Mon, 23 Nov 2020

Package comperes updated to version 0.2.5 with previous version 0.2.4 dated 2020-05-09

Title: Manage Competition Results
Description: Tools for storing and managing competition results. Competition is understood as a set of games in which players gain some abstract scores. There are two ways for storing results: in long (one row per game-player) and wide (one row per game with fixed amount of players) formats. This package provides functions for creation and conversion between them. Also there are functions for computing their summary and Head-to-Head values for players. They leverage grammar of data manipulation from 'dplyr'.
Author: Evgeni Chasnovski [aut, cre] (<https://orcid.org/0000-0002-1617-4019>)
Maintainer: Evgeni Chasnovski <evgeni.chasnovski@gmail.com>

Diff between comperes versions 0.2.4 dated 2020-05-09 and 0.2.5 dated 2020-11-23

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Package sgpv updated to version 1.1.0 with previous version 1.0.0 dated 2020-07-06

Title: Calculate Second-Generation p-Values and Associated Measures
Description: Computation of second-generation p-values as described in Blume et al. (2018) <doi:10.1371/journal.pone.0188299> and Blume et al. (2019) <doi:10.1080/00031305.2018.1537893>. There are additional functions which provide power and type I error calculations, create graphs (particularly suited for large-scale inference usage), and a function to estimate false discovery rates based on second-generation p-value inference.
Author: Valerie Welty [aut, cre], Rebecca Irlmeier [aut], Thomas Stewart [aut], Robert Greevy, Jr. [aut], Lucy D'Agostino McGowan [aut], Jeffrey Blume [aut]
Maintainer: Valerie Welty <valerie.welty@vanderbilt.edu>

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Package rvinecopulib updated to version 0.5.5.1.0 with previous version 0.5.4.1.0 dated 2020-10-03

Title: High Performance Algorithms for Vine Copula Modeling
Description: Provides an interface to 'vinecopulib', a C++ library for vine copula modeling. The 'rvinecopulib' package implements the core features of the popular 'VineCopula' package, in particular inference algorithms for both vine copula and bivariate copula models. Advantages over 'VineCopula' are a sleeker and more modern API, improved performances, especially in high dimensions, nonparametric and multi-parameter families, and the ability to model discrete variables. The 'rvinecopulib' package includes 'vinecopulib' as header-only C++ library (currently version 0.5.5). Thus users do not need to install 'vinecopulib' itself in order to use 'rvinecopulib'. Since their initial releases, 'vinecopulib' is licensed under the MIT License, and 'rvinecopulib' is licensed under the GNU GPL version 3.
Author: Thomas Nagler [aut, cre], Thibault Vatter [aut]
Maintainer: Thomas Nagler <info@vinecopulib.org>

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Package nimble updated to version 0.10.1 with previous version 0.10.0 dated 2020-10-10

Title: MCMC, Particle Filtering, and Programmable Hierarchical Modeling
Description: A system for writing hierarchical statistical models largely compatible with 'BUGS' and 'JAGS', writing nimbleFunctions to operate models and do basic R-style math, and compiling both models and nimbleFunctions via custom-generated C++. 'NIMBLE' includes default methods for MCMC, Monte Carlo Expectation Maximization, and some other tools. The nimbleFunction system makes it easy to do things like implement new MCMC samplers from R, customize the assignment of samplers to different parts of a model from R, and compile the new samplers automatically via C++ alongside the samplers 'NIMBLE' provides. 'NIMBLE' extends the 'BUGS'/'JAGS' language by making it extensible: New distributions and functions can be added, including as calls to external compiled code. Although most people think of MCMC as the main goal of the 'BUGS'/'JAGS' language for writing models, one can use 'NIMBLE' for writing arbitrary other kinds of model-generic algorithms as well. A full User Manual is available at <https://r-nimble.org>.
Author: Perry de Valpine [aut], Christopher Paciorek [aut, cre], Daniel Turek [aut], Nick Michaud [aut], Cliff Anderson-Bergman [aut], Fritz Obermeyer [aut], Claudia Wehrhahn Cortes [aut] (Bayesian nonparametrics system), Abel Rodrìguez [aut] (Bayesian nonparametrics system), Duncan Temple Lang [aut] (packaging configuration), Sally Paganin [aut] (reversible jump MCMC), Jagadish Babu [ctb] (code for the compilation system for an early version of NIMBLE), Lauren Ponisio [ctb] (contributions to the cross-validation code), Peter Sujan [ctb] (multivariate t distribution code)
Maintainer: Christopher Paciorek <paciorek@stat.berkeley.edu>

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Package colorist updated to version 0.1.2 with previous version 0.1.1 dated 2020-08-13

Title: Coloring Wildlife Distributions in Space-Time
Description: Color and visualize wildlife distributions in space-time using raster data. In addition to enabling display of sequential change in distributions through the use of small multiples, 'colorist' provides functions for extracting several features of interest from a sequence of distributions and for visualizing those features using HCL (hue-chroma-luminance) color palettes. Resulting maps allow for "fair" visual comparison of intensity values (e.g., occurrence, abundance, or density) across space and time and can be used to address questions about where, when, and how consistently a species, group, or individual is likely to be found.
Author: Justin Schuetz [aut] (<https://orcid.org/0000-0002-6163-538X>), Matthew Strimas-Mackey [aut, cre] (<https://orcid.org/0000-0001-8929-7776>), Tom Auer [aut] (<https://orcid.org/0000-0001-8619-7147>)
Maintainer: Matthew Strimas-Mackey <mes335@cornell.edu>

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Package WriteXLS updated to version 6.1.0 with previous version 6.0.0 dated 2020-10-17

Title: Cross-Platform Perl Based R Function to Create Excel 2003 (XLS) and Excel 2007 (XLSX) Files
Description: Cross-platform Perl based R function to create Excel 2003 (XLS) and Excel 2007 (XLSX) files from one or more data frames. Each data frame will be written to a separate named worksheet in the Excel spreadsheet. The worksheet name will be the name of the data frame it contains or can be specified by the user.
Author: Marc Schwartz <marc_schwartz@me.com> and various authors for Perl modules listed in each .pm file.
Maintainer: Marc Schwartz <marc_schwartz@me.com>

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Package portalr updated to version 0.3.6 with previous version 0.3.5 dated 2020-08-28

Title: Create Useful Summaries of the Portal Data
Description: Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Project. Portal is a long-term (and ongoing) experimental monitoring site in the Chihuahua desert. The raw data files can be found at <https://github.com/weecology/portaldata>.
Author: Glenda M. Yenni [aut, cre] (<https://orcid.org/0000-0001-6969-1848>), Hao Ye [aut] (<https://orcid.org/0000-0002-8630-1458>), Erica M. Christensen [aut] (<https://orcid.org/0000-0002-5635-2502>), Juniper L. Simonis [aut] (<https://orcid.org/0000-0001-9798-0460>), Ellen K. Bledsoe [aut] (<https://orcid.org/0000-0002-3629-7235>), Renata M. Diaz [aut] (<https://orcid.org/0000-0003-0803-4734>), Shawn D. Taylor [aut] (<https://orcid.org/0000-0002-6178-6903>), Ethan P, White [aut] (<https://orcid.org/0000-0001-6728-7745>), S.K. Morgan Ernest [aut] (<https://orcid.org/0000-0002-6026-8530>), Weecology [cph]
Maintainer: Glenda M. Yenni <glenda@weecology.org>

Diff between portalr versions 0.3.5 dated 2020-08-28 and 0.3.6 dated 2020-11-23

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Package windAC updated to version 1.2.4 with previous version 1.2.3 dated 2020-11-05

Title: Area Correction Methods
Description: Post-construction fatality monitoring studies at wind facilities are based on data from searches for bird and bat carcasses in plots beneath turbines. Bird and bat carcasses can fall outside of the search plot. Bird and bat carcasses from wind turbines often fall outside of the searched area. To compensate, area correction (AC) estimations are calculated to estimate the percentage of fatalities that fall within the searched area versus those that fall outside of it. This package provides two likelihood based methods and one physics based method (Hull and Muir (2010) <doi:10.1080/14486563.2010.9725253>, Huso and Dalthorp (2014) <doi:10.1002/jwmg.663>) to estimate the carcass fall distribution. There are also functions for calculating the proportion of area searched within one unit annuli, log logistic distribution functions, and truncated distribution functions.
Author: Jared Studyvin [aut, cre], Paul Rabie [aut], Daniel Riser-Espinoza [aut], Trent McDonald [ctb]
Maintainer: Jared Studyvin <jstudyvin@west-inc.com>

Diff between windAC versions 1.2.3 dated 2020-11-05 and 1.2.4 dated 2020-11-23

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Package slopeOP updated to version 1.0.1 with previous version 1.0.0 dated 2020-11-20

Title: Change-in-Slope OP Algorithm with a Finite Number of States
Description: Optimal partitioning algorithm for change-in-slope problem with continuity constraint and a finite number of states. Some constraints can be enforced in the inference: isotonic, unimodal or smoothing. With the function slopeSN() (segment neighborhood) the number of segments to infer is fixed by the user and does not depend on a penalty value.
Author: Vincent Runge [aut, cre], Marco Pascucci [aut]
Maintainer: Vincent Runge <vincent.runge@univ-evry.fr>

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Package mistr updated to version 0.0.4 with previous version 0.0.3 dated 2020-02-04

Title: Mixture and Composite Distributions
Description: A flexible computational framework for mixture distributions with the focus on the composite models.
Author: Lukas Sablica [aut, cre] (<https://orcid.org/0000-0001-9166-4563>), Kurt Hornik [aut] (<https://orcid.org/0000-0003-4198-9911>)
Maintainer: Lukas Sablica <lsablica@wu.ac.at>

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Package gmt updated to version 2.0.2 with previous version 2.0-1 dated 2017-09-11

Title: Interface Between GMT Map-Making Software and R
Description: Interface between the GMT map-making software and R, enabling the user to manipulate geographic data within R and call GMT commands to draw and annotate maps in postscript format. The gmt package is about interactive data analysis, rapidly visualizing subsets and summaries of geographic data, while performing statistical analysis in the R console.
Author: Arni Magnusson [aut, cre]
Maintainer: Arni Magnusson <thisisarni@gmail.com>

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Package cmfrec updated to version 2.3.2 with previous version 2.3.0 dated 2020-11-23

Title: Collective Matrix Factorization for Recommender Systems
Description: Collective matrix factorization (a.k.a. multi-view or multi-way factorization, Singh, Gordon, (2008) <doi:10.1145/1401890.1401969>) tries to approximate a matrix 'X' as the product of two low-dimensional matrices aided with secondary information matrices about rows and/or columns of 'X' which are also factorized using the same latent components. The intended usage is for recommender systems, dimensionality reduction, and missing value imputation. Implements extensions of the original model (Cortes, (2018) <arXiv:1809.00366>) and can produce different factorizations such as the weighted 'implicit-feedback' model (Hu, Koren, Volinsky, (2008) <doi:10.1109/ICDM.2008.22>) or the enhanced model with 'implicit features' (Rendle, Zhang, Koren, (2019) <arXiv:1905.01395>), with or without side information. Can use gradient-based procedures or alternating-least squares procedures (Koren, Bell, Volinsky, (2009) <doi:10.1109/MC.2009.263>), with either a Cholesky solver, a faster conjugate gradient solver (Takacs, Pilaszy, Tikk, (2011) <doi:10.1145/2043932.2043987>), or a non-negative coordinate descent solver (Franc, Hlavac, Navara, (2005) <doi:10.1007/11556121_50>), providing efficient methods for sparse and dense data, and mixtures thereof. Offers alternative most-popular and content-based models, and implements functionality for cold-start recommendations and imputation of 2D data.
Author: David Cortes [aut, cre, cph], Jorge Nocedal [cph], Naoaki Okazaki [cph]
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

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Package scape updated to version 2.3.3 with previous version 2.3-2 dated 2018-05-01

Title: Statistical Catch-at-Age Plotting Environment
Description: Import, plot, and diagnose results from statistical catch-at-age models, used in fisheries stock assessment.
Author: Arni Magnusson [aut, cre]
Maintainer: Arni Magnusson <thisisarni@gmail.com>

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Package plotMCMC updated to version 2.0.1 with previous version 2.0-0 dated 2014-03-12

Title: MCMC Diagnostic Plots
Description: Markov chain Monte Carlo diagnostic plots. The purpose of the package is to combine existing tools from the 'coda' and 'lattice' packages, and make it easy to adjust graphical details.
Author: Arni Magnusson [aut, cre], Ian Stewart [aut]
Maintainer: Arni Magnusson <thisisarni@gmail.com>

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Package monaco updated to version 0.2.0 with previous version 0.1.0 dated 2020-10-26

Title: The 'Monaco' Editor as a HTML Widget
Description: A HTML widget rendering the 'Monaco' editor. The 'Monaco' editor is the code editor which powers 'VS Code'. It is particularly well developed for 'JavaScript'. In addition to the built-in features of the 'Monaco' editor, the widget allows to prettify multiple languages, to view the 'HTML' rendering of 'Markdown' code, and to view and resize 'SVG' images.
Author: Stéphane Laurent [aut, cre], Microsoft Corporation [ctb, cph] ('Monaco Editor' library), James Long and contributors [ctb, cph] ('Prettier' library), Rich Harris [ctb, cph] ('svg-parser' library), Lionel Tzatzkin [ctb, cph] ('scale-that-svg' library), Andrei Kashcha [ctb, cph] ('panzoom' library), Vitaly Puzrin [ctb, cph] ('markdown-it' library), Alex Kocharin [ctb, cph] ('markdown-it' library), John Schlinkert [ctb, cph] ('word-wrap' library), jQuery contributors [ctb, cph] ('jQuery' library), Kyle Fox [ctb, cph] ('jQuery Modal' library), Tristan Edwards [ctb, cph] ('sweetalert2' library), Limon Monte [ctb, cph] ('sweetalert2' library)
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>

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Package areaplot updated to version 1.2.2 with previous version 1.2-1 dated 2019-02-16

Title: Plot Stacked Areas and Confidence Bands as Filled Polygons
Description: Plot stacked areas and confidence bands as filled polygons, or add polygons to existing plots. A variety of input formats are supported, including vectors, matrices, data frames, formulas, etc.
Author: Arni Magnusson [aut, cre]
Maintainer: Arni Magnusson <thisisarni@gmail.com>

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Package SMMT updated to version 1.0.5 with previous version 1.0.2 dated 2020-07-16

Title: The Swiss Municipal Data Merger Tool Maps Municipalities Over Time
Description: In Switzerland, the landscape of municipalities is changing rapidly mainly due to mergers. The Swiss Municipal Data Merger Tool automatically detects these mutations and maps municipalities over time, i.e. municipalities of an old state to municipalities of a new state. This functionality is helpful when working with datasets that are based on different spatial references. The spatial reference in this context signifies a set of municipalities at a given point in time.
Author: Valentin Knechtl [aut, cre] (<https://orcid.org/0000-0002-8545-8883>)
Maintainer: Valentin Knechtl <valentin.knechtl@unibas.ch>

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Package ShinyQuickStarter updated to version 1.0.1 with previous version 1.0.0 dated 2020-11-16

Title: 'RStudio' Addin for Quick Setup of ShinyDashboard Apps
Description: This 'RStudio' addin enables faster creation of the project structure and design of 'ShinyDashboard' apps. The graphical interface allows you to add certain code templates interactively. In addition to generating the basic project structure, the navigation in the app itself can also be defined or the app can be structured with modules.
Author: Leon Binder [cre, aut], Bernhard Bauer [ctb], Michael Scholz [ctb], Bernhard Daffner [ctb], Jörg Bauer [ctb]
Maintainer: Leon Binder <leon.binder@th-deg.de>

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Package RstoxData updated to version 1.0.17 with previous version 1.0.16 dated 2020-11-18

Title: Tools to Read and Manipulate Fisheries Data
Description: Set of tools to read and manipulate various data formats for fisheries. Mainly catered towards scientific trawl survey sampling ('biotic') data, acoustic trawl data, and commercial fishing catch ('landings') data. Among the supported data formats are the data products from the Norwegian Institute Marine Research ('IMR') and the International Council for the Exploration of the Sea (ICES).
Author: Ibrahim Umar [cre, aut], Sindre Vatnehol [aut], Arne Johannes Holmin [aut], Edvin Fuglebakk [aut], Espen Johnsen [aut], Norwegian Institute of Marine Research [cph, fnd]
Maintainer: Ibrahim Umar <ibrahim.umar@hi.no>

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Package rgl updated to version 0.103.5 with previous version 0.100.54 dated 2020-04-14

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>

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More information about rgl at CRAN
Permanent link

Package Ravages updated to version 0.1.1 with previous version 0.1 dated 2020-11-11

Title: Rare Variant Analysis and Genetic Simulations
Description: Rare variant association tests: burden tests (Bocher et al. 2019 <doi:10.1002/gepi.22210>) and the Sequence Kernel Association Test; and genetic simulations.
Author: Ozvan Bocher and Hervé Perdry
Maintainer: Ozvan Bocher <bocherozvan@gmail.com>

Diff between Ravages versions 0.1 dated 2020-11-11 and 0.1.1 dated 2020-11-23

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Permanent link

New package phonfieldwork with initial version 0.0.10
Package: phonfieldwork
Type: Package
Title: Linguistic Phonetic Fieldwork Tools
Version: 0.0.10
Depends: R (>= 3.5.0)
Imports: tuneR, phonTools, grDevices, utils, graphics, rmarkdown, xml2, uchardet, tools
Authors@R: c( person( given = "George", family = "Moroz", role = c("aut", "cre"), email = "agricolamz@gmail.com", comment = c(ORCID="0000-0003-1990-6083")), person( given = "Jonathan", family = "Keane", role = c("rev"), email = "jkeane@gmail.com", comment = c(ORCID = "0000-0001-7087-9776")), person( given = "Niko", family = "Partanen", role = c("rev"), email = "nikotapiopartanen@gmail.com", comment = c(ORCID = "0000-0001-8584-3880")) )
Description: There are a lot of different typical tasks that have to be solved during phonetic research and experiments. This includes creating a presentation that will contain all stimuli, renaming and concatenating multiple sound files recorded during a session, automatic annotation in 'Praat' TextGrids (this is one of the sound annotation standards provided by 'Praat' software, see Boersma & Weenink 2020 <https://www.fon.hum.uva.nl/praat/>), creating an html table with annotations and spectrograms, and converting multiple formats ('Praat' TextGrid, 'ELAN', 'EXMARaLDA', 'Audacity', subtitles '.srt', and 'FLEx' flextext). All of these tasks can be solved by a mixture of different tools (any programming language has programs for automatic renaming, and Praat contains scripts for concatenating and renaming files, etc.). 'phonfieldwork' provides a functionality that will make it easier to solve those tasks independently of any additional tools. You can also compare the functionality with other packages: 'rPraat' <https://CRAN.R-project.org/package=rPraat>, 'textgRid' <https://CRAN.R-project.org/package=textgRid>.
License: GPL (>= 2)
SystemRequirements: pandoc (>= 1.14) - http://pandoc.org
URL: https://CRAN.R-project.org/package=phonfieldwork, https://ropensci.github.io/phonfieldwork/
BugReports: https://github.com/ropensci/phonfieldwork/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Suggests: knitr, dplyr, tidyr, DT, lingtypology, testthat
Language: en-US
NeedsCompilation: no
Packaged: 2020-11-12 18:38:56 UTC; agricolamz
Author: George Moroz [aut, cre] (<https://orcid.org/0000-0003-1990-6083>), Jonathan Keane [rev] (<https://orcid.org/0000-0001-7087-9776>), Niko Partanen [rev] (<https://orcid.org/0000-0001-8584-3880>)
Maintainer: George Moroz <agricolamz@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-23 14:10:02 UTC

More information about phonfieldwork at CRAN
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New package LatticeDesign with initial version 2.0-2
Package: LatticeDesign
Version: 2.0-2
Title: Lattice-Based Space-Filling Designs
Authors@R: c(person("Xu He", role = c("aut", "cre"), email = "hexu@amss.ac.cn"))
Description: Lattice-based space-filling designs with fill or separation distance properties including interleaved lattice-based minimax distance designs, interleaved lattice-based maximin distance designs, (sliced) rotated sphere packing designs, and densest packing-based maximum projections designs.
License: LGPL-2.1
Author: Xu He [aut, cre]
Maintainer: Xu He <hexu@amss.ac.cn>
Depends: methods
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2020-11-21 12:30:51 UTC; Mario
Repository: CRAN
Date/Publication: 2020-11-23 14:40:05 UTC

More information about LatticeDesign at CRAN
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New package giscoR with initial version 0.2.2
Package: giscoR
Type: Package
Title: Download Map Data from GISCO API - Eurostat
Version: 0.2.2
Authors@R: c(person(given = "Diego", family = "Hernangómez", role = c("aut", "cre", "cph"), email = "diego.hernangomezherrero@gmail.com", comment = c(ORCID = "0000-0001-8457-4658")), person(given = "EuroGraphics", role = "cph", comment = "for the administrative boundaries."), person(given = "Vincent", family = "Arel-Bundock", role = "cph", comment = c(ORCID = "0000-0003-2042-7063","for the gisco_countrycode dataset.")) )
Description: Tools to download data from the GISCO (Geographic Information System of the Commission) Eurostat database <https://ec.europa.eu/eurostat/web/gisco>. Global and European map data available. This package is in no way officially related to or endorsed by Eurostat.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.1.1
BugReports: https://github.com/dieghernan/giscoR/issues
URL: https://dieghernan.github.io/giscoR/, https://github.com/dieghernan/giscoR
Depends: R (>= 3.6.0)
Imports: sf (>= 0.9), countrycode (>= 1.2.0), geojsonsf (>= 2.0)
Suggests: cartography (>= 2.4), lwgeom, tinytest
LazyData: true
NeedsCompilation: no
Packaged: 2020-11-22 07:38:50 UTC; Diego
Author: Diego Hernangómez [aut, cre, cph] (<https://orcid.org/0000-0001-8457-4658>), EuroGraphics [cph] (for the administrative boundaries.), Vincent Arel-Bundock [cph] (<https://orcid.org/0000-0003-2042-7063>, for the gisco_countrycode dataset.)
Maintainer: Diego Hernangómez <diego.hernangomezherrero@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-23 14:20:02 UTC

More information about giscoR at CRAN
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Package elevatr updated to version 0.3.1 with previous version 0.2.0 dated 2018-11-28

Title: Access Elevation Data from Various APIs
Description: Several web services are available that provide access to elevation data. This package provides access to several of those services and returns elevation data either as a SpatialPointsDataFrame from point elevation services or as a raster object from raster elevation services. Currently, the package supports access to the Amazon Web Services Terrain Tiles <https://registry.opendata.aws/terrain-tiles/>, the Open Topography Global Datasets API <https://opentopography.org/developers/>, and the USGS Elevation Point Query Service <https://nationalmap.gov/epqs/>.
Author: Jeffrey Hollister [aut, cre] (<https://orcid.org/0000-0002-9254-9740>), Tarak Shah [ctb], Alec L. Robitaille [ctb] (<https://orcid.org/0000-0002-4706-1762>), Marcus W. Beck [rev] (<https://orcid.org/0000-0002-4996-0059>), Mike Johnson [ctb] (<https://orcid.org/0000-0002-5288-8350>)
Maintainer: Jeffrey Hollister <hollister.jeff@epa.gov>

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Package blockmodels updated to version 1.1.4 with previous version 1.1.1 dated 2015-04-21

Title: Latent and Stochastic Block Model Estimation by a 'V-EM' Algorithm
Description: Latent and Stochastic Block Model estimation by a Variational EM algorithm. Various probability distribution are provided (Bernoulli, Poisson...), with or without covariates.
Author: Jean-Benoist Leger <jbleger@hds.utc.fr>, Pierre Barbillon <pierre.barbillon@agroparistech.fr>, Julien Chiquet <julien.chiquet@inrae.fr>
Maintainer: Jean-Benoist Leger <jbleger@hds.utc.fr>

Diff between blockmodels versions 1.1.1 dated 2015-04-21 and 1.1.4 dated 2020-11-23

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More information about blockmodels at CRAN
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Package matman updated to version 1.1.1 with previous version 1.1.0 dated 2020-05-14

Title: Material Management
Description: A set of functions, classes and methods for performing ABC and ABC/XYZ analyses, identifying overperforming, underperforming and constantly performing items, and plotting, analyzing as well as predicting the temporal development of items.
Author: Leon Binder [cre, aut], Bernhard Bauer [aut], Michael Scholz [aut]
Maintainer: Leon Binder <leon.binder@th-deg.de>

Diff between matman versions 1.1.0 dated 2020-05-14 and 1.1.1 dated 2020-11-23

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Package FuzzySTs updated to version 0.2 with previous version 0.1 dated 2020-07-03

Title: Fuzzy Statistical Tools
Description: The main goal of this package is to present various fuzzy statistical tools. It intends to provide an implementation of the theoretical and empirical approaches presented in the thesis entitled "The signed distance measure in fuzzy statistical analysis. Some theoretical, empirical and programming advances" (Thesis to be published soon. For the theoretical approaches, see Berkachy R. and Donze L. (2019) <doi:10.1007/978-3-030-03368-2_1>. For the empirical approaches, see Berkachy R. and Donze L. (2016) <ISBN: 978-989-758-201-1>). Important (non-exhaustive) implementation highlights of this package are as follows: (1) a numerical procedure to estimate the fuzzy difference and the fuzzy square. (2) two numerical methods of fuzzification. (3) a function performing different possibilities of distances, including the signed distance and the generalized signed distance for instance. (4) numerical estimations of fuzzy statistical measures such as the variance, the moment, etc. (5) two methods of estimation of the bootstrap distribution of the likelihood ratio in the fuzzy context. (6) an estimation of a fuzzy confidence interval by the likelihood ratio method. (7) testing fuzzy hypotheses and/or fuzzy data by fuzzy confidence intervals in the Kwakernaak - Kruse and Meyer sense. (8) a general method to estimate the fuzzy p-value with fuzzy hypotheses and/or fuzzy data. (9) a method of estimation of global and individual evaluations of linguistic questionnaires. (10) numerical estimations of multi-ways analysis of variance models in the fuzzy context. The unbalance in the considered designs are also foreseen.
Author: Redina Berkachy <redina.berkachy@unifr.ch>, Laurent Donze <laurent.donze@unifr.ch>
Maintainer: Redina Berkachy <redina.berkachy@unifr.ch>

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Package rmdformats updated to version 1.0.0 with previous version 0.3.7 dated 2020-03-11

Title: HTML Output Formats and Templates for 'rmarkdown' Documents
Description: HTML formats and templates for 'rmarkdown' documents, with some extra features such as automatic table of contents, lightboxed figures, dynamic crosstab helper.
Author: Julien Barnier [aut, cre]
Maintainer: Julien Barnier <julien.barnier@cnrs.fr>

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New package UKFE with initial version 0.1.0
Package: UKFE
Type: Package
Title: UK Flood Estimation
Version: 0.1.0
Author: Anthony Hammond
Maintainer: Anthony Hammond <agqhammond@gmail.com>
Description: Functions to implement the methods of the Flood Estimation Handbook (FEH), associated updates and the revitalised flood hydrograph model (ReFH). Currently the packages uses NRFA peak flow dataset version 9. Aside from FEH functionality, further hydrological functions are available. Most of the methods implemented in this package are described in one or more of the following: "Flood Estimation Handbook", Centre for Ecology & Hydrology (1999, ISBN:0 948540 94 X). "Flood Estimation Handbook Supplementary Report No. 1", Kjeldsen (2007, ISBN:0 903741 15 7). "Regional Frequency Analysis - an approach based on L-moments", Hosking & Wallis (1997, ISBN: 978 0 521 01940 8). "Proposal of the ‘extreme rank plot’ for extreme value analysis: with an emphasis on flood frequency studies", Hammond (2019, <doi:10.2166/nh.2019.157>). "Making better use of local data in flood frequency estimation", Environment Agency (2017, ISBN: 978 1 84911 387 8). "Improving the FEH statistical procedures for flood frequency estimation", Environment Agency (2008, ISBN: 978 1 84432 920 5). "Low flow estimation in the United Kingdom", Institute of Hydrology (1992, ISBN 0 948540 45 1). Wallingford HydroSolutions, (2016, <http://software.hydrosolutions.co.uk/winfap4/Urban-Adjustment-Procedure-Technical-Note.pdf>). 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>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2020-11-21 16:16:10 UTC; AnthonyHammond
Repository: CRAN
Date/Publication: 2020-11-23 10:30:02 UTC

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New package tidyseurat with initial version 0.1.17
Type: Package
Package: tidyseurat
Title: Brings Seurat to the Tidyverse
Version: 0.1.17
Authors@R: c(person("Stefano", "Mangiola", email = "mangiolastefano@gmail.com", role = c("aut", "cre")), person("Maria", "Doyle", email = "Maria.Doyle@petermac.org", role = c("ctb")) )
Description: It creates an invisible layer that allow to see the 'Seurat' object as tibble and interact seamlessly with the tidyverse.
License: GPL-3
Depends: R (>= 4.0.0), Seurat
Imports: tibble, dplyr, magrittr, tidyr, ggplot2, rlang, purrr, lifecycle, methods, plotly, tidyselect, utils, ellipsis, pillar, stringr, cli, fansi
Suggests: testthat, knitr, GGally, markdown
VignetteBuilder: knitr
RdMacros: lifecycle
Biarch: true
biocViews: AssayDomain, Infrastructure, RNASeq, DifferentialExpression, GeneExpression, Normalization, Clustering, QualityControl, Sequencing, Transcription, Transcriptomics
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-19 00:08:19 UTC; mangiola.s
Author: Stefano Mangiola [aut, cre], Maria Doyle [ctb]
Maintainer: Stefano Mangiola <mangiolastefano@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-23 10:50:02 UTC

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Package svars updated to version 1.3.5 with previous version 1.3.4 dated 2020-11-12

Title: Data-Driven Identification of SVAR Models
Description: Implements data-driven identification methods for structural vector autoregressive (SVAR) models. Based on an existing VAR model object (provided by e.g. VAR() from the 'vars' package), the structural impact matrix is obtained via data-driven identification techniques (i.e. changes in volatility (Rigobon, R. (2003) <doi:10.1162/003465303772815727>), patterns of GARCH (Normadin, M., Phaneuf, L. (2004) <doi:10.1016/j.jmoneco.2003.11.002>), independent component analysis (Matteson, D. S, Tsay, R. S., (2013) <doi:10.1080/01621459.2016.1150851>), least dependent innovations (Herwartz, H., Ploedt, M., (2016) <doi:10.1016/j.jimonfin.2015.11.001>), smooth transition in variances (Luetkepohl, H., Netsunajev, A. (2017) <doi:10.1016/j.jedc.2017.09.001>) or non-Gaussian maximum likelihood (Lanne, M., Meitz, M., Saikkonen, P. (2017) <doi:10.1016/j.jeconom.2016.06.002>)).
Author: Alexander Lange [aut, cre], Bernhard Dalheimer [aut], Helmut Herwartz [aut], Simone Maxand [aut], Hannes Riebl [ctb]
Maintainer: Alexander Lange <alexander.lange@uni-goettingen.de>

Diff between svars versions 1.3.4 dated 2020-11-12 and 1.3.5 dated 2020-11-23

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Package rNeighborGWAS updated to version 1.2.2 with previous version 1.2.1 dated 2020-07-22

Title: Testing Neighbor Effects in Marker-Based Regressions
Description: To incorporate neighbor genotypic identity into genome-wide association studies, the package provides a set of functions for variation partitioning and association mapping. The theoretical background of the method is described in Sato et al. (2019) <doi:10.1101/845735>.
Author: Yasuhiro Sato [aut, cre] (<https://orcid.org/0000-0002-6466-723X>), Eiji Yamamoto [aut], Kentaro K. Shimizu [aut] (<https://orcid.org/0000-0002-6483-1781>), Atsushi J. Nagano [aut] (<https://orcid.org/0000-0001-7891-5049>)
Maintainer: Yasuhiro Sato <sato.yasuhiro.36c@kyoto-u.jp>

Diff between rNeighborGWAS versions 1.2.1 dated 2020-07-22 and 1.2.2 dated 2020-11-23

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New package Q2q with initial version 0.1.0
Package: Q2q
Type: Package
Title: Interpolating Age-Specific Mortality Rates at All Ages
Version: 0.1.0
Authors@R: person('Farid', 'FLICI', email = 'farid.flici@cread.dz', role = c('aut', 'cre'), comment = c(ORCID = 'https://orcid.org/0000-0002-1954-2120'))
Description: Mortality Rates are usually published following an abridged description, i.e., by age groups 0, [1, 5[, [5, 10[, [10, 15[ and so on. For some applications, a detailed (single) ages description is required. Despite the huge number of the proposed methods in the literature, there is a limited number of methods ensuring a high performance at lower and higher ages in the same time. For example, the 6-terms 'Lagrange' interpolation function is well adapted to mortality interpolation at lower ages (with unequal intervals) but is not adapted to higher ages. On the other hand, the 'Karup-King' method allows a good performance at higher ages but not adapted to lower ages. Interested readers can refer to the book of Shryock, Siegel and Associates (1993) for a detailed overview of the two cited methods.The package Q2q allows combining both the two methods to allow interpolating mortality rates at all ages. First, it starts by implementing each method separately, then the resulted curves are joined based on a 5-age averaged error between the two curves.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R(>= 3.0.0)
NeedsCompilation: no
Packaged: 2020-11-21 07:45:34 UTC; Administrateur
Author: Farid FLICI [aut, cre] (<https://orcid.org/0000-0002-1954-2120>)
Maintainer: Farid FLICI <farid.flici@cread.dz>
Repository: CRAN
Date/Publication: 2020-11-23 10:10:03 UTC

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New package NADIA with initial version 0.4.0
Package: NADIA
Type: Package
Title: NA Data Imputation Algorithms
Version: 0.4.0
Author: Jan Borowski, Piotr Fic
Maintainer: Jan Borowski <janborowka7@gmail.com>
Description: Package crate uniform interface for several advanced imputations missing data methods. Every available method can be used as a part of 'mlr3' pipelines whats allow easy tuning and performance evaluation. Most of the used function work separately on train and test sets ( imputation is trained on the training set and impute train data, after that imputation is again trained on test set and impute test data).
License: GPL
Depends: mlr3, mlr3pipelines, paradox
Imports: mlr3learners, missForest, missMDA, doParallel, testthat, Amelia, VIM, softImpute, missRanger, methods, mice, data.table, foreach, glmnet
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1.9000
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-21 09:25:44 UTC; jan
Repository: CRAN
Date/Publication: 2020-11-23 10:20:02 UTC

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New package mappoly with initial version 0.2.1
Package: mappoly
Type: Package
Title: Genetic Linkage Maps in Autopolyploids
Version: 0.2.1
Authors@R: c(person(given = "Marcelo", family = "Mollinari", role = c("aut", "cre"), email = "mmollin@ncsu.edu", comment = c(ORCID="0000-0002-7001-8498")), person(given = "Gabriel", family = "Gesteira", role = "aut", email = "gabrielgesteira@usp.br", comment = c(ORCID="0000-0002-4106-7346")), person(given = "Guilhereme", family = "Pereira", role = "ctb", comment = c(ORCID="0000-0002-7106-8630")), person(given = "Augusto", family = "Garcia", role = "ctb", comment = c(ORCID="0000-0003-0634-3277")), person(given = "Zhao-Bang", family = "Zeng", role = "ctb", comment = c(ORCID="0000-0002-3115-1149")), person(given = "Katharine", family = "Preedy", role = c("ctb", "cph"), comment = "MDS ordering algorithm"), person(given = "Robert", family = "Gentleman", role = "cph", comment = "C code for MLE optimization in src/pairwise_estimation.cpp"), person(given = "Ross", family = "Ihaka", role = "cph", comment = "C code for MLE optimization in src/pairwise_estimation.cpp"), person(given = "R Foundation", role = "cph", comment = "C code for MLE optimization in src/pairwise_estimation.cpp"), person(given = "R-core", role = "cph", comment = "C code for MLE optimization in src/pairwise_estimation.cpp"))
Maintainer: Marcelo Mollinari <mmollin@ncsu.edu>
Description: Construction of genetic maps in autopolyploid full-sib populations. Uses pairwise recombination fraction estimation as the first source of information to sequentially position allelic variants in specific homologues. For situations where pairwise analysis has limited power, the algorithm relies on the multilocus likelihood obtained through a hidden Markov model (HMM). For more detail, please see Mollinari and Garcia (2019) <doi:10.1534/g3.119.400378> and Mollinari et al. (2020) <doi:10.1534/g3.119.400620>.
License: GPL-3
LazyData: TRUE
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 0.12.6), RCurl, plotly, fields, ggpubr, ggsci, rstudioapi, scatterplot3d, dplyr, crayon, cli, magrittr, reshape2, ggplot2, smacof, princurve, dendextend, vcfR, zoo
LinkingTo: Rcpp
RoxygenNote: 7.1.1
SystemRequirements: C++11
Encoding: UTF-8
Suggests: testthat, RColorBrewer, updog, covr, polymapR, fitPoly
URL: https://github.com/mmollina/MAPpoly
BugReports: https://github.com/mmollina/MAPpoly/issues
NeedsCompilation: yes
Packaged: 2020-11-18 15:57:05 UTC; marcelomollinari
Author: Marcelo Mollinari [aut, cre] (<https://orcid.org/0000-0002-7001-8498>), Gabriel Gesteira [aut] (<https://orcid.org/0000-0002-4106-7346>), Guilhereme Pereira [ctb] (<https://orcid.org/0000-0002-7106-8630>), Augusto Garcia [ctb] (<https://orcid.org/0000-0003-0634-3277>), Zhao-Bang Zeng [ctb] (<https://orcid.org/0000-0002-3115-1149>), Katharine Preedy [ctb, cph] (MDS ordering algorithm), Robert Gentleman [cph] (C code for MLE optimization in src/pairwise_estimation.cpp), Ross Ihaka [cph] (C code for MLE optimization in src/pairwise_estimation.cpp), R Foundation [cph] (C code for MLE optimization in src/pairwise_estimation.cpp), R-core [cph] (C code for MLE optimization in src/pairwise_estimation.cpp)
Repository: CRAN
Date/Publication: 2020-11-23 10:50:11 UTC

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New package joinet with initial version 0.0.6
Package: joinet
Version: 0.0.6
Title: Multivariate Elastic Net Regression
Description: Implements high-dimensional multivariate regression by stacked generalisation (Wolpert 1992 <doi:10.1016/S0893-6080(05)80023-1>). For positively correlated outcomes, a single multivariate regression is typically more predictive than multiple univariate regressions. Includes functions for model fitting, extracting coefficients, outcome prediction, and performance measurement. If required, install MRCE from GitHub (<https://github.com/cran/MRCE>).
Depends: R (>= 3.0.0)
Imports: glmnet, palasso, cornet
Suggests: knitr, rmarkdown, testthat, MASS
Enhances: mice, earth, spls, MRCE, remMap, MultivariateRandomForest, SiER, mcen, GPM, RMTL, MTPS
Authors@R: person("Armin","Rauschenberger",email="armin.rauschenberger@uni.lu",role=c("aut","cre"))
VignetteBuilder: knitr
License: GPL-3
LazyData: true
Language: en-GB
RoxygenNote: 7.1.1
URL: https://github.com/rauschenberger/joinet
BugReports: https://github.com/rauschenberger/joinet/issues
NeedsCompilation: no
Packaged: 2020-11-18 09:19:56 UTC; armin.rauschenberger
Author: Armin Rauschenberger [aut, cre]
Maintainer: Armin Rauschenberger <armin.rauschenberger@uni.lu>
Repository: CRAN
Date/Publication: 2020-11-23 10:50:16 UTC

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New package FSinR with initial version 2.0.5
Package: FSinR
Maintainer: Alfonso Jiménez-Vílchez <i52jivia@uco.es>
Type: Package
Title: Feature Selection
Description: Feature subset selection algorithms modularized in search algorithms and measure utilities. Full list and more information available at <https://dicits.ugr.es/software/FSinR/>.
Version: 2.0.5
Date: 2020-11-16
Authors@R: c( person("Alfonso", "Jiménez-Vílchez", email = "i52jivia@uco.es", role = c("aut", "cre")), person("Francisco", "Aragón-Royón", email = "far@decsai.ugr.es", role = "aut"), person("Adan M.", "Rodriguez", email = "i32muroa@gmail.com", role = "aut"), person("Antonio", "Arauzo-Azofra", email = "arauzo@uco.es", role = "aut"), person("José Manuel", "Benítez", email = "J.M.Benitez@decsai.ugr.es", role = "aut"))
Repository: CRAN
License: GPL-3
LazyData: false
Imports: rpart, neuralnet, class, digest, caret, mlbench, Rdpack, GA, dplyr, tidyr, prodlim, rlang, purrr, e1071
RdMacros: Rdpack
Encoding: UTF-8
RoxygenNote: 7.1.1
Suggests: testthat, knitr, rmarkdown, RSNNS
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-16 14:05:48 UTC; alfonso
Author: Alfonso Jiménez-Vílchez [aut, cre], Francisco Aragón-Royón [aut], Adan M. Rodriguez [aut], Antonio Arauzo-Azofra [aut], José Manuel Benítez [aut]
Date/Publication: 2020-11-23 10:50:26 UTC

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Package basicTrendline updated to version 2.0.5 with previous version 2.0.3 dated 2018-07-26

Title: Add Trendline and Confidence Interval of Basic Regression Models to Plot
Description: Plot, draw regression line and confidence interval, and show regression equation, R-square and P-value, as simple as possible, by using different models ("line2P", "line3P", "log2P", "exp2P", "exp3P", "power2P", "power3P") built in the 'trendline()' function.
Author: Weiping Mei [aut, cre, cph] (<https://orcid.org/0000-0001-6400-9862>), Guangchuang Yu [aut] (<https://orcid.org/0000-0002-6485-8781>), Jiangshan Lai [ctb], Qiang Rao [ctb], Yu Umezawa [ctb]
Maintainer: Weiping Mei <meiweipingg@163.com>

Diff between basicTrendline versions 2.0.3 dated 2018-07-26 and 2.0.5 dated 2020-11-23

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Package airt updated to version 0.2.0 with previous version 0.1.0 dated 2020-05-12

Title: Evaluation of Algorithm Collections Using Item Response Theory
Description: An evaluation framework for algorithm portfolios using Item Response Theory (IRT). We use continuous and polytomous IRT models to evaluate algorithms and introduce algorithm characteristics such as stability, effectiveness and anomalousness (Kandanaarachchi, Smith-Miles 2020) <doi:10.13140/RG.2.2.11363.09760>.
Author: Sevvandi Kandanaarachchi [aut, cre] (<https://orcid.org/0000-0002-0337-0395>)
Maintainer: Sevvandi Kandanaarachchi <sevvandik@gmail.com>

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Package UCSCXenaTools updated to version 1.3.6 with previous version 1.3.5 dated 2020-11-14

Title: Download and Explore Datasets from UCSC Xena Data Hubs
Description: Download and explore datasets from UCSC Xena data hubs, which are a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others. Databases are normalized so they can be combined, linked, filtered, explored and downloaded.
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>), Xue-Song Liu [aut] (<https://orcid.org/0000-0002-7736-0077>), Martin Morgan [ctb], Christine Stawitz [rev] (Christine reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/315>), Carl Ganz [rev] (Carl reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/315>)
Maintainer: Shixiang Wang <w_shixiang@163.com>

Diff between UCSCXenaTools versions 1.3.5 dated 2020-11-14 and 1.3.6 dated 2020-11-23

 DESCRIPTION                      |    6 +++---
 MD5                              |   10 +++++-----
 NEWS.md                          |    5 +++++
 R/XenaDownload.R                 |   12 ++++++++++--
 inst/doc/USCSXenaTools.html      |    8 ++++----
 tests/testthat/test-full-tests.R |    3 ++-
 6 files changed, 29 insertions(+), 15 deletions(-)

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New package TGST with initial version 1.0
Package: TGST
Title: Targeted Gold Standard Testing
Version: 1.0
Authors@R: c( person("Yizhen", "Xu", email = "yizhen_xu@alumni.brown.edu", role = c("aut", "cre")), person("Tao", "Liu", email = "tliu@stat.brown.edu", role = "aut") )
Description: Functions for implementing the targeted gold standard (GS) testing. You provide the true disease or treatment failure status and the risk score, tell 'TGST' the availability of GS tests and which method to use, and it returns the optimal tripartite rules. Please refer to Liu et al. (2013) <doi:10.1080/01621459.2013.810149> for more details.
Depends: R (>= 3.2.0)
License: GPL-3
LazyData: true
Suggests: rmarkdown
VignetteBuilder: knitr
Imports: ggplot2, methods, graphics, knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-11-20 22:12:32 UTC; yizhenxu
Author: Yizhen Xu [aut, cre], Tao Liu [aut]
Maintainer: Yizhen Xu <yizhen_xu@alumni.brown.edu>
Repository: CRAN
Date/Publication: 2020-11-23 09:50:05 UTC

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New package text with initial version 0.9.0
Package: text
Type: Package
Title: Analyses of Text using Natural Language Processing and Machine Learning
Version: 0.9.0
Authors@R: c( person("Oscar", "Kjell", , "oscar.kjell@psy.lu.se", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-2728-6278"), ), person("Salvatore", "Giorgi", role = c("aut"), comment = c(ORCID = "0000-0001-7381-6295") ), person("Andrew", "Schwartz", role = c("aut"), comment = c(ORCID = "0000-0002-6383-3339")) )
Description: Transforms text variables to word embeddings; where the word embeddings are used to statistically test the mean difference between set of texts, compute semantic similarity scores between texts, predict numerical variables, and visual statistically significant words according to various dimensions etc. For more information see <https://www.r-text.org>.
License: GPL-3
URL: https://r-text.org/, https://github.com/OscarKjell/text/
BugReports: https://github.com/OscarKjell/text/issues/
Encoding: UTF-8
Archs: x64
SystemRequirements: Python (>= 3.6.0)
LazyData: true
BuildVignettes: true
Imports: dplyr, tokenizers, tibble, stringr, tidyr, ggplot2, ggrepel, cowplot, rlang, purrr, magrittr, parsnip, recipes, rsample, reticulate, tune, workflows, yardstick, future, furrr
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, testthat, rio, glmnet, randomForest, covr, xml2, ranger
VignetteBuilder: knitr
Depends: R (>= 4.00)
Config/reticulate: list( packages = list( list(package = "torch", pip = TRUE), list(package = "transformers", version = "3.3.1", pip = TRUE), list(package = "nltk", pip = TRUE), list(package = "numpy", pip = TRUE) ) )
NeedsCompilation: no
Packaged: 2020-11-20 16:22:21 UTC; oscarkjell
Author: Oscar Kjell [aut, cre] (<https://orcid.org/0000-0002-2728-6278>), Salvatore Giorgi [aut] (<https://orcid.org/0000-0001-7381-6295>), Andrew Schwartz [aut] (<https://orcid.org/0000-0002-6383-3339>)
Maintainer: Oscar Kjell <oscar.kjell@psy.lu.se>
Repository: CRAN
Date/Publication: 2020-11-23 09:30:02 UTC

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New package scTenifoldKnk with initial version 1.0.0
Package: scTenifoldKnk
Type: Package
Title: In-Silico Knockout Experiments from Single-Cell Gene Regulatory Networks
Version: 1.0.0
Authors@R: c(person(given = "Daniel", family = "Osorio", email = "dcosorioh@tamu.edu", role = c("aut","cre"), comment = c(ORCID = '0000-0003-4424-8422')), person(given = "Yan", family = "Zhong", role = c("aut","ctb")), person(given = "Guanxun", family = "Li", role = c("aut","ctb")), person(given = "Qian", family = "Xu", role = c("aut","ctb")), person(given = "Andrew", family = "Hillhouse", role = c("aut","ctb")), person(given = "Jingshu", family = "Chen", role = c("aut","ctb")), person(given = "Laurie", family = "Davidson", role = c("aut","ctb")), person(given = "Yanan", family = "Tian", role = c("aut","ctb")), person(given = "Robert", family = "Chapkin", role = c("aut","ctb")), person(given = "Jianhua", family = "Huang", role = c("aut","ctb")), person(given = "James", family = "Cai", role = c("aut", "ctb", "ths"), comment = c(ORCID = '0000-0002-8081-6725')) )
Description: A workflow based on 'scTenifoldNet' to perform in-silico knockout experiments using single-cell RNA sequencing (scRNA-seq) data from wild-type (WT) control samples as input. First, the package constructs a single-cell gene regulatory network (scGRN) and knocks out a target gene from the adjacency matrix of the WT scGRN by setting the gene’s outdegree edges to zero. Then, it compares the knocked out scGRN with the WT scGRN to identify differentially regulated genes, called virtual-knockout perturbed genes, which are used to assess the impact of the gene knockout and reveal the gene’s function in the analyzed cells.
URL: https://github.com/cailab-tamu/scTenifoldKnk
BugReports: https://github.com/cailab-tamu/scTenifoldKnk/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
biocViews:
Imports: pbapply, RSpectra, Matrix, methods, stats, utils, MASS, scTenifoldNet
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2020-11-20 17:11:22 UTC; dcosorioh
Author: Daniel Osorio [aut, cre] (<https://orcid.org/0000-0003-4424-8422>), Yan Zhong [aut, ctb], Guanxun Li [aut, ctb], Qian Xu [aut, ctb], Andrew Hillhouse [aut, ctb], Jingshu Chen [aut, ctb], Laurie Davidson [aut, ctb], Yanan Tian [aut, ctb], Robert Chapkin [aut, ctb], Jianhua Huang [aut, ctb], James Cai [aut, ctb, ths] (<https://orcid.org/0000-0002-8081-6725>)
Maintainer: Daniel Osorio <dcosorioh@tamu.edu>
Repository: CRAN
Date/Publication: 2020-11-23 09:40:02 UTC

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New package personalr with initial version 1.0.1
Package: personalr
Title: Automated Personal Package Setup
Version: 1.0.1
Authors@R: person(given = "Sebastian", family = "Carl", role = c("aut", "cre"), email = "mrcaseb@gmail.com")
Description: Functions to setup a personal R package that attaches given libraries and exports personal helper functions.
License: MIT + file LICENSE
URL: https://github.com/mrcaseb/personalr
BugReports: https://github.com/mrcaseb/personalr/issues
Imports: desc, devtools, fs, glue, magrittr, purrr, rprojroot, rstudioapi, usethis, utils, withr, xfun
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-20 11:42:49 UTC; ne48wop
Author: Sebastian Carl [aut, cre]
Maintainer: Sebastian Carl <mrcaseb@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-23 09:10:03 UTC

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Package overviewR updated to version 0.0.7 with previous version 0.0.6 dated 2020-08-24

Title: Easily Extracting Information About Your Data
Description: Makes it easy to display descriptive information on a data set. Getting an easy overview of a data set by displaying and visualizing sample information in different tables (e.g., time and scope conditions). The package also provides publishable 'LaTeX' code to present the sample information.
Author: Cosima Meyer [cre, aut], Dennis Hammerschmidt [aut]
Maintainer: Cosima Meyer <cosima.meyer@gmail.com>

Diff between overviewR versions 0.0.6 dated 2020-08-24 and 0.0.7 dated 2020-11-23

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 MD5                                |   34 ++--
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 tests/testthat/test-check_output.R |   17 ++
 vignettes/overviewR_vignette.Rmd   |  171 +++++++++++-------------
 19 files changed, 615 insertions(+), 442 deletions(-)

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Package openair updated to version 2.8-0 with previous version 2.7-6 dated 2020-10-01

Title: Tools for the Analysis of Air Pollution Data
Description: Tools to analyse, interpret and understand air pollution data. Data are typically hourly time series and both monitoring data and dispersion model output can be analysed. Many functions can also be applied to other data, including meteorological and traffic data.
Author: David Carslaw [aut, cre], Karl Ropkins [aut]
Maintainer: David Carslaw <david.carslaw@york.ac.uk>

Diff between openair versions 2.7-6 dated 2020-10-01 and 2.8-0 dated 2020-11-23

 DESCRIPTION         |    8 
 MD5                 |   20 -
 NAMESPACE           |    1 
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 R/windRose.R        |   90 ++---
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 12 files changed, 889 insertions(+), 852 deletions(-)

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New package NFLSimulatoR with initial version 0.1.0
Package: NFLSimulatoR
Type: Package
Title: Simulating Plays and Drives in the NFL
Version: 0.1.0
Authors@R: c( person("Ryan", "Elmore", email = "Ryan.Elmore@du.edu", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-0092-4532")), person("Ben", "Williams", email = "Benjamin.Williams@du.edu", role = "aut", comment = c(ORCID = "0000-0001-8474-5066")), person("Will", "Palmquist", email = "Will.Palmquist@du.edu", role = "aut", comment = c(ORCID = "0000-0002-6100-0923")))
Maintainer: Ryan Elmore <Ryan.Elmore@du.edu>
Description: The intent here is to enable the simulation of plays/drives and evaluate game-play strategies in the National Football League (NFL). Built-in strategies include going for it on fourth down and varying the proportion of passing/rushing plays during a drive. The user should be familiar with nflscrapR data before trying to write his/her own strategies. This work is inspired by a blog post by Mike Lopez, currently the Director of Data and Analytics at the NFL, Lopez (2019) <https://statsbylopez.netlify.app/post/resampling-nfl-drives/>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: data.table, progress
LazyData: true
Depends: R (>= 3.5.0)
RoxygenNote: 7.1.1
URL: https://github.com/rtelmore/NFLSimulatoR/
BugReports: https://github.com/rtelmore/NFLSimulatoR/issues/
NeedsCompilation: no
Packaged: 2020-11-20 15:52:10 UTC; Ryan
Author: Ryan Elmore [cre, aut] (<https://orcid.org/0000-0002-0092-4532>), Ben Williams [aut] (<https://orcid.org/0000-0001-8474-5066>), Will Palmquist [aut] (<https://orcid.org/0000-0002-6100-0923>)
Repository: CRAN
Date/Publication: 2020-11-23 09:20:06 UTC

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New package mikropml with initial version 0.0.1
Package: mikropml
Title: User-Friendly R Package for Supervised Machine Learning Pipelines
Version: 0.0.1
Authors@R: c( person(given = "Begüm", family = "Topçuoğlu", role = c("aut"), email = "topcuoglu.begum@gmail.com", comment = c(ORCID = "0000-0003-3140-537X") ), person(given = "Zena", family = "Lapp", role = c("aut"), email = "zenalapp@umich.edu", comment = c(ORCID = "0000-0003-4674-2176") ), person(given = "Kelly", family = "Sovacool", role = c("aut", "cre"), email = "sovacool@umich.edu", comment = c(ORCID = "0000-0003-3283-829X") ), person(given = "Evan", family = "Snitkin", role = c('aut'), comment = c(ORCID = "0000-0001-8409-278X")), person(given = "Jenna", family = "Wiens", role = c('aut'), comment = c(ORCID = "0000-0002-1057-7722")), person(given = "Patrick", family = "Schloss", role = c('aut'), email = 'pschloss@umich.edu', comment = c(ORCID = "0000-0002-6935-4275")), person(given = "Nick", family = "Lesniak", role = c("ctb"), email = "nlesniak@umich.edu", comment = c(ORCID = "0000-0001-9359-5194")))
Date: 2020-11-20
URL: http://www.schlosslab.org/mikropml/, https://github.com/SchlossLab/mikropml
BugReports: https://github.com/SchlossLab/mikropml/issues
Description: An interface to build machine learning models for classification and regression problems. 'mikropml' implements the ML pipeline described by Topçuoğlu et al. (2020) <doi:10.1128/mBio.00434-20> with reasonable default options for data preprocessing, hyperparameter tuning, cross-validation, testing, model evaluation, and interpretation steps. See the website <http://www.schlosslab.org/mikropml/> for more information, documentation, and examples.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: caret, dplyr, e1071, glmnet, kernlab, MLmetrics, randomForest, rlang, stats, utils, xgboost
Suggests: doFuture, foreach, future, future.apply, ggplot2, knitr, purrr, rmarkdown, rpart, testthat, tidyr
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-11-20 17:07:23 UTC; kelly
Author: Begüm Topçuoğlu [aut] (<https://orcid.org/0000-0003-3140-537X>), Zena Lapp [aut] (<https://orcid.org/0000-0003-4674-2176>), Kelly Sovacool [aut, cre] (<https://orcid.org/0000-0003-3283-829X>), Evan Snitkin [aut] (<https://orcid.org/0000-0001-8409-278X>), Jenna Wiens [aut] (<https://orcid.org/0000-0002-1057-7722>), Patrick Schloss [aut] (<https://orcid.org/0000-0002-6935-4275>), Nick Lesniak [ctb] (<https://orcid.org/0000-0001-9359-5194>)
Maintainer: Kelly Sovacool <sovacool@umich.edu>
Repository: CRAN
Date/Publication: 2020-11-23 09:40:11 UTC

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New package IAcsSPCR with initial version 1.2.1
Package: IAcsSPCR
Type: Package
Title: Data and Functions for "An Intro. to Accept. Samp. & SPC/R"
Version: 1.2.1
Author: John Lawson
Maintainer: John Lawson <lawsonjsl7net@gmail.com>
Description: Contains data frames and functions used in the book "An Introduction to Acceptance Sampling and SPC with R". This book is available electronically at <https://bookdown.org/>. A physical copy will be published by CRC Press.
License: GPL-2
Imports: lattice, FrF2, graphics, grDevices, stats, stringi, abind
Encoding: UTF-8
LazyData: yes
Repository: CRAN
Repository/R-Forge/Project: daewr
Repository/R-Forge/Revision: 213
Repository/R-Forge/DateTimeStamp: 2020-11-18 16:17:41
Date/Publication: 2020-11-23 09:30:13 UTC
NeedsCompilation: no
Packaged: 2020-11-18 16:27:21 UTC; rforge
Depends: R (>= 3.5.0)

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New package graphhopper with initial version 0.1.1
Package: graphhopper
Title: An R Interface to the 'GraphHopper' Directions API
Version: 0.1.1
Date: 2020-11-20
Maintainer: Stefan Kuethe <crazycapivara@gmail.com>
Authors@R: person("Stefan", "Kuethe", role = c("aut", "cre"), email = "crazycapivara@gmail.com")
Description: Provides a quick and easy access to the 'GraphHopper' Directions API. 'GraphHopper' <https://www.graphhopper.com/> itself is a routing engine based on 'OpenStreetMap' data. API responses can be converted to simple feature (sf) objects in a convenient way.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: magrittr, httr, googlePolylines, jsonlite, tibble, dplyr
Suggests: sf, ggplot2, testthat
RoxygenNote: 6.1.1
URL: https://github.com/crazycapivara/graphhopper-r
BugReports: https://github.com/crazycapivara/graphhopper-r/issues
NeedsCompilation: no
Packaged: 2020-11-20 16:15:46 UTC; gabbo
Author: Stefan Kuethe [aut, cre]
Repository: CRAN
Date/Publication: 2020-11-23 09:30:06 UTC

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New package CVEK with initial version 0.1-0
Package: CVEK
Title: Cross-Validated Kernel Ensemble
Version: 0.1-0
Date: 2020-11-16
Authors@R: c(person("Wenying", "Deng", role = c("aut", "cre"), email = "wdeng@g.harvard.edu"), person("Jeremiah Zhe", "Liu", role = c("ctb")))
Description: Implementation of Cross-Validated Kernel Ensemble (CVEK), a flexible modeling framework for robust nonlinear regression and hypothesis testing based on ensemble learning with kernel-ridge estimators (Jeremiah et al. (2017) <arXiv:1710.01406> and Wenying et al. (2018) <arXiv:1811.11025>). It allows user to conduct nonlinear regression with minimal assumption on the function form by aggregating nonlinear models generated from a diverse collection of kernel families. It also provides utilities to test for the estimated nonlinear effect under this ensemble estimator, using either the asymptotic or the bootstrap version of a generalized score test.
Depends: R (>= 3.6.0), MASS, limSolve
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, knitr, rmarkdown, ggplot2, ggrepel
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-20 23:48:57 UTC; irisdeng
Author: Wenying Deng [aut, cre], Jeremiah Zhe Liu [ctb]
Maintainer: Wenying Deng <wdeng@g.harvard.edu>
Repository: CRAN
Date/Publication: 2020-11-23 10:00:03 UTC

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New package cpss with initial version 0.0.2
Package: cpss
Title: Change-Point Detection by Sample-Splitting Methods
Version: 0.0.2
Authors@R: c( person(given = "Guanghui", family = "Wang", role = c("aut", "cre"), email = "ghwang.nk@gmail.com"), person(given = "Changliang", family = "Zou", role = "aut", email = "nk.chlzou@gmail.com") )
Description: Implements multiple change searching algorithms for a variety of frequently considered parametric change-point models. In particular, it integrates a criterion proposed by Zou, Wang and Li (2020) <doi:10.1214/19-AOS1814> to select the number of change-points in a data-driven fashion. Moreover, it also provides interfaces for users-customized change-point models with their own cost function and estimation routines.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, magrittr, methods, stats, mvtnorm, Rfast, tibble, dplyr, tidyr, rlang, ggplot2, gridExtra
Suggests: MASS, L1pack
NeedsCompilation: yes
Packaged: 2020-11-20 13:03:08 UTC; stat
Author: Guanghui Wang [aut, cre], Changliang Zou [aut]
Maintainer: Guanghui Wang <ghwang.nk@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-23 09:40:15 UTC

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New package cmfrec with initial version 2.3.0
Package: cmfrec
Type: Package
Title: Collective Matrix Factorization for Recommender Systems
Version: 2.3.0
Date: 2020-11-21
Author: David Cortes [aut, cre, cph], Jorge Nocedal [cph], Naoaki Okazaki [cph]
Maintainer: David Cortes <david.cortes.rivera@gmail.com>
URL: https://github.com/david-cortes/cmfrec
BugReports: https://github.com/david-cortes/cmfrec/issues
Description: Collective matrix factorization (a.k.a. multi-view or multi-way factorization, Singh, Gordon, (2008) <doi:10.1145/1401890.1401969>) tries to approximate a matrix 'X' as the product of two low-dimensional matrices aided with secondary information matrices about rows and/or columns of 'X' which are also factorized using the same latent components. The intended usage is for recommender systems, dimensionality reduction, and missing value imputation. Implements extensions of the original model (Cortes, (2018) <arXiv:1809.00366>) and can produce different factorizations such as the weighted 'implicit-feedback' model (Hu, Koren, Volinsky, (2008) <doi:10.1109/ICDM.2008.22>) or the enhanced model with 'implicit features' (Rendle, Zhang, Koren, (2019) <arXiv:1905.01395>), with or without side information. Can use gradient-based procedures or alternating-least squares procedures (Koren, Bell, Volinsky, (2009) <doi:10.1109/MC.2009.263>), with either a Cholesky solver, a faster conjugate gradient solver (Takacs, Pilaszy, Tikk, (2011) <doi:10.1145/2043932.2043987>), or a non-negative coordinate descent solver (Franc, Hlavac, Navara, (2005) <doi:10.1007/11556121_50>), providing efficient methods for sparse and dense data, and mixtures thereof. Offers alternative most-popular and content-based models, and implements functionality for cold-start recommendations and imputation of 2D data.
License: MIT + file LICENSE
Suggests: Matrix, rsparse, recommenderlab, MASS
Enhances: SparseM
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-11-20 21:34:44 UTC; david
Repository: CRAN
Date/Publication: 2020-11-23 09:50:02 UTC

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New package BCT with initial version 1.0
Package: BCT
Type: Package
Title: Bayesian Context Trees for Discrete Time Series
Version: 1.0
Date: 2020-11-10
Author: Ioannis Papageorgiou, Valentinian Mihai Lungu, Ioannis Kontoyiannis
Maintainer: Valentinian Mihai Lungu <valentinian.mihai@gmail.com>
Description: An implementation of a collection of tools for exact Bayesian inference with discrete times series. This package contains functions that can be used for prediction, model selection, estimation, and other statistical tasks. Specifically, the functions provided can be used for the exact computation of the prior predictive likelihood of the data, for the identification of the a posteriori most likely (MAP) variable-memory Markov models, for calculating the exact posterior probabilities and the AIC and BIC scores of these models, and for prediction with respect to log-loss and 0-1 loss. All the functions here (except generate_data) are implementations of deterministic algorithms that have linear complexity in the length of the input data. Example data sets from finance, genetics and animal communication are also provided. Detailed descriptions of the underlying theory and algorithms can be found in [Kontoyiannis et al. 'Bayesian Context Trees: Modelling and exact inference for discrete time series.' <arXiv:2007.14900> [stat.ME], July 2020]. R version 4.0.2 or more recent required. Windows users may need to download and install Rtools separately; see <https://cran.r-project.org/bin/windows/Rtools/>. Mac users may need to ensure R uses C++11 to install the BCT package. Also it may help resolve installation errors to download and install the Xcode developer tools from the App Store.
License: GPL (>= 2)
LazyData: true
Encoding: UTF-8
Imports: Rcpp (>= 1.0.5), stringr, igraph, readr, grDevices, graphics
LinkingTo: Rcpp
Depends: R (>= 2.10)
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-11-20 14:14:46 UTC; valentinianmihailungu
Repository: CRAN
Date/Publication: 2020-11-23 09:20:09 UTC

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New package bcr with initial version 0.1.0
Package: bcr
Title: Extract Moroccan Financial Data
Version: 0.1.0
Authors@R: person(given = "Abdessabour", family = "Moutik", role = c("aut", "cre"), email = "a.moutik@insea.ac.ma")
Description: Get Moroccan Stock Prices (historical data and intraday changes), Market and Sector Indices and bonds. See <https://www.leboursier.ma/>.
URL: https://github.com/moutikabdessabour/bcr
BugReports: https://github.com/moutikabdessabour/bcr/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: httr, jsonlite
Depends: R (>= 3.1.0)
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-20 11:50:46 UTC; sabor
Author: Abdessabour Moutik [aut, cre]
Maintainer: Abdessabour Moutik <a.moutik@insea.ac.ma>
Repository: CRAN
Date/Publication: 2020-11-23 09:10:05 UTC

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New package WinRatio with initial version 1.0
Package: WinRatio
Type: Package
Title: Win Ratio for Prioritized Outcomes and 95% Confidence Interval
Version: 1.0
Date: 2020-11-16
Author: Kevin Duarte, Joao Pedro Ferreira
Maintainer: Kevin Duarte <k.duarte@chru-nancy.fr>
Description: Calculate the win ratio for prioritized outcomes and the 95% confidence interval based on Bebu and Lachin (2016) <doi:10.1093/biostatistics/kxv032>. Three type of outcomes can be analyzed: survival "failure-time" events, repeated survival "failure-time" events and continuous or ordinal "non-failure time" events that are captured at specific time-points in the study.
License: GPL (>= 2)
Depends: R (>= 4.0.0), tidyverse (>= 1.3.0)
Imports: Rcpp (>= 1.0.5), dplyr, magrittr, tidyselect
Suggests: survival
LinkingTo: Rcpp
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-11-19 20:52:26 UTC; U002453
Repository: CRAN
Date/Publication: 2020-11-23 08:10:02 UTC

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New package stacks with initial version 0.1.0
Package: stacks
Title: Tidy Model Stacking
Version: 0.1.0
Authors@R: c( person(given = "Simon", family = "Couch", role = c("aut", "cre"), email = "simonpatrickcouch@gmail.com"), person(given = "Max", family = "Kuhn", email = "max@rstudio.com", role = "aut"), person("RStudio", role = "cph") )
Description: Model stacking is an ensemble technique that involves training a model to combine the outputs of many diverse statistical models, and has been shown to improve predictive performance in a variety of settings. 'stacks' implements a grammar for 'tidymodels'-aligned model stacking.
License: MIT + file LICENSE
Depends: R (>= 2.10)
Imports: tune (>= 0.1.2), dplyr (>= 1.0.0), rlang (>= 0.4.0), tibble (>= 2.1.3), purrr (>= 0.3.2), parsnip (>= 0.0.4), workflows (>= 0.1.0), recipes (>= 0.1.15), yardstick, tidyr, dials, digest, glue, ggplot2, glmnet, rsample, cli, butcher, stats, foreach, generics
Suggests: testthat, covr, kernlab, knitr, modeldata, rmarkdown, palmerpenguins, ranger, nnet, kknn
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-20 00:13:21 UTC; simonpcouch
Author: Simon Couch [aut, cre], Max Kuhn [aut], RStudio [cph]
Maintainer: Simon Couch <simonpatrickcouch@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-23 08:40:02 UTC

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New package ppmSuite with initial version 0.1.0
Package: ppmSuite
Type: Package
Title: A Collection of Models that Employ a Prior Distribution on Partitions
Version: 0.1.0
Authors@R: c( person(given = "Garritt L.", family = "Page", email = "page@stat.byu.edu", role = c("aut", "cre", "cph")), person(given = "S. McKay", family = "Curtis", email = "s.mckay.curtis@gmail.com", role = c("ctb", "cph")), person(given = "Radford M.", family = "Neal", role = c("ctb", "cph")))
Maintainer: Garritt L. Page <page@stat.byu.edu>
Description: Provides functions that fit hierarchical Gaussian and probit ordinal models. A (covariate dependent) product partition model is used as a prior. If a covariate dependent product partition model is selected, then all the options detailed in Page, G.L.; Quintana, F.A.; (2018) <doi:10.1007/s11222-017-9777-z> are available. In addition, a function that fits a Gaussian likelihood spatial product partition model that is detailed in Page, G.L.; Quintana, F.A.; (2016) <doi:10.1214/15-BA971> is also provided.
Depends: R (>= 3.5.0)
License: GPL
Encoding: UTF-8
LazyData: true
Suggests: cluster
NeedsCompilation: yes
Packaged: 2020-11-20 03:02:31 UTC; gpage
Author: Garritt L. Page [aut, cre, cph], S. McKay Curtis [ctb, cph], Radford M. Neal [ctb, cph]
Repository: CRAN
Date/Publication: 2020-11-23 08:50:02 UTC

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New package pda with initial version 1.0
Package: pda
Type: Package
Title: Privacy-Preserving Distributed Algorithms
Version: 1.0
Date: 2020-11-19
Authors@R: c(person("Chongliang", "Luo", role=c("aut","cre"), email ="luocl3009@gmail.com"), person("Rui", "Duan", role="aut"), person("Mackenzie", "Edmondson", role="aut"), person("Jiayi", "Tong", role="aut"), person("Yong", "Chen", role="aut", email ="ychen123@upenn.edu"), person("Penn Computing Inference Learning (PennCIL) lab", role = c("cph")))
Description: A collection of privacy-preserving distributed algorithms for conducting multi-site data analyses. The regression analyses can be linear regression for continuous outcome, logistic regression for binary outcome, Cox proportional hazard regression for time-to event outcome, or Poisson regression for count outcome. The PDA algorithm runs on a lead site and only requires summary statistics from collaborating sites, with one or few iterations. For more information, please visit our software websites: <https://github.com/Penncil/pda>, and <https://penncil2019pda.wixsite.com/mysite>.
Maintainer: Chongliang Luo <luocl3009@gmail.com>
License: Apache License 2.0
Suggests: imager
Imports: Rcpp (>= 0.12.19), stats, httr, rvest, jsonlite, data.table, survival
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-11-20 05:28:32 UTC; chl18019
Author: Chongliang Luo [aut, cre], Rui Duan [aut], Mackenzie Edmondson [aut], Jiayi Tong [aut], Yong Chen [aut], Penn Computing Inference Learning (PennCIL) lab [cph]
Repository: CRAN
Date/Publication: 2020-11-23 09:00:03 UTC

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Package modeltime updated to version 0.4.0 with previous version 0.3.1 dated 2020-11-09

Title: The Tidymodels Extension for Time Series Modeling
Description: The time series forecasting framework for use with the 'tidymodels' ecosystem. Models include ARIMA, Exponential Smoothing, and additional time series models from the 'forecast' and 'prophet' packages. Refer to "Forecasting Principles & Practice, Second edition" (<https://otexts.com/fpp2/>). Refer to "Prophet: forecasting at scale" (<https://research.fb.com/blog/2017/02/prophet-forecasting-at-scale/>.).
Author: Matt Dancho [aut, cre], Business Science [cph]
Maintainer: Matt Dancho <mdancho@business-science.io>

Diff between modeltime versions 0.3.1 dated 2020-11-09 and 0.4.0 dated 2020-11-23

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New package M2SMJF with initial version 1.0
Package: M2SMJF
Title: Multi-Modal Similarity Matrix Joint Factorization
Version: 1.0
Authors@R: person("Xiaoyao", "Yin", email = "yinxy1992@sina.com", role = c("aut", "cre"))
Description: A new method to implement clustering from multiple modality data of certain samples, the function M2SMjF() jointly factorizes multiple similarity matrices into a shared sub-matrix and several modality private sub-matrices, which is further used for clustering. Along with this method, we also provide function to calculate the similarity matrix and function to evaluate the best cluster number from the original data.
Imports: dplyr, MASS, stats
Depends: R (>= 3.4.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-20 00:49:57 UTC; DELL
Author: Xiaoyao Yin [aut, cre]
Maintainer: Xiaoyao Yin <yinxy1992@sina.com>
Repository: CRAN
Date/Publication: 2020-11-23 08:40:06 UTC

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New package fctbases with initial version 1.0.0
Package: fctbases
Type: Package
Title: Functional Bases
Version: 1.0.0
Date: 2020-11-20
Author: Niels Olsen
Maintainer: Niels Olsen <nalo@dtu.dk>
Description: Easy-to-use, very fast implementation of various functional bases. Easily used together with other packages. A functional basis is a collection of basis functions [\phi_1, ..., \phi_n] that can represent a smooth function, i.e. $f(t) = \sum c_k \phi_k(t)$. As of version 1.0, this package includes B-splines, Fourier bases and polynomials.
URL: https://github.com/naolsen/fctbases
License: GPL-3
Imports: Rcpp (>= 0.12.19)
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2020-11-19 21:12:08 UTC; nalo
Repository: CRAN
Date/Publication: 2020-11-23 08:50:11 UTC

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Package wikifacts (with last version 0.4) was removed from CRAN

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

2020-08-10 0.4
2020-06-14 0.3.0
2020-05-13 0.2
2019-08-01 0.1.0

Permanent link
New package WRI with initial version 0.1.0
Package: WRI
Type: Package
Title: Wasserstein Regression Inference
Version: 0.1.0
Authors@R: c( person("Xi", "Liu", email = "xiliu@ucsb.edu", role = c("aut", "cre")), person("Matthew", "Coleman", email = "matthewbcoleman@ucsb.edu", role = "aut"), person("Alexander", "Petersen", email = "petersen@pstat.ucsb.edu", role = "aut"))
Author: Xi Liu [aut, cre], Matthew Coleman [aut], Alexander Petersen [aut]
Description: An implementation of the methodologies described in Alexander Petersen, Xi Liu and Afshin A. Divani (2019) <arXiv:1910.13418>, including global F tests, partial F tests, intrinsic Wasserstein-infinity bands and Wasserstein density bands.
License: GPL-2
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.6.0)
Imports: fdapace (>= 0.2.0), fdadensity (>= 0.1.2), Rfast (>= 1.9.8), CVXR (>= 0.99.7), expm (>= 0.999-4), ggplot2 (>= 3.2.1), gridExtra (>= 2.3), stats, Rcpp (>= 1.0.3), locfit (>= 1.5-9.1), mvtnorm (>= 1.1-0), locpol (>= 0.7), modeest (>= 2.4.0), methods, rlang
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-11-19 16:12:25 UTC; lucyliu
Maintainer: Xi Liu <xiliu@ucsb.edu>
Repository: CRAN
Date/Publication: 2020-11-23 08:00:06 UTC

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New package healthyR.data with initial version 1.0.0
Package: healthyR.data
Title: Data Only Package to 'healthyR'
Version: 1.0.0
Authors@R: c( person("Steven","Sanderson", email = "spsanderson@gmail.com", role = c("aut","cre")), person("Steven Sanderson", role = "cph"))
Description: Provides data for functions typically used in the 'healthyR' package.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/spsanderson/healthyR.data
BugReports: https://github.com/spsanderson/healthyR.data/issues
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-11-19 16:34:02 UTC; Steve
Author: Steven Sanderson [aut, cre], Steven Sanderson [cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-23 08:00:02 UTC

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New package EcotoneFinder with initial version 0.2.2
Package: EcotoneFinder
Type: Package
Title: Characterising and Locating Ecotones and Communities
Version: 0.2.2
Author: Antoine Bagnaro
Maintainer: Antoine Bagnaro <antoine.bagnaro@postgrad.otago.ac.nz>
Description: Analytical methods to locate and characterise ecotones, ecosystems and environmental patchiness along ecological gradients. Methods are implemented for isolated sampling or for space/time series. It includes Detrended Correspondence Analysis (Hill & Gauch (1980) <doi:10.1007/BF00048870>), fuzzy clustering (De Cáceres et al. (2010) <doi:10.1080/01621459.1963.10500845>), biodiversity indices (Jost (2006) <doi:10.1111/j.2006.0030-1299.14714.x>), and network analyses (Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>) - as well as tools to explore the number of clusters in the data. Functions to produce synthetic ecological datasets are also provided.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: cluster, colorspace, corrplot, e1071, ggplot2, graphics, qgraph, igraph, methods, philentropy, plyr, purrr, reshape, rlang, Rmisc, stats, vegan, vegclust, withr
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, bookdown
NeedsCompilation: no
Packaged: 2020-11-18 22:40:26 UTC; antoine
Repository: CRAN
Date/Publication: 2020-11-23 08:00:09 UTC

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Package CropScapeR updated to version 1.1.2 with previous version 1.1.0 dated 2020-08-01

Title: Access Cropland Data Layer Data via the 'CropScape' Web Service
Description: Interface to easily access Cropland Data Layer (CDL) data for any area of interest via the 'CropScape' <https://nassgeodata.gmu.edu/CropScape/> web service.
Author: Bowen Chen [aut, cre] (<https://orcid.org/0000-0003-0370-2756>), Benjamin Gramig [ctb], Taro Mieno [ctb]
Maintainer: Bowen Chen <bwchen0719@gmail.com>

Diff between CropScapeR versions 1.1.0 dated 2020-08-01 and 1.1.2 dated 2020-11-23

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Package auk updated to version 0.4.3 with previous version 0.4.2 dated 2020-10-19

Title: eBird Data Extraction and Processing in R
Description: Extract and process bird sightings records from eBird (<http://ebird.org>), an online tool for recording bird observations. Public access to the full eBird database is via the eBird Basic Dataset (EBD; see <http://ebird.org/ebird/data/download> for access), a downloadable text file. This package is an interface to AWK for extracting data from the EBD based on taxonomic, spatial, or temporal filters, to produce a manageable file size that can be imported into R.
Author: Matthew Strimas-Mackey [aut, cre] (<https://orcid.org/0000-0001-8929-7776>), Eliot Miller [aut], Wesley Hochachka [aut], Cornell Lab of Ornithology [cph]
Maintainer: Matthew Strimas-Mackey <mes335@cornell.edu>

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Package mStats updated to version 3.4.0 with previous version 3.2.2 dated 2020-03-31

Title: Epidemiological Data Analysis
Description: This is a tool for epidemiologist, medical data analyst, medical or public health professionals. It contains three domains of functions: 1) data management, 2) statistical analysis and 3) calculating epidemiological measures.
Author: Myo Minn Oo [aut, cre] (<https://orcid.org/0000-0003-4089-016X>)
Maintainer: Myo Minn Oo <dr.myominnoo@gmail.com>

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More information about mStats at CRAN
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Package breakfast updated to version 2.1 with previous version 2.0 dated 2020-11-03

Title: Methods for Fast Multiple Change-Point Detection and Estimation
Description: A developing software suite for multiple change-point detection/estimation (data segmentation) in data sequences.
Author: Andreas Anastasiou [aut], Yining Chen [aut, cre], Haeran Cho [aut], Piotr Fryzlewicz [aut]
Maintainer: Yining Chen <y.chen101@lse.ac.uk>

Diff between breakfast versions 2.0 dated 2020-11-03 and 2.1 dated 2020-11-23

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More information about breakfast at CRAN
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