Mon, 15 Feb 2021

Package gpmap updated to version 0.1.2 with previous version 0.1.1 dated 2014-01-09

Title: Analysing and Plotting Genotype-Phenotype Maps
Description: Tools for studying genotype-phenotype maps for bi-allelic loci underlying quantitative phenotypes. The 0.1 version is released in connection with the publication of Gjuvsland et al (2013) and implements basic line plots and the monotonicity measures for GP maps presented in the paper. Reference: Gjuvsland AB, Wang Y, Plahte E and Omholt SW (2013) Monotonicity is a key feature of genotype-phenotype maps. Frontier in Genetics 4:216 <doi:10.3389/fgene.2013.00216>.
Author: Arne B. Gjuvsland <arne.gjuvsland@nmbu.no> and Yunpeng Wang <yunpeng.wng@gmail.com>
Maintainer: Arne B. Gjuvsland <arne.gjuvsland@nmbu.no>

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Package xmeta updated to version 1.3-0 with previous version 1.2-1 dated 2020-10-22

Title: A Toolbox for Multivariate Meta-Analysis
Description: A toolbox for meta-analysis. This package includes (1) a robust multivariate meta-analysis of continuous or binary outcomes; (2) a bivariate Egger's test for detecting small study effects; (3) Galaxy Plot: A New Visualization Tool of Bivariate Meta-Analysis Studies; and (4) a bivariate T&F method accounting for publication bias in bivariate meta-analysis, based on symmetry of the galaxy plot.
Author: Chuan Hong [aut], Chongliang Luo [aut], Jiayi Tong [aut, cre], Rui Duan [ctb], Haitao Chu [ctb], Yulun Liu [ctb], Yong Chen [aut]
Maintainer: Jiayi Tong <Jiayi.Tong@pennmedicine.upenn.edu>

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Package mpath updated to version 0.4-2.18 with previous version 0.4-2.17 dated 2020-12-13

Title: Regularized Linear Models
Description: Algorithms compute concave convex (CC) estimators including robust (penalized) generalized linear models and robust support vector machines via the COCO - composite optimization by conjugation operator. The package also contains penalized Poisson, negative binomial, zero-inflated Poisson, zero-inflated negative binomial regression models and robust models with non-convex loss functions. Wang et al. (2014) <doi:10.1002/sim.6314>, Wang et al. (2015) <doi:10.1002/bimj.201400143>, Wang et al. (2016) <doi:10.1177/0962280214530608>, Wang (2019) <arXiv:1912.11119>, Wang (2020) <arXiv:2010.02848>.
Author: Zhu Wang, with contributions from Achim Zeileis, Simon Jackman, Brian Ripley, and Patrick Breheny
Maintainer: Zhu Wang <wangz1@uthscsa.edu>

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Package formulaic updated to version 0.0.8 with previous version 0.0.7 dated 2020-05-04

Title: Dynamic Generation and Quality Checks of Formula Objects
Description: 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. Users may specify the outcome and inputs of a model directly, search for variables to include based upon naming patterns, incorporate interactions, 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. Variables that do not meet these quality checks can be automatically excluded from the model. These issues are documented and reported in a manner that provides greater accountability and useful information to guide an investigation of the data.
Author: David Shilane [aut], Anderson Nelson [aut, ctb, cre], Caffrey Lee [aut, ctb], Zichen Huang [aut, ctb]
Maintainer: Anderson Nelson <an2908@columbia.edu>

Diff between formulaic versions 0.0.7 dated 2020-05-04 and 0.0.8 dated 2021-02-15

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Package swissdd updated to version 1.1.1 with previous version 1.1.0 dated 2021-02-03

Title: Get Swiss Federal and Cantonal Vote Results from Opendata.swiss
Description: Builds upon the real time data service as well as the archive for national votes <https://opendata.swiss/api/3/action/package_show?id=echtzeitdaten-am-abstimmungstag-zu-eidgenoessischen-abstimmungsvorlagen> and cantonal votes <https://opendata.swiss/api/3/action/package_show?id=echtzeitdaten-am-abstimmungstag-zu-kantonalen-abstimmungsvorlagen>. It brings the results of Swiss popular votes, aggregated at the geographical level of choice, into R. Additionally, it allows to retrieve data from the Swissvotes-Database, one of the most comprehensive data platforms on Swiss referendums and initiatives <https://swissvotes.ch/page/dataset/swissvotes_dataset.csv>.
Author: Thomas Lo Russo [cre, aut], Thomas Willi [aut]
Maintainer: Thomas Lo Russo <th.lorusso@gmail.com>

Diff between swissdd versions 1.1.0 dated 2021-02-03 and 1.1.1 dated 2021-02-15

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Package rnoaa updated to version 1.3.2 with previous version 1.3.0 dated 2021-01-07

Title: 'NOAA' Weather Data from R
Description: Client for many 'NOAA' data sources including the 'NCDC' climate 'API' at <https://www.ncdc.noaa.gov/cdo-web/webservices/v2>, with functions for each of the 'API' 'endpoints': data, data categories, data sets, data types, locations, location categories, and stations. In addition, we have an interface for 'NOAA' sea ice data, the 'NOAA' severe weather inventory, 'NOAA' Historical Observing 'Metadata' Repository ('HOMR') data, 'NOAA' storm data via 'IBTrACS', tornado data via the 'NOAA' storm prediction center, and more.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Brooke Anderson [ctb], Maƫlle Salmon [ctb], Adam Erickson [ctb], Nicholas Potter [ctb], Joseph Stachelek [ctb], Alex Simmons [ctb], Karthik Ram [ctb], Hart Edmund [ctb], rOpenSci [fnd] (https://ropensci.org)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package r3dmol updated to version 0.1.1 with previous version 0.1.0 dated 2020-10-26

Title: Create Interactive 3D Visualizations of Molecular Data
Description: Create rich and fully interactive 3D visualizations of molecular data. Visualizations can be included in Shiny apps and R markdown documents, or viewed from the R console and 'RStudio' Viewer. 'r3dmol' includes an extensive API to manipulate the visualization after creation, and supports getting data out of the visualization into R. Based on the '3dmol.js' and the 'htmlwidgets' R package.
Author: Wei Su [aut, cre], Brady Johnston [aut]
Maintainer: Wei Su <swsoyee@gmail.com>

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Package nflfastR updated to version 4.0.0 with previous version 3.2.0 dated 2020-11-20

Title: Functions to Efficiently Access NFL Play by Play Data
Description: A set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.
Author: Sebastian Carl [aut], Ben Baldwin [cre, aut], Lee Sharpe [ctb], Maksim Horowitz [ctb], Ron Yurko [ctb], Samuel Ventura [ctb], Tan Ho [ctb]
Maintainer: Ben Baldwin <bbaldwin206@gmail.com>

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Package cgmanalysis updated to version 2.7.1 with previous version 2.7 dated 2020-04-30

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', 'iPro 2', 'Diasend', 'Libre', or 'Carelink' 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. 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 2.7 dated 2020-04-30 and 2.7.1 dated 2021-02-15

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Package matrixdist updated to version 1.0.1 with previous version 1.0 dated 2021-01-08

Title: Statistics for Matrix Distributions
Description: Tools for homogeneous and in-homogeneous phase-type distributions. Methods for functional evaluation, simulation and estimation using the expectation-maximization (EM) algorithm are provided. The methods of this package are based on the following references. Asmussen, S., Nerman, O., & Olsson, M. (1996) <https://www.jstor.org/stable/4616418>, Olsson, M. (1996) <https://www.jstor.org/stable/4616419>. Albrecher, H., & Bladt, M. (2019) <doi:10.1017/jpr.2019.60> Albrecher, H., Bladt, M., & Yslas, J. (2020) <doi:10.1111/sjos.12505> Bladt, M., & Yslas, J. (2020) <arXiv:2011.03219>.
Author: Martin Bladt [aut, cre], Jorge Yslas [aut]
Maintainer: Martin Bladt <martinbladt@gmail.com>

Diff between matrixdist versions 1.0 dated 2021-01-08 and 1.0.1 dated 2021-02-15

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Package genderBR updated to version 1.1.1 with previous version 1.1.0 dated 2018-04-17

Title: Predict Gender from Brazilian First Names
Description: A method to predict and report gender from Brazilian first names using the Brazilian Institute of Geography and Statistics' Census data.
Author: Fernando Meireles [aut, cre]
Maintainer: Fernando Meireles <fmeireles@ufmg.br>

Diff between genderBR versions 1.1.0 dated 2018-04-17 and 1.1.1 dated 2021-02-15

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New package bifurcatingr with initial version 1.0.0
Package: bifurcatingr
Title: Bifurcating Autoregressive Models
Version: 1.0.0
Authors@R: c( person("Tamer", "Elbayoumi", email = "tmelbayoumi@ncat.edu", role = c("aut", "cre"),comment = c(ORCID = "0000-0001-9071-7766")), person("Sayed", "Mostafa", email = "sabdelmegeed@ncat.edu", role = "aut", comment = c(ORCID = "0000-0002-8113-702X")))
Description: Estimation of bifurcating autoregressive models of any order, p, BAR(p) as well as several types of bias correction for the least squares estimators of the autoregressive parameters as described in Zhou and Basawa (2005) <doi:10.1016/j.spl.2005.04.024> and Elbayoumi and Mostafa (2020) <doi:10.1002/sta4.342>. Currently, the bias correction methods supported include bootstrap (single, double and fast-double) bias correction and linear-bias-function-based bias correction. Functions for generating and plotting bifurcating autoregressive data from any BAR(p) model are also included.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: graphics (>= 4.0.0), igraph (>= 1.2.5), MASS (>= 7.3.0)
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-02-12 00:03:41 UTC; sayedmostafa2
Author: Tamer Elbayoumi [aut, cre] (<https://orcid.org/0000-0001-9071-7766>), Sayed Mostafa [aut] (<https://orcid.org/0000-0002-8113-702X>)
Maintainer: Tamer Elbayoumi <tmelbayoumi@ncat.edu>
Repository: CRAN
Date/Publication: 2021-02-15 17:10:02 UTC

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New package SimReg with initial version 3.3
Package: SimReg
Type: Package
Title: Similarity Regression
Version: 3.3
Date: 2021-02-10
Author: Daniel Greene
Maintainer: Daniel Greene <dg333@cam.ac.uk>
Description: Similarity regression, evaluating the probability of association between sets of ontological terms and binary response vector. A no-association model is compared with one in which the log odds of a true response is linked to the semantic similarity between terms and a latent characteristic ontological profile - 'Phenotype Similarity Regression for Identifying the Genetic Determinants of Rare Diseases', Greene et al 2016 <doi:10.1016/j.ajhg.2016.01.008>.
License: GPL (>= 2)
Imports: Rcpp (>= 0.11.1), ontologyIndex (>= 2.0), ontologySimilarity (>= 2.0), ontologyPlot
LinkingTo: Rcpp
Depends: R (>= 3.0.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-02-15 14:14:56 UTC; dg
Repository: CRAN
Date/Publication: 2021-02-15 16:30:05 UTC

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Package rgl updated to version 0.105.13 with previous version 0.105.12 dated 2021-02-14

Title: 3D Visualization Using OpenGL
Description: Provides medium to high level functions for 3D interactive graphics, including functions modelled on base graphics (plot3d(), etc.) as well as functions for constructing representations of geometric objects (cube3d(), etc.). Output may be on screen using OpenGL, or to various standard 3D file formats including WebGL, PLY, OBJ, STL as well as 2D image formats, including PNG, Postscript, SVG, PGF.
Author: Daniel Adler <dadler@uni-goettingen.de>, Duncan Murdoch <murdoch.duncan@gmail.com>, and others (see README)
Maintainer: Duncan Murdoch <murdoch.duncan@gmail.com>

Diff between rgl versions 0.105.12 dated 2021-02-14 and 0.105.13 dated 2021-02-15

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Package ragg updated to version 1.1.0 with previous version 0.4.1 dated 2021-01-11

Title: Graphic Devices Based on AGG
Description: Anti-Grain Geometry (AGG) is a high-quality and high-performance 2D drawing library. The 'ragg' package provides a set of graphic devices based on AGG to use as alternative to the raster devices provided through the 'grDevices' package.
Author: Thomas Lin Pedersen [cre, aut] (<https://orcid.org/0000-0002-5147-4711>), Maxim Shemanarev [aut, cph] (Author of AGG), Tony Juricic [ctb, cph] (Contributor to AGG), Milan Marusinec [ctb, cph] (Contributor to AGG), Spencer Garrett [ctb] (Contributor to AGG), RStudio [cph]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@rstudio.com>

Diff between ragg versions 0.4.1 dated 2021-01-11 and 1.1.0 dated 2021-02-15

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New package IntervalSurgeon with initial version 1.1
Package: IntervalSurgeon
Type: Package
Title: Operating on Integer-Bounded Intervals
Version: 1.1
Date: 2021-02-03
Author: Daniel Greene
Maintainer: Daniel Greene <dg333@cam.ac.uk>
Description: Manipulate integer-bounded intervals including finding overlaps, piling and merging.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.4)
LinkingTo: Rcpp
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-02-15 15:56:34 UTC; dg
Repository: CRAN
Date/Publication: 2021-02-15 16:20:05 UTC

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New package gbm.auto with initial version 1.4.0
Package: gbm.auto
Title: Automated Boosted Regression Tree Modelling and Mapping Suite
Version: 1.4.0
Authors@R: c( person("Simon", "Dedman", email = "simondedman@gmail.com", role = c("aut", "cre")), person("Hans", "Gerritsen", role = "aut"))
Description: Automates delta log-normal boosted regression tree abundance prediction. Loops through parameters provided (LR (learning rate), TC (tree complexity), BF (bag fraction)), chooses best, simplifies, & generates line, dot & bar plots, & outputs these & predictions & a report, makes predicted abundance maps, and Unrepresentativeness surfaces. Package core built around 'gbm' (gradient boosting machine) functions in 'dismo' (Hijmans, Phillips, Leathwick & Jane Elith, 2020 & ongoing), itself built around 'gbm' (Greenwell, Boehmke, Cunningham & Metcalfe, 2020 & ongoing, originally by Ridgeway). Indebted to Elith/Leathwick/Hastie 2008 'Working Guide' <doi:10.1111/j.1365-2656.2008.01390.x>; workflow follows Appendix S3. See <http://www.simondedman.com/> for published guides and papers using this package.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
LazyData: true
Imports: gbm (>= 2.1.1), dismo (>= 1.0-15), beepr (>= 1.2), mapplots (>= 1.5), maptools (>= 0.9-1), rgdal (>= 1.1-10), rgeos (>= 0.3-19), raster (>= 2.5-8), sf (>= 0.9-7), shapefiles (>= 0.7), stats (>= 3.3.1)
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-11 22:02:25 UTC; simon
Author: Simon Dedman [aut, cre], Hans Gerritsen [aut]
Maintainer: Simon Dedman <simondedman@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-15 16:50:02 UTC

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Package Directional updated to version 4.7 with previous version 4.6 dated 2021-01-09

Title: A Collection of R Functions for Directional Data Analysis
Description: A collection of functions for directional data (including massive, with millions of observations, data) analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). Other references include a) Phillip J. Paine, Simon P. Preston Michail Tsagris and Andrew T. A. Wood (2018). An elliptically symmetric angular Gaussian distribution. Statistics and Computing 28(3): 689-697. <doi:10.1007/s11222-017-9756-4>. b) Tsagris M. and Alenazi A. (2019). Comparison of discriminant analysis methods on the sphere. Communications in Statistics: Case Studies, Data Analysis and Applications 5(4):467--491. <doi:10.1080/23737484.2019.1684854>. c) P. J. Paine, S. P. Preston, M. Tsagris and Andrew T. A. Wood (2020). Spherical regression models with general covariates and anisotropic errors. Statistics and Computing 30(1): 153--165. <doi:10.1007/s11222-019-09872-2>.
Author: Michail Tsagris, Giorgos Athineou, Anamul Sajib, Eli Amson, Micah J. Waldstein
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

Diff between Directional versions 4.6 dated 2021-01-09 and 4.7 dated 2021-02-15

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Package crul updated to version 1.1.0 with previous version 1.0.0 dated 2020-07-30

Title: HTTP Client
Description: A simple HTTP client, with tools for making HTTP requests, and mocking HTTP requests. The package is built on R6, and takes inspiration from Ruby's 'faraday' gem (<https://rubygems.org/gems/faraday>). The package name is a play on curl, the widely used command line tool for HTTP, and this package is built on top of the R package 'curl', an interface to 'libcurl' (<https://curl.se/libcurl/>).
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between crul versions 1.0.0 dated 2020-07-30 and 1.1.0 dated 2021-02-15

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New package collin with initial version 0.0.1
Package: collin
Type: Package
Title: Effects of Collinearity in Distributed Lag and Other Models
Version: 0.0.1
Authors@R: c(person("Jose", "Barrera-Gomez", email = "jose.barrera@isglobal.org", role = c("aut", "cre")), person("Xavier", "Basagana", role = "aut"))
Description: Visual tool to assessing whether the results of a study could be driven by collinearity. The methods are described in Basagana X, Barrera-Gomez J (2021) "Visualizing the effects of collinearity in distributed lag models". International Journal of Epidemiology (under review).
Depends: R (>= 3.6.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dlnm, graphics, grDevices, MASS, mgcv, nlme, stats, utils, VGAM
Suggests: knitr, rmarkdown, splines, xtable
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-11 19:56:54 UTC; jbarrera
Author: Jose Barrera-Gomez [aut, cre], Xavier Basagana [aut]
Maintainer: Jose Barrera-Gomez <jose.barrera@isglobal.org>
Repository: CRAN
Date/Publication: 2021-02-15 16:30:02 UTC

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New package CHOIRBM with initial version 0.0.2
Package: CHOIRBM
Title: Plots the CHOIR Body Map
Version: 0.0.2
Authors@R: c(person(given = "Eric", family = "Cramer", role = c("aut", "cre"), email = "emcramer@stanford.edu", comment = c(ORCID = "0000-0003-2085-3679")), person(given = "Stanford University School of Medicine", role = c("cph", "fnd")))
Description: Collection of utility functions for visualizing body map data collected with the Collaborative Health Outcomes Information Registry.
License: MIT + file LICENSE
URL: https://github.com/emcramer/CHOIRBM
BugReports: https://github.com/emcramer/CHOIRBM/issues
Depends: R (>= 3.5.0)
Imports: ggplot2, rlang, stringr
Suggests: knitr, rmarkdown, testthat (>= 2.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-11 22:15:35 UTC; crame
Author: Eric Cramer [aut, cre] (<https://orcid.org/0000-0003-2085-3679>), Stanford University School of Medicine [cph, fnd]
Maintainer: Eric Cramer <emcramer@stanford.edu>
Repository: CRAN
Date/Publication: 2021-02-15 16:50:11 UTC

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Package yamlet updated to version 0.6.5 with previous version 0.5.3 dated 2021-01-21

Title: Versatile Curation of Table Metadata
Description: A YAML-based mechanism for working with table metadata. It supports compact syntax for creating, modifying, viewing, exporting, importing, displaying, and plotting metadata coded as column attributes. The 'yamlet' dialect is valid 'YAML' with defaults and conventions chosen to improve readability. See ?yamlet, ?decorate.data.frame and ?modify.default. See ?read_yamlet ?write_yamlet, ?io_csv, and ?ggplot.decorated.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

Diff between yamlet versions 0.5.3 dated 2021-01-21 and 0.6.5 dated 2021-02-15

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New package rnrfa with initial version 2.0.4
Package: rnrfa
Title: UK National River Flow Archive Data from R
Version: 2.0.4
Authors@R: c(person("Claudia", "Vitolo", email = "cvitolodev@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4252-1176")), person("Matthew", "Fry", role = c("ctb"), comment = "Matthew supervised the unofficial API integration."), person("Wouter", "Buytaert", role = c("ctb"), comment = "This package is part of Claudia Vitolo's PhD work and Wouter is the supervisor."), person("Michael", "Spencer", role = c("ctb"), comment = "Michael updated the function osg_parse to work with grid references of different lengths."), person("Tobias", "Gauster", role = c("ctb"), comment = "Tobias improved the function osg_parse introducing vectorisation"), person("Ilaria", "Prosdocimi", role = c("ctb"), comment = "Ilaria contributed to the adaptation of the package to the 2019 API"))
Maintainer: Claudia Vitolo <cvitolodev@gmail.com>
URL: http://cvitolo.github.io/rnrfa/
BugReports: https://github.com/cvitolo/rnrfa/issues
Description: Utility functions to retrieve data from the UK National River Flow Archive (<https://nrfa.ceh.ac.uk/>, terms and conditions: <https://nrfa.ceh.ac.uk/costs-terms-and-conditions>). The package contains R wrappers to the UK NRFA data temporary-API. There are functions to retrieve stations falling in a bounding box, to generate a map and extracting time series and general information. The package is fully described in Vitolo et al (2016) "rnrfa: An R package to Retrieve, Filter and Visualize Data from the UK National River Flow Archive" <https://journal.r-project.org/archive/2016/RJ-2016-036/RJ-2016-036.pdf>.
Depends: R (>= 3.5)
Imports: rgdal, curl, jsonlite, lubridate, graphics, stats, httr, zoo, ggmap, ggplot2, sp, parallel, tibble
Suggests: testthat, knitr, covr, lintr, rmarkdown
LazyData: true
Encoding: UTF-8
License: GPL-3
Repository: CRAN
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-15 09:42:32 UTC; claudia
Author: Claudia Vitolo [aut, cre] (<https://orcid.org/0000-0002-4252-1176>), Matthew Fry [ctb] (Matthew supervised the unofficial API integration.), Wouter Buytaert [ctb] (This package is part of Claudia Vitolo's PhD work and Wouter is the supervisor.), Michael Spencer [ctb] (Michael updated the function osg_parse to work with grid references of different lengths.), Tobias Gauster [ctb] (Tobias improved the function osg_parse introducing vectorisation), Ilaria Prosdocimi [ctb] (Ilaria contributed to the adaptation of the package to the 2019 API)
Date/Publication: 2021-02-15 15:20:02 UTC

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Package mkin updated to version 1.0.3 with previous version 1.0.1 dated 2021-02-10

Title: Kinetic Evaluation of Chemical Degradation Data
Description: Calculation routines based on the FOCUS Kinetics Report (2006, 2014). Includes a function for conveniently defining differential equation models, model solution based on eigenvalues if possible or using numerical solvers. If a C compiler (on windows: 'Rtools') is installed, differential equation models are solved using automatically generated C functions. Please note that no warranty is implied for correctness of results or fitness for a particular purpose.
Author: Johannes Ranke [aut, cre, cph] (<https://orcid.org/0000-0003-4371-6538>), Katrin Lindenberger [ctb] (contributed to mkinresplot()), RenƩ Lehmann [ctb] (ilr() and invilr()), Eurofins Regulatory AG [cph] (copyright for some of the contributions of JR 2012-2014)
Maintainer: Johannes Ranke <jranke@uni-bremen.de>

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Package metagear updated to version 0.7 with previous version 0.6 dated 2020-04-11

Title: Comprehensive Research Synthesis Tools for Systematic Reviews and Meta-Analysis
Description: Functionalities for facilitating systematic reviews, data extractions, and meta-analyses. It includes a GUI (graphical user interface) to help screen the abstracts and titles of bibliographic data; tools to assign screening effort across multiple collaborators/reviewers and to assess inter- reviewer reliability; tools to help automate the download and retrieval of journal PDF articles from online databases; figure and image extractions from PDFs; web scraping of citations; automated and manual data extraction from scatter-plot and bar-plot images; PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow diagrams; simple imputation tools to fill gaps in incomplete or missing study parameters; generation of random effects sizes for Hedges' d, log response ratio, odds ratio, and correlation coefficients for Monte Carlo experiments; covariance equations for modelling dependencies among multiple effect sizes (e.g., effect sizes with a common control); and finally summaries that replicate analyses and outputs from widely used but no longer updated meta-analysis software (i.e., metawin). Funding for this package was supported by National Science Foundation (NSF) grants DBI-1262545 and DEB-1451031. CITE: Lajeunesse, M.J. (2016) Facilitating systematic reviews, data extraction and meta-analysis with the metagear package for R. Methods in Ecology and Evolution 7, 323-330 <doi:10.1111/2041-210X.12472>.
Author: Marc J. Lajeunesse [aut, cre] (<https://orcid.org/0000-0002-9678-2080>)
Maintainer: Marc J. Lajeunesse <lajeunesse@usf.edu>

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Package lifecycle updated to version 1.0.0 with previous version 0.2.0 dated 2020-03-06

Title: Manage the Life Cycle of your Package Functions
Description: Manage the life cycle of your exported functions with shared conventions, documentation badges, and user-friendly deprecation warnings.
Author: Lionel Henry [aut, cre], Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>), RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>

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Package epwshiftr updated to version 0.1.2 with previous version 0.1.1 dated 2020-08-11

Title: Create Future 'EnergyPlus' Weather Files using 'CMIP6' Data
Description: Query, download climate change projection data from the 'CMIP6' (Coupled Model Intercomparison Project Phase 6) project <https://pcmdi.llnl.gov/CMIP6/> in the 'ESGF' (Earth System Grid Federation) platform <https://esgf.llnl.gov>, and create future 'EnergyPlus' <https://energyplus.net> Weather ('EPW') files adjusted from climate changes using data from Global Climate Models ('GCM').
Author: Hongyuan Jia [aut, cre] (<https://orcid.org/0000-0002-0075-8183>), Adrian Chong [aut] (<https://orcid.org/0000-0002-9486-4728>)
Maintainer: Hongyuan Jia <hongyuan.jia@bears-berkeley.sg>

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New package dynamichazard with initial version 0.6.8
Package: dynamichazard
Type: Package
Title: Dynamic Hazard Models using State Space Models
Version: 0.6.8
Authors@R: c(person("Benjamin", "Christoffersen", email = "boennecd@gmail.com", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-7182-1346")), person("Alan", "Miller", role = c("cph")), person("Anthony", "Williams", role = c("cph")), person("Boost developers", role = c("cph")), person("R-core", email = "R-core@R-project.org", role = c("cph")))
Description: Contains functions that lets you fit dynamic hazard models using state space models. The first implemented model is described in Fahrmeir (1992) <doi:10.1080/01621459.1992.10475232> and Fahrmeir (1994) <doi:10.1093/biomet/81.2.317>. Extensions hereof are available where the Extended Kalman filter is replaced by an unscented Kalman filter and other options including particle filters. The implemented particle filters support more general state space models.
License: GPL-2
LazyData: TRUE
LinkingTo: Rcpp, RcppArmadillo
Imports: parallel, Rcpp (>= 0.12.6), boot
Depends: R (>= 3.5.0), stats, graphics, utils, survival
RoxygenNote: 7.1.1
Suggests: testthat, knitr, rmarkdown, timereg, captioner, biglm, httr, mgcv, shiny, formatR, R.rsp, speedglm, dichromat, colorspace, plyr, gsl, mvtnorm, nloptr (>= 1.2.0)
VignetteBuilder: knitr, R.rsp
BugReports: https://github.com/boennecd/dynamichazard/issues
SystemRequirements: C++11
URL: https://github.com/boennecd/dynamichazard
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2021-02-15 14:25:48 UTC; boennecd
Author: Benjamin Christoffersen [cre, aut] (<https://orcid.org/0000-0002-7182-1346>), Alan Miller [cph], Anthony Williams [cph], Boost developers [cph], R-core [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-15 15:20:09 UTC

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Package BiDAG updated to version 2.0.0 with previous version 1.4.1 dated 2020-07-14

Title: Bayesian Inference for Directed Acyclic Graphs
Description: Implementation of a collection of MCMC methods for Bayesian structure learning of directed acyclic graphs (DAGs), both from continuous and discrete data. For efficient inference on larger DAGs, the space of DAGs is pruned according to the data. To filter the search space, the algorithm employs a hybrid approach, combining constraint-based learning with search and score. A reduced search space is initially defined on the basis of a skeleton obtained by means of the PC-algorithm, and then iteratively improved with search and score. Search and score is then performed following two approaches: Order MCMC, or Partition MCMC. The BGe score is implemented for continuous data and the BDe score is implemented for binary data or categorical data. The algorithms may provide the maximum a posteriori (MAP) graph or a sample (a collection of DAGs) from the posterior distribution given the data. All algorithms are also applicable for structure learning and sampling for dynamic Bayesian networks. References: J. Kuipers, P. Suter and G. Moffa (2018) <arXiv:1803.07859v2>, N. Friedman and D. Koller (2003) <doi:10.1023/A:1020249912095>, D. Geiger and D. Heckerman (2002) <doi:10.1214/aos/1035844981>, J. Kuipers and G. Moffa (2017) <doi:10.1080/01621459.2015.1133426>, M. Kalisch et al.(2012) <doi:10.18637/jss.v047.i11>.
Author: Polina Suter [aut, cre], Jack Kuipers [aut]
Maintainer: Polina Suter <polina.suter@bsse.ethz.ch>

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New package bfp with initial version 0.0-42
Package: bfp
Version: 0.0-42
Date: 2021-02-15
Title: Bayesian Fractional Polynomials
Authors@R: c(person("Daniel", "Sabanes Bove", email="daniel.sabanesbove@gmx.net", role = c("aut", "cre")), person("Isaac", "Gravestock", email="isaac.gravestock@uzh.ch", role="aut"), person("Robert", "Davies", role="cph"), person("Stephen", "Moshier", role="cph"))
Depends: R (>= 3.0.0)
Imports: Rcpp (>= 0.11.0)
LinkingTo: Rcpp
Suggests: doBy, SoDA, Hmisc, mfp
SystemRequirements: GNU make, C++11
Description: Implements the Bayesian paradigm for fractional polynomial models under the assumption of normally distributed error terms, see Sabanes Bove, D. and Held, L. (2011) <doi:10.1007/s11222-010-9170-7>.
License: GPL (>= 2)
Copyright: hyp2f1 is from Cephes Math Library Release 2.3, Copyright 1995 by Stephen L. Moshier. Newmat is Copyright 1991-2005 by Robert B. Davies.
Author: Daniel Sabanes Bove [aut, cre], Isaac Gravestock [aut], Robert Davies [cph], Stephen Moshier [cph]
Maintainer: Daniel Sabanes Bove <daniel.sabanesbove@gmx.net>
Repository: CRAN
Repository/R-Forge/Project: bfp
Repository/R-Forge/Revision: 161
Repository/R-Forge/DateTimeStamp: 2021-02-15 09:17:01
Date/Publication: 2021-02-15 15:40:07 UTC
NeedsCompilation: yes
Packaged: 2021-02-15 09:30:42 UTC; rforge

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Package spatstat.Knet updated to version 1.65-0 with previous version 1.12-2 dated 2020-04-27

Title: Extension to 'spatstat' for Large Datasets on a Linear Network
Description: Extension to the 'spatstat' family of packages, for analysing large datasets of spatial points on a network. The geometrically- corrected K function is computed using a memory-efficient tree-based algorithm described by Rakshit, Baddeley and Nair (2019).
Author: Suman Rakshit [aut, cph] (<https://orcid.org/0000-0003-0052-128X>), Adrian Baddeley [cre, cph] (<https://orcid.org/0000-0001-9499-8382>)
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package rasciidoc updated to version 3.1.0 with previous version 3.0.2 dated 2021-02-01

Title: Create Reports Using R and 'asciidoc'
Description: Inspired by Karl Broman`s reader on using 'knitr' with 'asciidoc' (<http://kbroman.org/knitr_knutshell/pages/asciidoc.html>), this is merely a wrapper to 'knitr' and 'asciidoc'.
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>

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Package osmextract updated to version 0.2.1 with previous version 0.2.0 dated 2021-02-11

Title: Download and Read OpenStreetMap Data Extracts
Description: Find, download, convert and read Open Street Map data extracts obtained from several providers.
Author: Andrea Gilardi [aut, cre] (<https://orcid.org/0000-0002-9424-7439>), Robin Lovelace [aut] (<https://orcid.org/0000-0001-5679-6536>), Barry Rowlingson [ctb] (<https://orcid.org/0000-0002-8586-6625>), Salva FernƔndez [rev] (Salva reviewed the package (v. 0.1) for rOpenSci, see <https://github.com/ropensci/software-review/issues/395>), Nicholas Potter [rev] (Nicholas reviewed the package (v. 0.1) for rOpenSci, see <https://github.com/ropensci/software-review/issues/395>)
Maintainer: Andrea Gilardi <andrea.gilardi@unimib.it>

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Package monoClust updated to version 1.2.1 with previous version 1.2.0 dated 2020-11-24

Title: Perform Monothetic Clustering with Extensions to Circular Data
Description: Implementation of the Monothetic Clustering algorithm (Chavent, 1998 <doi:10.1016/S0167-8655(98)00087-7>) on continuous data sets. A lot of extensions are included in the package, including applying Monothetic clustering on data sets with circular variables, visualizations with the results, and permutation and cross-validation based tests to support the decision on the number of clusters.
Author: Tan Tran [aut, cre] (<https://orcid.org/0000-0001-9881-6339>), Brian McGuire [aut], Mark Greenwood [aut] (<https://orcid.org/0000-0001-6933-1201>)
Maintainer: Tan Tran <vinhtantran@gmail.com>

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Package jsmodule updated to version 1.1.6 with previous version 1.1.5 dated 2021-01-17

Title: 'RStudio' Addins and 'Shiny' Modules for Medical Research
Description: 'RStudio' addins and 'Shiny' modules for descriptive statistics, regression and survival analysis.
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>), Zarathu [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

Diff between jsmodule versions 1.1.5 dated 2021-01-17 and 1.1.6 dated 2021-02-15

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Package insight updated to version 0.13.0 with previous version 0.12.0 dated 2021-01-14

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel LĆ¼decke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>, @strengejacke), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>, @Dom_Makowski), Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Mattan S. Ben-Shachar [aut, ctb] (<https://orcid.org/0000-0002-4287-4801>)
Maintainer: Daniel LĆ¼decke <d.luedecke@uke.de>

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Package dm updated to version 0.1.12 with previous version 0.1.10 dated 2021-01-07

Title: Relational Data Models
Description: Provides tools for working with multiple related tables, stored as data frames or in a relational database. Multiple tables (data and metadata) are stored in a compound object, which can then be manipulated with a pipe-friendly syntax.
Author: Tobias Schieferdecker [aut], Kirill MĆ¼ller [aut, cre] (<https://orcid.org/0000-0002-1416-3412>), Darko Bergant [aut], Katharina Brunner [ctb], James Wondrasek [ctb], energie360Ā° AG [fnd], cynkra GmbH [fnd, cph]
Maintainer: Kirill MĆ¼ller <krlmlr+r@mailbox.org>

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Package cutpointr updated to version 1.1.0 with previous version 1.0.32 dated 2020-06-19

Title: Determine and Evaluate Optimal Cutpoints in Binary Classification Tasks
Description: Estimate cutpoints that optimize a specified metric in binary classification tasks and validate performance using bootstrapping. Some methods for more robust cutpoint estimation are supported, e.g. a parametric method assuming normal distributions, bootstrapped cutpoints, and smoothing of the metric values per cutpoint using Generalized Additive Models. Various plotting functions are included. For an overview of the package see Thiele and Hirschfeld (2020) <arXiv:2002.09209>.
Author: Christian Thiele [cre, aut] (<https://orcid.org/0000-0002-1156-5117>)
Maintainer: Christian Thiele <c.thiele@gmx-topmail.de>

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New package autoharp with initial version 0.0.5
Package: autoharp
Title: Semi-Automatic Grading of R and Rmd Scripts
Version: 0.0.5
Authors@R: c( person("Vik", "Gopal", email="vik.gopal@nus.edu.sg", role=c("aut", "cre")), person("Samuel", "Seah", email="samuelseah@u.nus.edu", role="aut"), person("Viknesh", "Jeya Kumar", email="viknesh@u.nus.edu", role="aut"), person("Gabriel", "Ang", email="gabrielang@u.nus.edu", role="aut"), person("Ruofan", "Liu", email="kelseyliu1998@gmail.com", role="ctb"), person("National University of Singapore", role="cph"))
Description: A customisable set of tools for assessing and grading R or R-markdown scripts from students. It allows for checking correctness of code output, runtime statistics and static code analysis. The latter feature is made possible by representing R expressions using a tree structure.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: magrittr, dplyr, stringr, rlang, tidyr, tibble, knitr, rmarkdown, pryr, shiny, lintr, methods, igraph, testthat
Collate: 'treeharp.R' 'th_getter-length.R' 'as.matrix.R' 'check_correctness.R' 'check_rmd.R' 'check_runtime.R' 'count_lints.R' 'env_size.R' 'examplify_to_r.R' 'forestharp.R' 'forestharp_helpers.R' 'generate_thumbnails.R' 'join_treeharp.R' 'lang_2_tree.R' 'lang_2_tree_helpers.R' 'log_summary.R' 'lum_local_match.R' 'nlp_related.R' 'populate_soln_env.R' 'render_one.R' 'reset_path.R' 'run_tuner.R' 'to_BFS.R' 'tree_kernel.R' 'tree_routines.R' 'utils-pipe.R' 'utils.R' 'write_html.R' 'zzz.R'
Suggests: readxl, xml2, rvest, formatR
SystemRequirements: pandoc (>= 1.14) - http://pandoc.org
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-15 13:33:34 UTC; viknesh
Author: Vik Gopal [aut, cre], Samuel Seah [aut], Viknesh Jeya Kumar [aut], Gabriel Ang [aut], Ruofan Liu [ctb], National University of Singapore [cph]
Maintainer: Vik Gopal <vik.gopal@nus.edu.sg>
Repository: CRAN
Date/Publication: 2021-02-15 14:50:07 UTC

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Package ausplotsR updated to version 1.2.2 with previous version 1.2.1 dated 2020-12-17

Title: TERN AusPlots Analysis Package
Description: Extraction, preparation, visualisation and analysis of TERN AusPlots ecosystem monitoring data. Direct access to plot-based data on vegetation and soils across Australia, including physical sample barcode numbers. Simple function calls extract the data and merge them into species occurrence matrices for downstream analysis, or calculate things like basal area and fractional cover. TERN AusPlots is a national field plot-based ecosystem surveillance monitoring method and dataset for Australia. The data have been collected across a national network of plots and transects by the Terrestrial Ecosystem Research Network (TERN - <https://www.tern.org.au>), an Australian Government NCRIS-enabled project, and its Ecosystem Surveillance platform (<https://www.tern.org.au/tern-observatory/tern-ecosystem-surveillance/>).
Author: Greg Guerin [aut, cre], Tom Saleeba [aut], Samantha Munroe [aut], Bernardo Blanco-Martin [aut], Irene Martƭn-ForƩs [aut], Andrew Tokmakoff [aut]
Maintainer: Greg Guerin <ggueri01@gmail.com>

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Package ggquickeda updated to version 0.2.0 with previous version 0.1.9 dated 2020-12-16

Title: Quickly Explore Your Data Using 'ggplot2' and 'table1' Summary Tables
Description: Quickly and easily perform exploratory data analysis by uploading your data as a 'csv' file. Start generating insights using 'ggplot2' plots and 'table1' tables with descriptive stats, all using an easy-to-use point and click 'Shiny' interface.
Author: Samer Mouksassi [aut, cre] (<https://orcid.org/0000-0002-7152-6654>), Dean Attali [aut], Benjamin Rich [aut] (provided summary stats tables tab code), Michael Sachs [aut] (provided ggkm code)
Maintainer: Samer Mouksassi <samermouksassi@gmail.com>

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Package asnipe updated to version 1.1.15 with previous version 1.1.13 dated 2020-09-23

Title: Animal Social Network Inference and Permutations for Ecologists
Description: Implements several tools that are used in animal social network analysis, as described in Whitehead (2007) Analyzing Animal Societies <University of Chicago Press> and Farine & Whitehead (2015) <doi: 10.1111/1365-2656.12418>. In particular, this package provides the tools to infer groups and generate networks from observation data, perform permutation tests on the data, calculate lagged association rates, and performed multiple regression analysis on social network data.
Author: Damien R. Farine <dfarine@ab.mpg.de>
Maintainer: Damien R. Farine <dfarine@ab.mpg.de>

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Package WRS2 updated to version 1.1-1 with previous version 1.1-0 dated 2020-06-19

Title: A Collection of Robust Statistical Methods
Description: A collection of robust statistical methods based on Wilcox' WRS functions. It implements robust t-tests (independent and dependent samples), robust ANOVA (including between-within subject designs), quantile ANOVA, robust correlation, robust mediation, and nonparametric ANCOVA models based on robust location measures.
Author: Patrick Mair [cre, aut], Rand Wilcox [aut]
Maintainer: Patrick Mair <mair@fas.harvard.edu>

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Package smacof updated to version 2.1-2 with previous version 2.1-1 dated 2020-06-29

Title: Multidimensional Scaling
Description: Implements the following approaches for multidimensional scaling (MDS) based on stress minimization using majorization (smacof): ratio/interval/ordinal/spline MDS on symmetric dissimilarity matrices, MDS with external constraints on the configuration, individual differences scaling (idioscal, indscal), MDS with spherical restrictions, and ratio/interval/ordinal/spline unfolding (circular restrictions, row-conditional). Various tools and extensions like jackknife MDS, bootstrap MDS, permutation tests, MDS biplots, gravity models, unidimensional scaling, drift vectors (asymmetric MDS), classical scaling, and Procrustes are implemented as well.
Author: Patrick Mair [aut, cre], Jan De Leeuw [aut], Patrick J. F. Groenen [aut], Ingwer Borg [ctb]
Maintainer: Patrick Mair <mair@fas.harvard.edu>

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Package homals updated to version 1.0-9 with previous version 1.0-8 dated 2018-05-26

Title: Gifi Methods for Optimal Scaling
Description: Performs a homogeneity analysis (multiple correspondence analysis) and various extensions. Rank restrictions on the category quantifications can be imposed (nonlinear PCA). The categories are transformed by means of optimal scaling with options for nominal, ordinal, and numerical scale levels (for rank-1 restrictions). Variables can be grouped into sets, in order to emulate regression analysis and canonical correlation analysis.
Author: Patrick Mair [aut, cre], Jan De Leeuw [aut]
Maintainer: Patrick Mair <mair@fas.harvard.edu>

Diff between homals versions 1.0-8 dated 2018-05-26 and 1.0-9 dated 2021-02-15

 homals-1.0-8/homals/R/plot3d.homals.R  |only
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 8 files changed, 49 insertions(+), 64 deletions(-)

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Package eRm updated to version 1.0-2 with previous version 1.0-1 dated 2020-03-03

Title: Extended Rasch Modeling
Description: Fits Rasch models (RM), linear logistic test models (LLTM), rating scale model (RSM), linear rating scale models (LRSM), partial credit models (PCM), and linear partial credit models (LPCM). Missing values are allowed in the data matrix. Additional features are the ML estimation of the person parameters, Andersen's LR-test, item-specific Wald test, Martin-Loef-Test, nonparametric Monte-Carlo Tests, itemfit and personfit statistics including infit and outfit measures, ICC and other plots, automated stepwise item elimination, simulation module for various binary data matrices.
Author: Patrick Mair [cre, aut], Reinhold Hatzinger [aut], Marco J. Maier [aut], Thomas Rusch [ctb], Rudolf Debelak [ctb]
Maintainer: Patrick Mair <mair@fas.harvard.edu>

Diff between eRm versions 1.0-1 dated 2020-03-03 and 1.0-2 dated 2021-02-15

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 18 files changed, 867 insertions(+), 850 deletions(-)

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New package eflm with initial version 0.1
Package: eflm
Title: Efficient Fitting of Linear and Generalized Linear Models
Version: 0.1
Authors@R: c( person(given = "Mauricio", family = "Vargas", role = c("aut", "cre"), email = "mvargas@dcc.uchile.cl", comment = c(ORCID = "0000-0003-1017-7574")), person(given = "Alexey", family = "Kravchenko", role = c("ths"), email = "kravchenkoa@un.org"), person(given = "Constanza", family = "Prado", role = c("ths"), email = "mcprado@uc.cl"), person(given = "Yoto", family = "Yotov", role = c("ths"), email = "yvy23@drexel.edu"), person(family = "The United Nations", role = c("dtc", "cph", "fnd") ) )
Description: Efficient Fitting of Linear and Generalized Linear Models by using just base R. As an alternative to lm() and glm(), this package provides elm() and eglm(), with a significant speedup when the number of observations is larger than the number of parameters to estimate, as it reduces the NxP model matrix to a PxP matrix. The best computational performance is obtained when R is linked against 'OpenBLAS', 'Intel MKL' or other optimized 'BLAS' library. This implementation aims at being compatible with 'broom' and 'sandwich' packages for summary statistics and clustering by providing S3 methods.
URL: https://github.com/pachamaltese/eflm/
BugReports: https://github.com/pachamaltese/eflm/issues/
License: GPL (>= 3)
Imports: stats, zoo, methods, utils, vctrs
Suggests: testthat (>= 3.0.0), covr, sandwich, MASS, tibble, broom
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-11 19:59:30 UTC; pacha
Author: Mauricio Vargas [aut, cre] (<https://orcid.org/0000-0003-1017-7574>), Alexey Kravchenko [ths], Constanza Prado [ths], Yoto Yotov [ths], The United Nations [dtc, cph, fnd]
Maintainer: Mauricio Vargas <mvargas@dcc.uchile.cl>
Repository: CRAN
Date/Publication: 2021-02-15 11:10:02 UTC

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New package ecolTest with initial version 0.0.1
Package: ecolTest
Title: Community Ecology Tests
Version: 0.0.1
Authors@R: c(person(given = "Hugo", family = "Salinas", role = c("aut", "cre"), email = "hugosal@comunidad.unam.mx"), person(given = "David", family = "Ramirez-Delgado", role = c("aut"), email = "linfocitoth1@gmail.com"))
Description: Functions and data sets to perform and demonstrate community ecology statistical tests, including Hutcheson's t-test (Hutcheson (1970) <doi:10.1016/0022-5193(70)90124-4>, Zar (2010) ISBN:9780321656865).
Imports: stats
License: MIT + file LICENSE
Encoding: UTF-8
BugReports: https://github.com/hugosal/ecolTest/issues
URL: https://github.com/hugosal/ecolTest
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-02-11 18:29:15 UTC; hugo
Author: Hugo Salinas [aut, cre], David Ramirez-Delgado [aut]
Maintainer: Hugo Salinas <hugosal@comunidad.unam.mx>
Repository: CRAN
Date/Publication: 2021-02-15 11:00:02 UTC

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Package vlad updated to version 0.2.2 with previous version 0.2.1 dated 2020-08-24

Title: Variable Life Adjusted Display and Other Risk-Adjusted Quality Control Charts
Description: Contains functions to set up risk-adjusted quality control charts in health care. For the variable life adjusted display (VLAD) proposed by Lovegrove et al. (1997) <doi:10.1016/S0140-6736(97)06507-0> signaling rules derived in Wittenberg et al. (2018) <doi:10.1002/sim.7647> are implemented. Additionally, for the risk-adjusted cumulative sum chart based on log-likelihood ratio statistic introduced by Steiner et al. (2000) <doi:10.1093/biostatistics/1.4.441> average run length and control limits can be computed with fast and accurate Markov chain approximations developed in Knoth et al. (2019) <doi:10.1002/sim.8104>.
Author: Philipp Wittenberg [aut, cre] (<https://orcid.org/0000-0001-7151-8243>), Sven Knoth [aut, ths] (<https://orcid.org/0000-0002-9666-5554>)
Maintainer: Philipp Wittenberg <pwitten@hsu-hh.de>

Diff between vlad versions 0.2.1 dated 2020-08-24 and 0.2.2 dated 2021-02-15

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 vlad-0.2.2/vlad/tests/testthat/test-racusum_beta_crit_mc.R  |    2 
 vlad-0.2.2/vlad/tests/testthat/test-racusum_beta_crit_sim.R |    6 
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 45 files changed, 301 insertions(+), 320 deletions(-)

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New package upstartr with initial version 0.1.0
Package: upstartr
Type: Package
Title: Utilities Powering the Globe and Mail's Data Journalism Template
Version: 0.1.0
Authors@R: c(person(given = "Tom", family = "Cardoso", email = "tcardoso@globeandmail.com", role = c("aut", "cre"), comment = "creator and maintainer"), person(given = "Michael", family = "Pereira", email = "hello@monkeycycle.org", role = c("ctb")), person(given = "The Globe and Mail Inc.", role = c("cph")))
Maintainer: Tom Cardoso <tcardoso@globeandmail.com>
Description: Core functions necessary for using The Globe and Mail's R data journalism template, 'startr', along with utilities for day-to-day data journalism tasks, such as reading and writing files, producing graphics and cleaning up datasets.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: here, stringr, readxl, magrittr, readr, purrr, ggplot2, glue, dplyr, librarian, openxlsx, knitr, beepr, tidytext, scales, rmarkdown, textclean, sf, tgamtheme, crayon
Suggests: testthat (>= 3.0.0)
Language: en-US
URL: https://github.com/globeandmail/upstartr, https://globeandmail.github.io/upstartr/
BugReports: https://github.com/globeandmail/upstartr/issues
RoxygenNote: 7.1.1
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2021-02-11 17:07:42 UTC; tcardoso
Author: Tom Cardoso [aut, cre] (creator and maintainer), Michael Pereira [ctb], The Globe and Mail Inc. [cph]
Repository: CRAN
Date/Publication: 2021-02-15 10:50:02 UTC

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New package runexp with initial version 0.1.0
Package: runexp
Type: Package
Title: Softball Run Expectancy using Markov Chains and Simulation
Version: 0.1.0
Authors@R: c( person("Annie", "Sauer", role = c("aut", "cre"), email = "anniees@vt.edu"), person("Sierra", "Merkes", role = "aut", email = "smerkes@vt.edu"))
Depends: R (>= 3.6)
Description: Implements two methods of estimating runs scored in a softball scenario: (1) theoretical expectation using discrete Markov chains and (2) empirical distribution using multinomial random simulation. Scores are based on player-specific input probabilities (out, single, double, triple, walk, and homerun). Optional inputs include probability of attempting a steal, probability of succeeding in an attempted steal, and an indicator of whether a player is "fast" (e.g. the player could stretch home). These probabilities may be calculated from common player statistics that are publicly available on team's webpages. Scores are evaluated based on a nine-player lineup and may be used to compare lineups, evaluate base scenarios, and compare the offensive potential of individual players. Manuscript forthcoming. See Bukiet & Harold (1997) <doi:10.1287/opre.45.1.14> for implementation of discrete Markov chains.
License: LGPL
LazyData: true
Encoding: UTF-8
Imports: stringr, doParallel, foreach, parallel
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-11 15:59:08 UTC; anniesauer
Author: Annie Sauer [aut, cre], Sierra Merkes [aut]
Maintainer: Annie Sauer <anniees@vt.edu>
Repository: CRAN
Date/Publication: 2021-02-15 10:40:02 UTC

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Package robslopes updated to version 1.0.2 with previous version 1.0.1 dated 2021-02-04

Title: Fast Algorithms for Robust Slopes
Description: Fast algorithms for the Theil-Sen estimator and Siegel's repeated median slope estimator. The implementation is based on algorithms by Dillencourt et. al (1992) <doi:10.1142/S0218195992000020> and Matousek et. al (1998) <doi:10.1007/PL00009190>. Both algorithms run in quasilinear time.
Author: Jakob Raymaekers
Maintainer: Jakob Raymaekers <jakob.raymaekers@kuleuven.be>

Diff between robslopes versions 1.0.1 dated 2021-02-04 and 1.0.2 dated 2021-02-15

 DESCRIPTION                      |    8 ++++----
 MD5                              |   16 ++++++++--------
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 R/RepeatedMedian.R               |    5 ++++-
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 src/HelpFunctions.cpp            |    4 ++--
 src/RcppExports.cpp              |   21 +++++++++++----------
 src/rcpparma_Theil_Sen.cpp       |   35 +++++++++++++++++++++--------------
 src/rcpparma_repeated_median.cpp |   28 ++++++++++++++++------------
 9 files changed, 80 insertions(+), 63 deletions(-)

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New package POSetR with initial version 1.0
Package: POSetR
Type: Package
Title: Partially Ordered Sets in R
Version: 1.0
Date: 2021-02-10
Authors@R: c(person("Alberto", "Arcagni", role = c("aut", "cre"), email = "alberto.arcagni@uniroma1.it"), person("Alessandro", "Avellone", role = c("aut"), email = "alessandro.avellone@unimib.it"), person("Marco", "Fattore", role = c("aut"), email = "marco.fattore@unimib.it"))
Author: Alberto Arcagni [aut, cre], Alessandro Avellone [aut], Marco Fattore [aut]
Maintainer: Alberto Arcagni <alberto.arcagni@uniroma1.it>
Description: Provides a set of basic tools for generating, analyzing, summarizing and visualizing finite partially ordered sets. In particular, it implements flexible and very efficient algorithms for the extraction of linear extensions and for the computation of mutual ranking probabilities and other user-defined functionals, over them. The package is meant as a computationally efficient "engine", for the implementation of data analysis procedures, on systems of multidimensional ordinal indicators and partially ordered data, in the spirit of Fattore, M. (2016) "Partially ordered sets and the measurement of multidimensional ordinal deprivation", Social Indicators Research <DOI:10.1007/s11205-015-1059-6>, and Fattore M. and Arcagni, A. (2018) "A reduced posetic approach to the measurement of multidimensional ordinal deprivation", Social Indicators Research <DOI:10.1007/s11205-016-1501-4>.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.0), igraph, methods, Rdpack
RdMacros: Rdpack
LinkingTo: Rcpp
SystemRequirements: C++17
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2021-02-11 14:55:41 UTC; Alberto
Repository: CRAN
Date/Publication: 2021-02-15 10:10:08 UTC

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New package percentiles with initial version 0.2.1
Package: percentiles
Type: Package
Title: Calculate (Stratified) Percentiles
Version: 0.2.1
Author: J. Peter Marquardt <peter@kmarquardt.de> [aut, cre]
Maintainer: J. Peter Marquardt <peter@kmarquardt.de>
Description: Calculate (stratified) percentiles on a data.frame Stratification will split the data.frame into subgroups and calculate percentiles for each independently.
Depends: R (>= 4.0.0)
Imports: dplyr, assertive.types, R6
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-11 15:02:34 UTC; Peter
Repository: CRAN
Date/Publication: 2021-02-15 10:10:05 UTC

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New package bhmbasket with initial version 0.9.1
Package: bhmbasket
Title: Bayesian Hierarchical Models for Basket Trials
Version: 0.9.1
Authors@R: person(given = 'Stephan', family = 'Wojciekowski', role = c('aut', 'cre'), email = 'stephan.wojciekowski@boehringer-ingelheim.com')
Description: Provides functions for the evaluation of basket trial designs with binary endpoints. Operating characteristics of a basket trial design are assessed by simulating trial data according to scenarios, analyzing the data with Bayesian hierarchical models (BHMs), and assessing decision probabilities based on Go / No-go decision making. The BHMs proposed by Berry et al. (2013) <doi:10.1177/1740774513497539> and Neuenschwander et al. (2016) <doi:10.1002/pst.1730>, as well as a model that combines both approaches are implemented. Functions are provided to implement Bayesian decision rules as for example proposed by Fisch et al. (2015) <doi:10.1177/2168479014533970>. In addition, posterior point estimates (mean/median) and credible intervals for response rates and some model parameters can be calculated. For simulated trial data, bias and mean squared errors of posterior point estimates for response rates can be provided.
License: GPL-3
URL: https://CRAN.R-project.org/package=bhmbasket
Depends: R (>= 3.5.0)
Imports: doParallel, foreach, parallel, R2jags
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
NeedsCompilation: no
Packaged: 2021-02-11 17:17:29 UTC; Stephan
Author: Stephan Wojciekowski [aut, cre]
Maintainer: Stephan Wojciekowski <stephan.wojciekowski@boehringer-ingelheim.com>
Repository: CRAN
Date/Publication: 2021-02-15 10:50:05 UTC

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Package aweSOM updated to version 1.1 with previous version 1.0 dated 2021-01-22

Title: Interactive Self-Organizing Maps
Description: Self-organizing maps (also known as SOM, see Kohonen (2001) <doi:10.1007/978-3-642-56927-2>) are a method for dimensionality reduction and clustering of continuous data. This package introduces interactive (html) graphics for easier analysis of SOM results. It also features an interactive interface, for push-button training and visualization of SOM on numeric, categorical or mixed data, as well as tools to evaluate the quality of SOM.
Author: Julien Boelaert [aut, cre], Etienne Ollion [aut], Jan Sodoge [aut], Mohamed Megdoud [ctb], Otmane Naji [ctb], Arnaud Lemba Kote [ctb], Theo Renoud [ctb], Samuel Hym [ctb]
Maintainer: Julien Boelaert <julien.boelaert@univ-lille.fr>

Diff between aweSOM versions 1.0 dated 2021-01-22 and 1.1 dated 2021-02-15

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Package aliases2entrez updated to version 0.1.2 with previous version 0.1.1 dated 2020-05-19

Title: Converts Human gene symbols to entrez IDs
Description: Queries multiple resources authors HGNC (2019) <https://www.genenames.org>, authors limma (2015) <doi:10.1093/nar/gkv007> to find the correspondence between evolving nomenclature of human gene symbols, aliases, previous symbols or synonyms with stable, curated gene entrezID from NCBI database. This allows fast, accurate and up-to-date correspondence between human gene expression datasets from various date and platform (e.g: gene symbol: BRCA1 - ID: 672).
Author: Raphael Bonnet [aut, cre] (UniversitĆ© CĆ“te dā€™Azur), Lee Mariault [ctb] (UniversitĆ© CĆ“te dā€™Azur), Jean-FranƧois Peyron [aut] (Inserm)
Maintainer: Raphael Bonnet <raphael.bonnet@univ-cotedazur.fr>

Diff between aliases2entrez versions 0.1.1 dated 2020-05-19 and 0.1.2 dated 2021-02-15

 DESCRIPTION            |   13 +++++++++----
 MD5                    |    6 +++---
 R/convert_symbols.R    |   24 ++++++++++++++++++++----
 man/convert_symbols.Rd |    2 +-
 4 files changed, 33 insertions(+), 12 deletions(-)

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Package mdgc (with last version 0.1.0) was removed from CRAN

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

2021-02-15 0.1.0

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New package RClimacell with initial version 0.1.0
Package: RClimacell
Title: R Wrapper for the 'Climacell' API
Version: 0.1.0
Authors@R: person(given = "Nikhil", family = "Agarwal", role = c("aut", "cre"), email = "gitnik@niks.me", comment = c(ORCID = "0000-0003-1470-7472"))
Description: 'Climacell' is a weather platform that provides hyper-local forecasts and weather data. This package enables the user to query the core layers of the time line interface of the 'Climacell' v4 API <https://www.climacell.co/weather-api/>. This package requires a valid API key. See vignettes for instructions on use.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: dplyr (>= 1.0.0), magrittr (>= 2.0.1), stringr (>= 1.4.0), tibble (>= 3.0.6), httr (>= 1.4.2), lubridate (>= 1.7.9.2), rlang (>= 0.4.10), parsedate (>= 1.2.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-10 20:08:50 UTC; nikhil
Author: Nikhil Agarwal [aut, cre] (<https://orcid.org/0000-0003-1470-7472>)
Maintainer: Nikhil Agarwal <gitnik@niks.me>
Repository: CRAN
Date/Publication: 2021-02-15 09:20:06 UTC

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New package pcoxtime with initial version 1.0
Package: pcoxtime
Type: Package
Title: Penalized Cox Proportional Hazard Model for Time-Dependent Covariates
Version: 1.0
Authors@R: c(person("Bicko","Cygu", role=c("aut","cre"), email="cygubicko@gmail.com", comment=c(ORCID = "0000-0002-9284-8863")), person("Ben","Bolker",role="aut", comment=c(ORCID="0000-0002-2127-0443")))
Description: Fits penalized models for both time-independent and time-dependent survival data. It fully implements elastic net and uses proximal gradient descent to solve the optimization problem. The package is an implementation of Steve Cygu and Benjamin M. Bolker. (2021) <arXiv:2102.02297>.
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.5), survival, doParallel, parallel, foreach, ggplot2, prodlim, riskRegression, PermAlgo
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
URL: https://github.com/CYGUBICKO/pcoxtime-pkg
NeedsCompilation: yes
Packaged: 2021-02-10 23:19:58 UTC; steve
Author: Bicko Cygu [aut, cre] (<https://orcid.org/0000-0002-9284-8863>), Ben Bolker [aut] (<https://orcid.org/0000-0002-2127-0443>)
Maintainer: Bicko Cygu <cygubicko@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-15 09:30:02 UTC

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New package mdgc with initial version 0.1.0
Package: mdgc
Type: Package
Title: Missing Data Imputation Using Gaussian Copulas
Version: 0.1.0
Authors@R: c( person("Benjamin", "Christoffersen", email = "boennecd@gmail.com", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-7182-1346")), person("Alan", "Genz", role = "cph"), person("Frank", "Bretz", role = "cph"), person("Torsten", "Hothorn", role = "cph"), person("R-core", email = "R-core@R-project.org", role = "cph"), person("Ross", "Ihaka", role = "cph"))
Description: Provides functions to impute missing values using Gaussian copulas for mixed data types as described by Christoffersen et al. (2021) <arXiv:2102.02642>. The method is related to Hoff (2007) <doi:10.1214/07-AOAS107> and Zhao and Udell (2019) <arXiv:1910.12845> but differs by making a direct approximation of the log marginal likelihood using an extended version of the Fortran code created by Genz and Bretz (2002) <doi:10.1198/106186002394> in addition to also support multinomial variables.
License: GPL-2
BugReports: https://github.com/boennecd/mdgc/issues
URL: https://github.com/boennecd/mdgc
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
LinkingTo: Rcpp, RcppArmadillo, testthat, BH, psqn
Imports: Rcpp
Suggests: testthat, catdata
SystemRequirements: C++14
NeedsCompilation: yes
Packaged: 2021-02-11 09:45:25 UTC; boennecd
Author: Benjamin Christoffersen [cre, aut] (<https://orcid.org/0000-0002-7182-1346>), Alan Genz [cph], Frank Bretz [cph], Torsten Hothorn [cph], R-core [cph], Ross Ihaka [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-15 09:30:05 UTC

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New package kgrams with initial version 0.1.0
Package: kgrams
Title: Classical k-gram Language Models
Version: 0.1.0
Authors@R: person(given = "Valerio", family = "Gherardi", role = c("aut", "cre"), email = "vgherard@sissa.it", comment = c(ORCID = "0000-0002-8215-3013"))
Description: Tools for training and evaluating k-gram language models in R, supporting several probability smoothing techniques, perplexity computations, random text generation and more.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
SystemRequirements: C++11
LinkingTo: Rcpp, RcppProgress
Imports: Rcpp, rlang, methods, utils, RcppProgress (>= 0.1), Rdpack
Depends: R (>= 3.5)
Suggests: testthat (>= 3.0.0), covr, knitr, rmarkdown
Config/testthat/edition: 3
RdMacros: Rdpack
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-02-11 11:31:26 UTC; vale
Author: Valerio Gherardi [aut, cre] (<https://orcid.org/0000-0002-8215-3013>)
Maintainer: Valerio Gherardi <vgherard@sissa.it>
Repository: CRAN
Date/Publication: 2021-02-15 09:40:03 UTC

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New package fundiversity with initial version 0.0.1
Package: fundiversity
Title: Easy Computation of Alpha Functional Diversity Indices
Version: 0.0.1
Authors@R: c( person("Matthias", "GreniƩ", email = "matthias.grenie@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4659-7522")), person("Hugo", "Gruson", role = "aut", comment = c(ORCID = "0000-0002-4094-1476")) )
Description: Computes 4 alpha-functional diversity indices: Functional Divergence FDiv, Function Evenness Feve, Functional Richness FRic, and Rao's entropy Q (reviewed in VillƩger et al. 2008 <doi:10.1890/07-1206.1>). Provides efficient and modular functions to compute functional diversity indices.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: geometry, Matrix, vegan
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
URL: https://bisaloo.github.io/fundiversity/, https://github.com/bisaloo/fundiversity
BugReports: https://github.com/Bisaloo/fundiversity/issues
Config/testthat/edition: 3
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-11 14:11:47 UTC; Rekyt
Author: Matthias GreniƩ [aut, cre] (<https://orcid.org/0000-0002-4659-7522>), Hugo Gruson [aut] (<https://orcid.org/0000-0002-4094-1476>)
Maintainer: Matthias GreniƩ <matthias.grenie@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-15 09:40:06 UTC

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Package diffcor updated to version 0.6.4 with previous version 0.6.3 dated 2021-01-04

Title: Fisher's z-Tests Concerning Difference of Correlations
Description: Computations of Fisher's z-tests concerning differences between correlations. diffcor.one() could be used to test for differences regarding an expected value, e.g., in construct validation. diffcor.two() may be useful in replication studies, to test if the original study and the replication study differed in terms of effects. diffcor.dep() can be applied to check if the correlation between one construct with another one (r12) is significantly different/higher/smaller than the correlation of one of the constructs with a third construct (r13), given the correlation of the constructs that are compared (r23). The outputs for all the three functions provide the test statistic in z-units, 95 percent confidence intervals, and p-values. For diffcor.one() and diffcor.two(), the output further provides the effect size Cohens q as well as confidence intervals for the empirical correlations. According to Cohen (1988), q = |.10|, |.30| and |.50| are considered small, moderate, and large differences, respectively.
Author: Christian Blƶtner
Maintainer: Christian Blƶtner <c.bloetner@gmail.com>

Diff between diffcor versions 0.6.3 dated 2021-01-04 and 0.6.4 dated 2021-02-15

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New package briKmeans with initial version 0.1
Package: briKmeans
Version: 0.1
Date: 2021-01-30
Title: Package for Brik and Fabrik Algorithms to Initialise Kmeans
Author: Javier Albert Smet <javas@kth.se> and Aurora Torrente <etorrent@est-econ.uc3m.es>.
Maintainer: Aurora Torrente <etorrent@est-econ.uc3m.es>
Depends: R (>= 3.1.0), boot, cluster, depthTools
Description: Implementation of the BRIk and FABRIk algorithms to initialise k-means. These methods are intended for the clustering of multivariate and functional data, respectively. They make use of the Modified Band Depth and bootstrap to identify appropriate initial seeds for k-means, which are proven to be better options than many techniques in the literature. Torrente and Romo (2020) <doi:10.1007/s00357-020-09372-3>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2021-02-11 13:20:13 UTC; mtl
Repository: CRAN
Date/Publication: 2021-02-15 09:40:10 UTC

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Package upsetjs updated to version 1.9.0 with previous version 1.6.0 dated 2020-07-02

Title: 'HTMLWidget' Wrapper of 'UpSet.js' for Exploring Large Set Intersections
Description: 'UpSet.js' is a re-implementation of 'UpSetR' to create interactive set visualizations for more than three sets. This is a 'htmlwidget' wrapper around the 'JavaScript' library 'UpSet.js'.
Author: Samuel Gratzl [aut, cre]
Maintainer: Samuel Gratzl <sam@sgratzl.com>

Diff between upsetjs versions 1.6.0 dated 2020-07-02 and 1.9.0 dated 2021-02-15

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Package cmprskcoxmsm updated to version 0.2.0 with previous version 0.1.0 dated 2021-01-22

Title: Use IPW to Estimate Treatment Effect under Competing Risks
Description: Uses inverse probability weighting methods to estimate treatment effect under marginal structure model for the cause-specific hazard of competing risk events. Estimates also the cumulative incidence function (i.e. risk) of the potential outcomes, and provides inference on risk difference and risk ratio. Reference: Kalbfleisch & Prentice (2002)<doi:10.1002/9781118032985>; Hernan et al (2001)<doi:10.1198/016214501753168154>.
Author: Yiran Zhang, Ronghui Xu
Maintainer: Yiran Zhang <yiz038@health.ucsd.edu>

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Package XLConnect updated to version 1.0.2 with previous version 1.0.1 dated 2020-03-23

Title: Excel Connector for R
Description: Provides comprehensive functionality to read, write and format Excel data.
Author: Mirai Solutions GmbH [aut], Martin Studer [cre], The Apache Software Foundation [ctb, cph] (Apache POI), Graph Builder [ctb, cph] (Curvesapi Java library)
Maintainer: Martin Studer <martin.studer@mirai-solutions.com>

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More information about XLConnect at CRAN
Permanent link

Package randomLCA updated to version 1.1-1 with previous version 1.1-0 dated 2021-01-07

Title: Random Effects Latent Class Analysis
Description: Fits standard and random effects latent class models. The single level random effects model is described in Qu et al <doi:10.2307/2533043> and the two level random effects model in Beath and Heller <doi:10.1177/1471082X0800900302>. Examples are given for their use in diagnostic testing.
Author: Ken Beath [aut, cre]
Maintainer: Ken Beath <ken.beath@mq.edu.au>

Diff between randomLCA versions 1.1-0 dated 2021-01-07 and 1.1-1 dated 2021-02-15

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 build/partial.rdb   |binary
 build/vignette.rds  |binary
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 9 files changed, 28 insertions(+), 14 deletions(-)

More information about randomLCA at CRAN
Permanent link

Package fullfact updated to version 1.4 with previous version 1.3 dated 2019-09-02

Title: Full Factorial Breeding Analysis
Description: We facilitate the analysis of full factorial mating designs with mixed-effects models. The observed data functions extract the variance explained by random and fixed effects and provide their significance. We then calculate the additive genetic, nonadditive genetic, and maternal variance components explaining the phenotype. In particular, we integrate nonnormal error structures for estimating these components for nonnormal data types. The resampled data functions are used to produce bootstrap confidence intervals, which can then be plotted using a simple function. This package will facilitate the analyses of full factorial mating designs in R, especially for the analysis of binary, proportion, and/or count data types and for the ability to incorporate additional random and fixed effects and power analyses. The paper associated with the package including worked examples is: Houde ALS, Pitcher TE (2016) <doi:10.1002/ece3.1943>.
Author: Aimee Lee Houde [aut, cre], Trevor Pitcher [aut]
Maintainer: Aimee Lee Houde <aimee.lee.houde@gmail.com>

Diff between fullfact versions 1.3 dated 2019-09-02 and 1.4 dated 2021-02-15

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More information about fullfact at CRAN
Permanent link

Package sasLM updated to version 0.5.0 with previous version 0.3.0 dated 2021-01-16

Title: 'SAS' Linear Model
Description: This is a core implementation of 'SAS' procedures for linear models - GLM, REG, and ANOVA. Some R packages provide type II and type III SS. However, the results of nested and complex designs are often different from those of 'SAS.' Different results does not necessarily mean incorrectness. However, many wants the same results to SAS. This package aims to achieve that. Reference: Littell RC, Stroup WW, Freund RJ (2002, ISBN:0-471-22174-0).
Author: Kyun-Seop Bae [aut]
Maintainer: Kyun-Seop Bae <k@acr.kr>

Diff between sasLM versions 0.3.0 dated 2021-01-16 and 0.5.0 dated 2021-02-15

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More information about sasLM at CRAN
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Package PoolTestR updated to version 0.1.1 with previous version 0.1.0 dated 2021-02-08

Title: Prevalence and Regression for Pool-Tested (Group-Tested) Data
Description: An easy-to-use tool for working with presence/absence tests on 'pooled' or 'grouped' samples. The primary application is for estimating prevalence of a marker in a population based on the results of tests on pooled specimens. This sampling method is often employed in surveillance of rare conditions in humans or animals (e.g. molecular xenomonitoring). The package was initially conceived as an R-based alternative to the molecular xenomonitoring software, 'PoolScreen' <https://sites.uab.edu/statgenetics/software/>. However, it goes further, allowing for estimates of prevalence to be adjusted for hierarchical sampling frames, and perform flexible mixed-effect regression analyses (McLure et al. pre-print <arXiv:2012.05405>). The package is currently in early stages, however more features are planned or in the works: e.g. adjustments for imperfect test specificity/sensitivity, functions for helping with optimal experimental design, and functions for spatial modelling.
Author: Angus McLure [aut, cre] (<https://orcid.org/0000-0003-2551-3059>)
Maintainer: Angus McLure <angus.mclure@anu.edu.au>

Diff between PoolTestR versions 0.1.0 dated 2021-02-08 and 0.1.1 dated 2021-02-15

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More information about PoolTestR at CRAN
Permanent link


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