 3.3.0)
Imports: graphics, gstat, magrittr, methods, mvtnorm, purrr, raster, sp, whisker
Suggests: dplyr, GGally, gridExtra, knitr, png, readr, testthat
License: GPL (>= 3)
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.0
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-04-29 15:56:54 UTC; katwic55
Author: Kasia Sawicka [aut, cre], Gerard Heuvelink [aut], Dennis Walvoort [aut], Stefan van Dam [ctb], Damiano Luzzi [ctb]
Maintainer: Kasia Sawicka <katwic55@ceh.ac.uk>
Repository: CRAN
Date/Publication: 2020-04-30 22:20:06 UTC

More information about spup at CRAN
Permanent link

Package sigminer updated to version 1.0.3 with previous version 1.0.0 dated 2020-03-31

Title: Extract, Analyze and Visualize Signatures for Genomic Variations
Description: Genomic alterations including single nucleotide substitution, copy number alteration, etc. are the major force for cancer initialization and development. Due to the specificity of molecular lesions caused by genomic alterations, we can generate characteristic alteration spectra, called 'signature' (Wang, Shixiang, et al. (2020) <DOI:10.1101/2020.04.27.20082404> & Alexandrov, Ludmil B., et al. (2020) <DOI:10.1038/s41586-020-1943-3> & Macintyre, Geoff, et al. (2018) <DOI:10.1038/s41588-018-0179-8>). This package helps users to extract, analyze and visualize signatures from genomic alteration records, thus providing new insight into cancer study.
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>), Xue-Song Liu [aut, ctb] (<https://orcid.org/0000-0002-7736-0077>), Tao Wu [aut, ctb], Ziyu Tao [aut, ctb], Geoffrey Macintyre [ctb], Anand Mayakonda [ctb]
Maintainer: Shixiang Wang <w_shixiang@163.com>

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Package rcheology updated to version 4.0.0.0 with previous version 3.6.3.0 dated 2020-03-01

Title: Data on Base Packages for Current and Previous Versions of R
Description: Provides a dataset of functions in all base packages of R versions 1.0.1 onwards.
Author: David Hugh-Jones [aut, cre]
Maintainer: David Hugh-Jones <davidhughjones@gmail.com>

Diff between rcheology versions 3.6.3.0 dated 2020-03-01 and 4.0.0.0 dated 2020-04-30

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Package DescTools updated to version 0.99.35 with previous version 0.99.34 dated 2020-03-12

Title: Tools for Descriptive Statistics
Description: A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.
Author: Andri Signorell [aut, cre], Ken Aho [ctb], Andreas Alfons [ctb], Nanina Anderegg [ctb], Tomas Aragon [ctb], Antti Arppe [ctb], Adrian Baddeley [ctb], Kamil Barton [ctb], Ben Bolker [ctb], Hans W. Borchers [ctb], Frederico Caeiro [ctb], Stephane Champely [ctb], Daniel Chessel [ctb], Leanne Chhay [ctb], Clint Cummins [ctb], Michael Dewey [ctb], Harold C. Doran [ctb], Stephane Dray [ctb], Charles Dupont [ctb], Dirk Eddelbuettel [ctb], Jeff Enos [ctb], Claus Ekstrom [ctb], Martin Elff [ctb], Kamil Erguler [ctb], Richard W. Farebrother [ctb], John Fox [ctb], Romain Francois [ctb], Michael Friendly [ctb], Tal Galili [ctb], Matthias Gamer [ctb], Joseph L. Gastwirth [ctb], Yulia R. Gel [ctb], Vilmantas Gegzna [ctb], Juergen Gross [ctb], Gabor Grothendieck [ctb], Frank E. Harrell Jr [ctb], Richard Heiberger [ctb], Michael Hoehle [ctb], Christian W. Hoffmann [ctb], Soeren Hojsgaard [ctb], Torsten Hothorn [ctb], Markus Huerzeler [ctb], Wallace W. Hui [ctb], Pete Hurd [ctb], Rob J. Hyndman [ctb], Pablo J. Villacorta Iglesias [ctb], Christopher Jackson [ctb], Matthias Kohl [ctb], Mikko Korpela [ctb], Max Kuhn [ctb], Detlew Labes [ctb], Duncan Temple Lang [ctb], Friederich Leisch [ctb], Jim Lemon [ctb], Dong Li [ctb], Martin Maechler [ctb], Arni Magnusson [ctb], Daniel Malter [ctb], George Marsaglia [ctb], John Marsaglia [ctb], Alina Matei [ctb], David Meyer [ctb], Weiwen Miao [ctb], Giovanni Millo [ctb], Yongyi Min [ctb], David Mitchell [ctb], Franziska Mueller [ctb], Markus Naepflin [ctb], Daniel Navarro [ctb], Henric Nilsson [ctb], Klaus Nordhausen [ctb], Derek Ogle [ctb], Hong Ooi [ctb], Nick Parsons [ctb], Sandrine Pavoine [ctb], Tony Plate [ctb], Roland Rapold [ctb], William Revelle [ctb], Tyler Rinker [ctb], Brian D. Ripley [ctb], Caroline Rodriguez [ctb], Nathan Russell [ctb], Nick Sabbe [ctb], Venkatraman E. Seshan [ctb], Greg Snow [ctb], Michael Smithson [ctb], Karline Soetaert [ctb], Werner A. Stahel [ctb], Alec Stephenson [ctb], Mark Stevenson [ctb], Ralf Stubner [ctb], Matthias Templ [ctb], Terry Therneau [ctb], Yves Tille [ctb], Luis Torgo [ctb], Adrian Trapletti [ctb], Joshua Ulrich [ctb], Kevin Ushey [ctb], Jeremy VanDerWal [ctb], Bill Venables [ctb], John Verzani [ctb], Gregory R. Warnes [ctb], Stefan Wellek [ctb], Hadley Wickham [ctb], Rand R. Wilcox [ctb], Peter Wolf [ctb], Daniel Wollschlaeger [ctb], Joseph Wood [ctb], Ying Wu [ctb], Thomas Yee [ctb], Achim Zeileis [ctb]
Maintainer: Andri Signorell <andri@signorell.net>

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New package dataCompareR with initial version 0.1.3
Package: dataCompareR
Title: Compare Two Data Frames and Summarise the Difference
Version: 0.1.3
Authors@R: c( person("Sarah", "Johnston", email = "Sarah.Johnston@capitalone.com", role = c("aut", "cre")), person("Rob", "Noble-Eddy", role = c("aut")), person("Merlijn", "van Horssen", role = c("aut")), person("Krishan", "Bhasin", role = c("aut")), person("Sarah", "Pollicott", role = c("aut")), person("Lukas", "Drapal", role = c("ctb")), person("Nikolaos", "Perrakis", role = c("ctb")), person("Nikhil", "Thomas Joy", role = c("ctb")), person("Shahriar", "Asta", role = c("ctb")), person("Karandeep", "Lidher", role = c("ctb")), person("Dan", "Kellett", role = c("ctb")), person("Kevin", "Chisholm", role = c("ctb")), person("Laura", "Joy", role = c("ctb")), person("Fergus", "Wadsley", role = c("ctb")), person("Heather", "Hackett", role = c("ctb")), person("David", "Robinson", role = c("ctb")), person("Cheryl", "Renton", role = c("ctb")), person("Matt", "Triggs", role = c("ctb")), person("Carola", "Deppe", role = c("ctb")), person("Ruijing", "Li", role = c("ctb")), person("John", "Swift", role = c("ctb")), person(given = "Capital One Services, LLC", email = "opensource@capitalone.com", role = c("cph")) )
Description: Easy comparison of two tabular data objects in R. Specifically designed to show differences between two sets of data in a useful way that should make it easier to understand the differences, and if necessary, help you work out how to remedy them. Aims to offer a more useful output than all.equal() when your two data sets do not match, but isn't intended to replace all.equal() as a way to test for equality.
Depends: R (>= 3.2.3)
Imports: dplyr (>= 0.5.0), knitr, stringi, markdown
URL: https://github.com/capitalone/dataCompareR
BugReports: https://github.com/capitalone/dataCompareR/issues
License: Apache License 2.0 | file LICENSE
LazyData: true
RoxygenNote: 7.1.0
Suggests: testthat, data.table, tibble, bit64, rmarkdown, titanic
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-04-30 12:44:41 UTC; sarah
Author: Sarah Johnston [aut, cre], Rob Noble-Eddy [aut], Merlijn van Horssen [aut], Krishan Bhasin [aut], Sarah Pollicott [aut], Lukas Drapal [ctb], Nikolaos Perrakis [ctb], Nikhil Thomas Joy [ctb], Shahriar Asta [ctb], Karandeep Lidher [ctb], Dan Kellett [ctb], Kevin Chisholm [ctb], Laura Joy [ctb], Fergus Wadsley [ctb], Heather Hackett [ctb], David Robinson [ctb], Cheryl Renton [ctb], Matt Triggs [ctb], Carola Deppe [ctb], Ruijing Li [ctb], John Swift [ctb], Capital One Services, LLC [cph]
Maintainer: Sarah Johnston <Sarah.Johnston@capitalone.com>
Repository: CRAN
Date/Publication: 2020-04-30 22:30:07 UTC

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New package circlize with initial version 0.4.9
Package: circlize
Type: Package
Title: Circular Visualization
Version: 0.4.9
Date: 2020-04-28
Author: Zuguang Gu
Maintainer: Zuguang Gu <z.gu@dkfz.de>
Depends: R (>= 3.0.0), graphics
Imports: GlobalOptions (>= 0.1.0), shape, grDevices, utils, stats, colorspace, methods, grid
Suggests: knitr, dendextend (>= 1.0.1), ComplexHeatmap (>= 2.0.0), gridBase, png
VignetteBuilder: knitr
Description: Circular layout is an efficient way for the visualization of huge amounts of information. Here this package provides an implementation of circular layout generation in R as well as an enhancement of available software. The flexibility of the package is based on the usage of low-level graphics functions such that self-defined high-level graphics can be easily implemented by users for specific purposes. Together with the seamless connection between the powerful computational and visual environment in R, it gives users more convenience and freedom to design figures for better understanding complex patterns behind multiple dimensional data. The package is described in Gu et al. 2014 <doi:10.1093/bioinformatics/btu393>.
URL: https://github.com/jokergoo/circlize, http://jokergoo.github.io/circlize_book/book/
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2020-04-29 17:44:25 UTC; jokergoo
Repository: CRAN
Date/Publication: 2020-04-30 22:00:21 UTC

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Package cheese updated to version 0.1.0 with previous version 0.0.3 dated 2020-02-12

Title: Tools for Working with Data During Statistical Analysis
Description: Contains tools for working with data during statistical analysis, promoting flexible, intuitive, and reproducible workflows. There are functions designated for specific statistical tasks such building a custom univariate descriptive table, computing pairwise association statistics, etc. These are built on a collection of data manipulation tools designed for general use that are motivated by the functional programming concept.
Author: Alex Zajichek [aut, cre]
Maintainer: Alex Zajichek <alexzajichek@gmail.com>

Diff between cheese versions 0.0.3 dated 2020-02-12 and 0.1.0 dated 2020-04-30

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New package bst with initial version 0.3-20
Package: bst
Type: Package
Title: Gradient Boosting
Version: 0.3-20
Date: 2020-04-29
Authors@R: c(person("Zhu", "Wang", role = c("aut", "cre"), email = "wangz1@uthscsa.edu", comment = c(ORCID = "0000-0002-0773-0052")), person("Torsten", "Hothorn", role = "ctb"))
Author: Zhu Wang [aut, cre] (<https://orcid.org/0000-0002-0773-0052>), Torsten Hothorn [ctb]
Maintainer: Zhu Wang <wangz1@uthscsa.edu>
Description: Functional gradient descent algorithm for a variety of convex and non-convex loss functions, for both classical and robust regression and classification problems. See Wang (2011) <doi:10.2202/1557-4679.1304>, Wang (2012) <doi:10.3414/ME11-02-0020>, Wang (2018) <doi:10.1080/10618600.2018.1424635>, Wang (2018) <doi:10.1214/18-EJS1404>.
Imports: rpart, methods, foreach, doParallel, gbm
Suggests: hdi, pROC, R.rsp, knitr, gdata
VignetteBuilder: R.rsp, knitr
License: GPL (>= 2)
LazyLoad: yes
Packaged: 2020-04-29 19:26:28 UTC; zhu
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2020-04-30 22:00:26 UTC

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Package workflowr updated to version 1.6.2 with previous version 1.6.1 dated 2020-03-11

Title: A Framework for Reproducible and Collaborative Data Science
Description: Provides a workflow for your analysis projects by combining literate programming ('knitr' and 'rmarkdown') and version control ('Git', via 'git2r') to generate a website containing time-stamped, versioned, and documented results.
Author: John Blischak [aut, cre] (<https://orcid.org/0000-0003-2634-9879>), Peter Carbonetto [aut] (<https://orcid.org/0000-0003-1144-6780>), Matthew Stephens [aut] (<https://orcid.org/0000-0001-5397-9257>), Luke Zappia [ctb] (Instructions for hosting with GitLab), Pierre Formont [ctb] (Support for hosting with Shiny Server), Tim Trice [ctb] (Instructions for sharing common code), Jiaxiang Li [ctb] (Function wflow_toc() to create table of contents), Michael J. Kane [ctb] (<https://orcid.org/0000-0003-1899-6662>, Option suppress_report), Anh Tran [ctb] (Updated RStudio Project Template), Sydney Purdue [ctb] (Improved wflow_start() error handling)
Maintainer: John Blischak <jdblischak@uchicago.edu>

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Package themetagenomics updated to version 1.0.2 with previous version 1.0.1 dated 2020-04-14

Title: Exploring Thematic Structure and Predicted Functionality of 16s rRNA Amplicon Data
Description: A means to explore the structure of 16S rRNA surveys using a Structural Topic Model coupled with functional prediction. The user provides an abundance table, sample metadata, and taxonomy information, and themetagenomics infers associations between topics and sample features, as well as topics and predicted functional content. Functional prediction can be accomplished via Tax4Fun (for Silva references) and PICRUSt (for GreenGeenes references). See <doi:10.1371/journal.pone.0219235>.
Author: Stephen Woloszynek [aut, cre]
Maintainer: Stephen Woloszynek <sw424@drexel.edu>

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Package smicd updated to version 1.1.0 with previous version 1.0.3 dated 2019-02-11

Title: Statistical Methods for Interval Censored Data
Description: Functions that provide statistical methods for interval censored (grouped) data. The package supports the estimation of linear and linear mixed regression models with interval censored dependent variables. Parameter estimates are obtained by a stochastic expectation maximization algorithm. Furthermore, the package enables the direct (without covariates) estimation of statistical indicators from interval censored data via an iterative kernel density algorithm. Survey and Organisation for Economic Co-operation and Development (OECD) weights can be included into the direct estimation (see, Walter, P. (2019) <doi:10.17169/refubium-1621>).
Author: Paul Walter
Maintainer: Paul Walter <paul.walter@fu-berlin.de>

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Package sjlabelled updated to version 1.1.4 with previous version 1.1.3 dated 2020-01-28

Title: Labelled Data Utility Functions
Description: Collection of functions dealing with labelled data, like reading and writing data between R and other statistical software packages like 'SPSS', 'SAS' or 'Stata', and working with labelled data. This includes easy ways to get, set or change value and variable label attributes, to convert labelled vectors into factors or numeric (and vice versa), or to deal with multiple declared missing values.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), David Ranzolin [ctb]
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package naniar updated to version 0.5.1 with previous version 0.5.0 dated 2020-02-28

Title: Data Structures, Summaries, and Visualisations for Missing Data
Description: Missing values are ubiquitous in data and need to be explored and handled in the initial stages of analysis. 'naniar' provides data structures and functions that facilitate the plotting of missing values and examination of imputations. This allows missing data dependencies to be explored with minimal deviation from the common work patterns of 'ggplot2' and tidy data. The work is fully discussed at Tierney & Cook (2018) <arXiv:1809.02264>.
Author: Nicholas Tierney [aut, cre] (<https://orcid.org/0000-0003-1460-8722>), Di Cook [aut] (<https://orcid.org/0000-0002-3813-7155>), Miles McBain [aut] (<https://orcid.org/0000-0003-2865-2548>), Colin Fay [aut] (<https://orcid.org/0000-0001-7343-1846>), Mitchell O'Hara-Wild [ctb], Jim Hester [ctb], Luke Smith [ctb]
Maintainer: Nicholas Tierney <nicholas.tierney@gmail.com>

Diff between naniar versions 0.5.0 dated 2020-02-28 and 0.5.1 dated 2020-04-30

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Package mnormt updated to version 1.5-7 with previous version 1.5-6 dated 2020-02-03

Title: The Multivariate Normal and t Distributions
Description: Functions are provided for computing the density and the distribution function of multivariate normal and "t" random variables, and for generating random vectors sampled from these distributions. Probabilities are computed via non-Monte Carlo methods; different routines are used in the case d=1, d=2, d>2, if d denotes the number of dimensions.
Author: Fortran code by Alan Genz and other people referred to in the code, R code by Adelchi Azzalini
Maintainer: Adelchi Azzalini <adelchi.azzalini@unipd.it>

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Package bst (with last version 0.3-17) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2019-02-27 0.3-17
2019-01-16 0.3-16
2018-07-23 0.3-15
2016-09-21 0.3-14
2016-02-28 0.3-13
2016-01-04 0.3-12
2015-12-19 0.3-11
2014-06-23 0.3-4
2013-09-12 0.3-3
2012-01-17 0.3-2
2011-06-24 0.3-1
2011-03-31 0.2

Permanent link
Package circlize (with last version 0.4.8) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2019-09-08 0.4.8
2019-08-21 0.4.7
2019-04-03 0.4.6
2018-11-21 0.4.5
2018-06-10 0.4.4
2017-12-20 0.4.3
2017-11-18 0.4.2
2017-07-19 0.4.1
2017-05-29 0.4.0
2017-03-07 0.3.10
2016-09-26 0.3.9
2016-08-14 0.3.8
2016-05-15 0.3.7
2016-04-23 0.3.6
2016-03-28 0.3.5
2015-12-22 0.3.4
2015-11-26 0.3.3
2015-10-21 0.3.2
2015-08-18 0.3.1
2015-08-01 0.3.0
2015-07-08 0.2.5
2015-03-20 0.2.4
2015-02-22 0.2.3
2015-01-30 0.2.2
2015-01-08 0.2.1
2014-12-08 0.2.0
2014-11-06 0.1.3
2014-10-13 0.1.2
2014-09-01 0.1.1
2014-08-02 0.1.0
2014-07-11 0.0.9
2014-06-03 0.0.8
2013-10-01 0.0.7
2013-09-01 0.0.6
2013-08-03 0.0.5
2013-07-05 0.0.4
2013-06-02 0.0.3
2013-05-26 0.0.2

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Package seplyr updated to version 0.8.6 with previous version 0.8.5 dated 2020-01-17

Title: Improved Standard Evaluation Interfaces for Common Data Manipulation Tasks
Description: The 'seplyr' (standard evaluation plying) package supplies improved standard evaluation adapter methods for important common 'dplyr' data manipulation tasks. In addition the 'seplyr' package supplies several new "key operations bound together" methods. These include 'group_summarize()' (which combines grouping, arranging and calculation in an atomic unit), 'add_group_summaries()' (which joins grouped summaries into a 'data.frame' in a well documented manner), 'add_group_indices()' (which adds per-group identifiers to a 'data.frame' without depending on row-order), 'partition_mutate_qt()' (which optimizes mutate sequences), and 'if_else_device()' (which simulates per-row if-else blocks in expression sequences).
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between seplyr versions 0.8.5 dated 2020-01-17 and 0.8.6 dated 2020-04-30

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More information about seplyr at CRAN
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Package photobiologyFilters updated to version 0.5.1 with previous version 0.5.0 dated 2019-06-26

Title: Spectral Transmittance Data for Filters
Description: Spectral 'transmittance' data for frequently used filters and similar materials. Plastic sheets and films; photography filters; theatrical gels; machine-vision filters; various types of window glass; optical glass and some laboratory plastics and glassware. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre] (<https://orcid.org/0000-0003-3385-972X>), Titta K. Kotilainen [ctb] (Contributed data), Tania de la Rosa [ctb] (Contributed data), Riitta Tegelberg [ctb] (Contributed data), Andreas Albert [ctb] (Contributed data), SCHOTT AG [ctb] (Contributed data), Midwest Optical Systems, Inc. (MidOpt) [ctb] (Contributed data)
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

Diff between photobiologyFilters versions 0.5.0 dated 2019-06-26 and 0.5.1 dated 2020-04-30

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Package neonUtilities updated to version 1.3.4 with previous version 1.3.3 dated 2020-01-08

Title: Utilities for Working with NEON Data
Description: NEON data packages can be accessed through the NEON Data Portal <https://data.neonscience.org/home> or through the NEON Data API (see <https://data.neonscience.org/data-api> for documentation). Data delivered from the Data Portal are provided as monthly zip files packaged within a parent zip file, while individual files can be accessed from the API. This package provides tools that aid in discovering, downloading, and reformatting data prior to use in analyses. This includes downloading data via the API, merging data tables by type, and converting formats. For more information, see the readme file at <https://github.com/NEONScience/NEON-utilities>.
Author: Claire Lunch [aut, cre, ctb], Christine Laney [aut, ctb], Nathan Mietkiewicz [aut, ctb], Eric Sokol [aut, ctb], Kaelin Cawley [aut, ctb], NEON (National Ecological Observatory Network) [aut]
Maintainer: Claire Lunch <clunch@battelleecology.org>

Diff between neonUtilities versions 1.3.3 dated 2020-01-08 and 1.3.4 dated 2020-04-30

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Package germanpolls updated to version 0.3 with previous version 0.2 dated 2019-01-08

Title: German Polling Data
Description: Extracts political polling data from <http://wahlrecht.de>.
Author: Katharina Brunner [aut, cre]
Maintainer: Katharina Brunner <mail@katharina-brunner.de>

Diff between germanpolls versions 0.2 dated 2019-01-08 and 0.3 dated 2020-04-30

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Package dmdScheme updated to version 1.1.2 with previous version 1.1.0 dated 2020-03-18

Title: Domain Specific MetaData Scheme
Description: Forms the core for developing own domain specific metadata schemes. It contains the basic functionality needed for all metadata schemes based on the 'dmdScheme'. See R.M. Krug and O.L. Petchey (2019) <DOI:10.5281/zenodo.3581970>.
Author: Rainer M. Krug [aut, cre] (<https://orcid.org/0000-0002-7490-0066>), Owen L. Petchey [ctb] (<https://orcid.org/0000-0002-7724-1633>)
Maintainer: Rainer M. Krug <Rainer.Krug@uzh.ch>

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New package shinipsum with initial version 0.1.0
Package: shinipsum
Title: Lorem-Ipsum Helper Function for 'shiny' Prototyping
Version: 0.1.0
Authors@R: c(person(given = "Colin", family = "Fay", role = c("cre", "aut", "cph"), email = "contact@colinfay.me", comment = c(ORCID = "0000-0001-7343-1846")), person(given = "Sebastien", family = "Rochette", role = "aut", email = "sebastien@thinkr.fr", comment = c(ORCID = "0000-0002-1565-9313")), person(given = "ThinkR", role = c("cph", "fnd")))
Description: Prototype your 'shiny' apps quickly with these Lorem-Ipsum helper functions. Generate random elements for 'shiny' outputs that can be used as placeholder in your application.
License: MIT + file LICENSE
URL: https://github.com/Thinkr-open/shinipsum
BugReports: https://github.com/Thinkr-open/shinipsum/issues
Depends: R (>= 2.10)
Imports: attempt, datasets, DT, dygraphs, ggplot2 (>= 3.0.0), magrittr, plotly, stats, utils
Suggests: covr, pkgdown, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-25 20:18:00 UTC; colin
Author: Colin Fay [cre, aut, cph] (<https://orcid.org/0000-0001-7343-1846>), Sebastien Rochette [aut] (<https://orcid.org/0000-0002-1565-9313>), ThinkR [cph, fnd]
Maintainer: Colin Fay <contact@colinfay.me>
Repository: CRAN
Date/Publication: 2020-04-30 18:40:03 UTC

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New package maic with initial version 0.1.2
Package: maic
Type: Package
Title: Matching-Adjusted Indirect Comparison
Version: 0.1.2
Date: 2020-04-26
Authors@R: c(person("Rob", "Young", role = c("aut", "cre"), email = "rob.young@heor.co.uk"))
Maintainer: Rob Young <rob.young@heor.co.uk>
Depends: R (>= 3.0.0)
Description: A generalised workflow for generation of subject weights to be used in Matching-Adjusted Indirect Comparison (MAIC) per Signorovitch et al (2012) <doi:10.1016/j.jval.2012.05.004>, Signorovitch et al (2010) <doi:10.2165/11538370-000000000-00000>. In MAIC, unbiased comparison between outcomes of two trials is facilitated by weighting the subject-level outcomes of one trial with weights derived such that the weighted aggregate measures of the prognostic or effect modifying variables are equal to those of the sample in the comparator trial. The functions and classes included in this package wrap and abstract the process demonstrated in the UK National Institute for Health and Care Excellence Decision Support Unit (NICE DSU)'s example (Phillippo et al, (2016) [see URL]), providing a repeatable and easily specifiable workflow for producing multiple comparison variable sets against a variety of target studies, with preprocessing for a number of aggregate target forms (e.g. mean, median, domain limits).
License: GPL-3
URL: https://github.com/heorltd/maic, http://nicedsu.org.uk/technical-support-documents/population-adjusted-indirect-comparisons-maic-and-stc/
Imports: Hmisc, matrixStats, weights
RoxygenNote: 7.1.0
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-04-26 15:18:33 UTC; Rob Young
Author: Rob Young [aut, cre]
Repository: CRAN
Date/Publication: 2020-04-30 19:00:03 UTC

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New package nesRdata with initial version 0.3.1
Package: nesRdata
Title: National Eutrophication Survey Data
Version: 0.3.1
Authors@R: c( person("Joseph", "Stachelek", role = c("aut","cre"), email = "stachel2@msu.edu", comment = c(ORCID = "0000-0002-5924-2464")) )
URL: https://github.com/jsta/nesRdata
BugReports: https://github.com/jsta/nesRdata/issues
Description: Serves data from the United States Environmental Protection Agency (USEPA) National Eutrophication Survey <https://www.epa.gov/national-aquatic-resource-surveys>.
Depends: R (>= 3.4.0)
Imports: rappdirs, dplyr, purrr, readr, dataone
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-04-29 22:08:44 UTC; jose
Author: Joseph Stachelek [aut, cre] (<https://orcid.org/0000-0002-5924-2464>)
Maintainer: Joseph Stachelek <stachel2@msu.edu>
Repository: CRAN
Date/Publication: 2020-04-30 17:20:02 UTC

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New package liayson with initial version 1.0.3
Package: liayson
Type: Package
Title: Linking Singe-Cell Transcriptomes Atween Contemporary Subpopulation Genomes
Version: 1.0.3
Date: 2020-04-06
Author: Noemi Andor
Maintainer: Noemi Andor <liayson.scRNA.R@gmail.com>
Description: Given an RNA-seq derived cell-by-gene matrix and an DNA-seq derived copy number segmentation, LIAYSON predicts the number of clones present in a tumor, their size, the copy number profile of each clone and the clone membership of each single cell (Andor, N. & Lau, B., et al. (2018) <doi:10.1101/445932>).
License: GPL-2
URL: https://github.com/noemiandor/liayson, https://groups.google.com/d/forum/liayson
Depends: R (>= 3.0)
Imports: phangorn, RColorBrewer, ape, parallel, plyr, matlab, biomaRt, distances, arules, e1071, proxy, gplots, methods
Suggests: mclust, fpc, NbClust, modeest, pastecs, vegan
Packaged: 2020-04-30 01:06:34 UTC; 4470246
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2020-04-30 17:30:02 UTC
RoxygenNote: 6.1.1

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Package data360r updated to version 1.0.8 with previous version 1.0.6 dated 2020-04-28

Title: Wrapper for 'TCdata360' and 'Govdata360' API
Description: Makes it easy to engage with the Application Program Interface (API) of the 'TCdata360' and 'Govdata360' platforms at <https://tcdata360.worldbank.org/> and <https://govdata360.worldbank.org/>, respectively. These application program interfaces provide access to over 5000 trade, competitiveness, and governance indicator data, metadata, and related information from sources both inside and outside the World Bank Group. Package functions include easier download of data sets, metadata, and related information, as well as searching based on user-inputted query.
Author: Ramin Aliyev [cre], Ma. Regina Paz Onglao-Drilon [aut], World Bank Group [cph]
Maintainer: Ramin Aliyev <tcdata360@worldbank.org>

Diff between data360r versions 1.0.6 dated 2020-04-28 and 1.0.8 dated 2020-04-30

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Package recipes updated to version 0.1.11 with previous version 0.1.10 dated 2020-03-18

Title: Preprocessing Tools to Create Design Matrices
Description: An extensible framework to create and preprocess design matrices. Recipes consist of one or more data manipulation and analysis "steps". Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting design matrices can then be used as inputs into statistical or machine learning models.
Author: Max Kuhn [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

Diff between recipes versions 0.1.10 dated 2020-03-18 and 0.1.11 dated 2020-04-30

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Package modelr updated to version 0.1.7 with previous version 0.1.6 dated 2020-02-22

Title: Modelling Functions that Work with the Pipe
Description: Functions for modelling that help you seamlessly integrate modelling into a pipeline of data manipulation and visualisation.
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

Diff between modelr versions 0.1.6 dated 2020-02-22 and 0.1.7 dated 2020-04-30

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Package collections updated to version 0.3.1 with previous version 0.3.0 dated 2020-04-19

Title: High Performance Container Data Types
Description: Provides high performance container data types such as queues, stacks, deques, dicts and ordered dicts. Benchmarks <https://randy3k.github.io/collections/articles/benchmark.html> have shown that these containers are asymptotically more efficient than those offered by other packages.
Author: Randy Lai [aut, cre], Andrea Mazzoleni [cph] (tommy hash table library)
Maintainer: Randy Lai <randy.cs.lai@gmail.com>

Diff between collections versions 0.3.0 dated 2020-04-19 and 0.3.1 dated 2020-04-30

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 src/utils.h                          |    6 +
 tests/testthat/test-deque.R          |   17 ++++
 tests/testthat/test-ordered_dict.R   |   15 +++
 tests/testthat/test-priority_queue.R |   10 ++
 tests/testthat/test-queue.R          |   10 ++
 tests/testthat/test-stack.R          |   10 ++
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More information about collections at CRAN
Permanent link

Package Boom updated to version 0.9.6 with previous version 0.9.5 dated 2020-04-15

Title: Bayesian Object Oriented Modeling
Description: A C++ library for Bayesian modeling, with an emphasis on Markov chain Monte Carlo. Although boom contains a few R utilities (mainly plotting functions), its primary purpose is to install the BOOM C++ library on your system so that other packages can link against it.
Author: Steven L. Scott is the sole author and creator of the BOOM project. Some code in the BOOM libraries has been modified from other open source projects. These include Cephes (obtained from Netlib, written by Stephen L. Moshier), NEWUOA (M.J.D Powell, obtained from Powell's web site), and a modified version of the R math libraries (R core development team). Original copyright notices have been maintained in all source files. In these cases, copyright claimed by Steven L. Scott is limited to modifications made to the original code. Google claims copyright for code written while Steven L. Scott was employed at Google from 2008 - 2018, but BOOM is not an officially supported Google project.
Maintainer: Steven L. Scott <steve.the.bayesian@gmail.com>

Diff between Boom versions 0.9.5 dated 2020-04-15 and 0.9.6 dated 2020-04-30

 DESCRIPTION                                                                                     |    8 
 MD5                                                                                             |  104 +++++-----
 R/plot.dynamic.distribution.R                                                                   |   18 +
 inst/include/LinAlg/Array.hpp                                                                   |   14 -
 inst/include/LinAlg/DiagonalMatrix.hpp                                                          |   10 
 inst/include/LinAlg/Eigen.hpp                                                                   |    2 
 inst/include/LinAlg/Matrix.hpp                                                                  |   16 -
 inst/include/LinAlg/SWEEP.hpp                                                                   |    2 
 inst/include/LinAlg/SpdMatrix.hpp                                                               |    8 
 inst/include/LinAlg/VectorView.hpp                                                              |    8 
 inst/include/Models/DataTypes.hpp                                                               |    8 
 inst/include/Models/Glm/GlmCoefs.hpp                                                            |   16 -
 inst/include/Models/Glm/PosteriorSamplers/IndependentRegressionModelsPosteriorSampler.hpp       |    6 
 inst/include/Models/Glm/VariableSelectionPrior.hpp                                              |   20 -
 inst/include/Models/HMM/Clickstream/PosteriorSamplers/NestedHmmPosteriorSampler.hpp             |    4 
 inst/include/Models/IRT/ItemSliceSampler.hpp                                                    |    3 
 inst/include/Models/MarkovModel.hpp                                                             |    2 
 inst/include/Models/Mixtures/DirichletProcessMvnModel.hpp                                       |    2 
 inst/include/Models/Mixtures/PosteriorSamplers/ConditionalFiniteMixtureSampler.hpp              |    5 
 inst/include/Models/Mixtures/PosteriorSamplers/DirichletProcessCollapsedGibbsSampler.hpp        |    2 
 inst/include/Models/Mixtures/PosteriorSamplers/DirichletProcessSliceSampler.hpp                 |    7 
 inst/include/Models/Mixtures/PosteriorSamplers/SplitMerge.hpp                                   |    5 
 inst/include/Models/Nnet/PosteriorSamplers/GaussianFeedForwardPosteriorSampler.hpp              |   13 -
 inst/include/Models/Policies/DeferredDataPolicy.hpp                                             |   15 -
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 inst/include/Models/StateSpace/StateModels/SeasonalStateModel.hpp                               |    4 
 inst/include/Models/TimeSeries/MarkovLink.hpp                                                   |   15 -
 inst/include/Samplers/failed_experiments/AdaptiveGaussianMixtureMhSampler.hpp                   |    5 
 inst/include/Samplers/failed_experiments/AdaptiveRandomWalkMetropolisSampler.hpp                |    7 
 src/Models/Glm/GlmCoefs.cpp                                                                     |   47 ++--
 src/Models/Glm/PosteriorSamplers/AdaptiveSpikeSlabRegressionSampler.cpp                         |   16 -
 src/Models/Glm/PosteriorSamplers/BregVsSampler.cpp                                              |   14 -
 src/Models/Glm/PosteriorSamplers/MlogitRwm.cpp                                                  |    1 
 src/Models/Glm/RegressionModel.cpp                                                              |    5 
 src/Models/HMM/HMM2.cpp                                                                         |    3 
 src/Models/HMM/HealthStateModel.cpp                                                             |    2 
 src/Models/Hierarchical/PosteriorSamplers/HierarchicalZeroInflatedPoissonSampler.cpp            |    6 
 src/Models/IRT/DafePcrRwmSubject.cpp                                                            |    1 
 src/Models/IRT/IrtModel.cpp                                                                     |    3 
 src/Models/MarkovModel.cpp                                                                      |   12 -
 src/Models/PosteriorSamplers/AbsorbingMarkovConjSampler.cpp                                     |    1 
 src/Models/StateSpace/AggregatedStateSpaceRegression.cpp                                        |    2 
 src/Models/StateSpace/DynamicRegression.cpp                                                     |only
 src/Models/StateSpace/MultivariateStateSpaceModelBase.cpp                                       |   15 -
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 src/Models/StateSpace/StateModels/LocalLevelStateModel.cpp                                      |   17 -
 src/Models/WeightedMvnModel.cpp                                                                 |    1 
 src/TargetFun/Transformation.cpp                                                                |    1 
 src/cpputil/split.cpp                                                                           |    3 
 src/list_io.cpp                                                                                 |   28 +-
 src/stats/NaturalSpline.cpp                                                                     |    2 
 55 files changed, 278 insertions(+), 265 deletions(-)

More information about Boom at CRAN
Permanent link

Package vegtable updated to version 0.1.6 with previous version 0.1.5 dated 2020-01-13

Title: Handling Vegetation Data Sets
Description: Import and handling data from vegetation-plot databases, especially data stored in 'Turboveg' (<https://www.synbiosys.alterra.nl/turboveg>). Also import/export routines for exchange of data with 'Juice' (<http://www.sci.muni.cz/botany/juice>) are implemented.
Author: Miguel Alvarez [aut, cre] (<https://orcid.org/0000-0003-1500-1834>)
Maintainer: Miguel Alvarez <kamapu78@gmail.com>

Diff between vegtable versions 0.1.5 dated 2020-01-13 and 0.1.6 dated 2020-04-30

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 91 files changed, 4041 insertions(+), 2200 deletions(-)

More information about vegtable at CRAN
Permanent link

Package tidytable updated to version 0.4.1 with previous version 0.4.0 dated 2020-03-28

Title: Tidy Interface to 'data.table'
Description: Tidy interface to 'data.table'. 'rlang' compatible, which allows the user to build custom functions much like they would in the tidyverse.
Author: Mark Fairbanks [aut, cre], Tyson Barrett [ctb], Ivan Leung [ctb], Ross Kennedy [ctb]
Maintainer: Mark Fairbanks <mark.t.fairbanks@gmail.com>

Diff between tidytable versions 0.4.0 dated 2020-03-28 and 0.4.1 dated 2020-04-30

 DESCRIPTION                     |   13 +--
 MD5                             |  164 ++++++++++++++++++++--------------------
 NAMESPACE                       |   49 +++++------
 NEWS.md                         |   30 +++++++
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More information about tidytable at CRAN
Permanent link

Package stoRy updated to version 0.1.4 with previous version 0.1.3 dated 2019-07-09

Title: Functions for the Analysis of Star Trek Thematic Data
Description: An implementation of 1) the hypergeometric test for over-representation of literary themes in a storyset (a list of stories) relative to a background list of stories, and 2) a recommendation system that takes a user-selected story as input and returns a ranked list of similar stories on the basis of shared themes. The package is currently implemented for the episodes of the Star Trek television franchise series The Original Series (TOS), The Animated Series (TAS), The Next Generation (TNG), and Voyager (VOY).
Author: Paul Sheridan, Mikael Onsjö
Maintainer: Paul Sheridan <paul.sheridan.stats@gmail.com>

Diff between stoRy versions 0.1.3 dated 2019-07-09 and 0.1.4 dated 2020-04-30

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More information about stoRy at CRAN
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Package modelsummary updated to version 0.2.1 with previous version 0.2.0 dated 2020-04-05

Title: Summary Tables for Statistical Models: Beautiful, Customizable, and Publication-Ready
Description: Create beautiful, customizable, publication-ready summary tables for statistical models. 'modelsummary' leverages the power of the 'gt' and 'broom' packages. It can produce tables in HTML, RTF, JPG, and LaTeX formats.
Author: Vincent Arel-Bundock [aut, cre]
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>

Diff between modelsummary versions 0.2.0 dated 2020-04-05 and 0.2.1 dated 2020-04-30

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More information about modelsummary at CRAN
Permanent link

Package pathmox (with last version 0.2.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2013-12-10 0.2.0

Permanent link
Package ProgGUIinR (with last version 0.0-4) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2014-07-20 0.0-4
2012-09-14 0.0-3
2012-07-03 0.0-2
2012-06-12 0.0-1

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Package JavaGD updated to version 0.6-2 with previous version 0.6-1.1 dated 2019-04-15

Title: Java Graphics Device
Description: Graphics device routing all graphics commands to a Java program. The actual functionality of the JavaGD depends on the Java-side implementation. Simple AWT and Swing implementations are included.
Author: Simon Urbanek <Simon.Urbanek@R-project.org>
Maintainer: Simon Urbanek <Simon.Urbanek@R-project.org>

Diff between JavaGD versions 0.6-1.1 dated 2019-04-15 and 0.6-2 dated 2020-04-30

 DESCRIPTION          |   18 +++++++++---------
 MD5                  |   14 +++++++-------
 NAMESPACE            |    3 +++
 NEWS                 |    9 +++++++++
 configure            |    8 +-------
 configure.ac         |    3 +--
 inst/java/javaGD.jar |binary
 src/javaGD.h         |    2 +-
 8 files changed, 31 insertions(+), 26 deletions(-)

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Package diseasemapping (with last version 1.4.6) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2018-07-12 1.4.6
2016-09-20 1.4.2
2016-03-07 1.4.0
2015-11-09 1.2.7
2015-07-07 1.2.3
2015-03-25 1.2.0
2015-02-25 1.1.7
2015-01-15 1.1.5
2015-01-05 1.1.4
2014-11-13 1.1.2
2014-10-06 1.1.0
2014-09-24 1.0.1
2014-08-14 0.7.7
2013-07-17 0.7.5
2013-06-09 0.7.3
2012-01-17 0.6

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Package geostatsp (with last version 1.8.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2020-01-29 1.8.0
2019-04-16 1.7.8
2019-03-06 1.7.7
2018-07-13 1.7.2
2018-04-19 1.7.1
2018-01-03 1.6.0
2017-07-19 1.5.4
2016-07-07 1.4.4
2016-03-04 1.4.0
2015-11-09 1.3.10
2015-08-17 1.3.5
2015-07-07 1.3.4
2015-02-27 1.2.1
2015-01-23 1.1.9
2015-01-05 1.1.8
2014-11-13 1.1.5
2014-10-02 1.1.0
2014-09-18 1.0.1
2014-09-17 1.0.0
2014-08-04 0.9.999
2014-07-10 0.9.9
2014-02-27 0.9.7
2014-01-21 0.9.1
2013-11-27 0.8.0
2013-10-08 0.7.0
2013-08-26 0.6.0
2013-08-20 0.5.8
2013-07-12 0.4.4

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Package cgmanalysis updated to version 2.7 with previous version 2.6.1 dated 2020-03-12

Title: Clean and Analyze Continuous Glucose Monitor Data
Description: This code provides several different functions for cleaning and analyzing continuous glucose monitor data. Currently it works with 'Dexcom' (<https://www.dexcom.com>), 'iPro 2' (<http://professional.medtronicdiabetes.com/ipro2-professional-cgm>), Diasend (<https://diasend.com//us>), Libre (<https://www.freestylelibre.us/>) or Carelink (<https://www.medtronicdiabetes.com/products/carelink-personal-diabetes-software>) data. The cleandata() function takes a directory of CGM data files and prepares them for analysis. cgmvariables() iterates through a directory of cleaned CGM data files and produces a single spreadsheet with data for each file in either rows or columns. The column format of this spreadsheet is compatible with REDCap data upload ("--1" is added to each subject ID automatically for double data entry). cgmreport() also iterates through a directory of cleaned data, and produces PDFs of individual and aggregate AGP plots. Please visit <https://github.com/childhealthbiostatscore/R-Packages/> to download the new-user guide.
Author: Tim Vigers [aut, cre]
Maintainer: Tim Vigers <tim.b.vigers@gmail.com>

Diff between cgmanalysis versions 2.6.1 dated 2020-03-12 and 2.7 dated 2020-04-30

 DESCRIPTION         |    6 +++---
 MD5                 |    8 ++++----
 R/cgmvariables.R    |   41 ++++++++++++++++++++++++-----------------
 R/cleandata.R       |   22 ++++++++++++++++------
 man/cgmvariables.Rd |    2 +-
 5 files changed, 48 insertions(+), 31 deletions(-)

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Package mapmisc (with last version 1.7.7) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2020-04-24 1.7.7

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