Thu, 06 Feb 2020

New package wdpar with initial version 1.0.1
Package: wdpar
Type: Package
Version: 1.0.1
Title: Interface to the World Database on Protected Areas
Description: Fetch and clean data from the World Database on Protected Areas (WDPA). Data is obtained from Protected Planet <http://protectedplanet.net>.
Authors@R: c(person(c('Jeffrey', 'O'), 'Hanson', email='jeffrey.hanson@uqconnect.edu.au', role = c('aut', 'cre')))
Imports: utils, sp, assertthat (>= 0.2.0), progress (>= 1.2.0), curl (>= 3.2), rappdirs (>= 0.3.1), httr (>= 1.3.1), countrycode (>= 1.1.0), wdman (>= 0.2.4), RSelenium (>= 1.7.4), xml2 (>= 1.2.0), cli (>= 1.0.1), lwgeom (>= 0.1-4)
Suggests: testthat (>= 2.0.1), knitr (>= 1.2.0), roxygen2 (>= 6.1.1), rmarkdown (>= 1.10), ggmap (>= 2.6.1), ggplot2 (>= 3.1.0), pingr (>= 1.1.2)
Depends: R(>= 3.4.0), sf(>= 0.7-1)
License: GPL-3
LazyData: true
URL: https://prioritizr.github.io/wdpar, https://github.com/prioritizr/wdpar
BugReports: https://github.com/prioritizr/wdpar/issues
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Collate: 'internal.R' 'geo.R' 'package.R' 'wdpa_clean.R' 'wdpa_url.R' 'wdpa_fetch.R' 'wdpa_read.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2020-02-06 22:01:38 UTC; jeff
Author: Jeffrey O Hanson [aut, cre]
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>
Repository: CRAN
Date/Publication: 2020-02-07 01:10:02 UTC

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New package RMallow with initial version 1.1
Package: RMallow
Type: Package
Title: Fit Multi-Modal Mallows' Models to Ranking Data
Version: 1.1
Date: 2020-01-23
Depends: combinat
Authors@R: person("Erik", "Gregory", email = "egregory2011@gmail.com", role = c("aut", "cre"))
Description: An EM algorithm to fit Mallows' Models to full or partial rankings, with or without ties. Based on Adkins and Flinger (1998) <doi:10.1080/03610929808832223>.
License: GPL (>= 2)
Packaged: 2020-02-06 17:51:43 UTC; adrien
Repository: CRAN
Date/Publication: 2020-02-07 01:10:16 UTC
NeedsCompilation: no
Author: Erik Gregory [aut, cre]
Maintainer: Erik Gregory <egregory2011@gmail.com>

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Package groc updated to version 1.0.7 with previous version 1.0.6 dated 2018-05-10

Title: Generalized Regression on Orthogonal Components
Description: Robust multiple or multivariate linear regression, nonparametric regression on orthogonal components, classical or robust partial least squares models.
Author: Pierre Lafaye De Micheaux [aut, cre], Martin Bilodeau [aut], Jiahui Wang [cph] (covRob and related functions from orphaned package robust), Ruben Zamar [cph] (covRob and related functions from orphaned package robust), Alfio Marazzi [cph] (covRob and related functions from orphaned package robust), Victor Yohai [cph] (covRob and related functions from orphaned package robust), Matias Salibian-Barrera [cph] (covRob and related functions from orphaned package robust), Ricardo Maronna [cph] (covRob and related functions from orphaned package robust), Eric Zivot [cph] (covRob and related functions from orphaned package robust), David Rocke [cph] (covRob and related functions from orphaned package robust), Doug Martin [cph] (covRob and related functions from orphaned package robust), Martin Maechler [cph] (covRob and related functions from orphaned package robust), Kjell Konis [cph] (covRob and related functions from orphaned package robust)
Maintainer: Pierre Lafaye De Micheaux <lafaye@unsw.edu.au>

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Package dbplot updated to version 0.3.3 with previous version 0.3.2 dated 2019-07-02

Title: Simplifies Plotting Data Inside Databases
Description: Leverages 'dplyr' to process the calculations of a plot inside a database. This package provides helper functions that abstract the work at three levels: outputs a 'ggplot', outputs the calculations, outputs the formula needed to calculate bins.
Author: Edgar Ruiz [aut, cre]
Maintainer: Edgar Ruiz <edgararuiz@gmail.com>

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Package corporaexplorer updated to version 0.8.1 with previous version 0.8.0 dated 2019-12-02

Title: A 'Shiny' App for Exploration of Text Collections
Description: Facilitates dynamic exploration of text collections through an intuitive graphical user interface and the power of regular expressions. The package contains 1) a helper function to convert a data frame to a 'corporaexplorerobject', 2) a 'Shiny' app for fast and flexible exploration of a 'corporaexplorerobject', and 3) a 'Shiny' app for simple retrieval/extraction of documents from a 'corporaexplorerobject' in a reading-friendly format. The package also includes demo apps with which one can explore Jane Austen's novels and the State of the Union Addresses (data fra the 'janeaustenr' and 'sotu' packages respectively).
Author: Kristian Lundby Gjerde [aut, cre]
Maintainer: Kristian Lundby Gjerde <kristian.gjerde@gmail.com>

Diff between corporaexplorer versions 0.8.0 dated 2019-12-02 and 0.8.1 dated 2020-02-06

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Package BayesReversePLLH updated to version 1.3 with previous version 1.2 dated 2020-02-01

Title: Fits the Bayesian Piecewise Linear Log-Hazard Model
Description: Contains posterior samplers for the Bayesian piecewise linear log-hazard and piecewise exponential hazard models, including Cox models. Posterior mean restricted survival times are also computed for non-Cox an Cox models with only treatment indicators. The ApproxMean() function can be used to estimate restricted posterior mean survival times given a vector of patient covariates in the Cox model. Functions included to return the posterior mean hazard and survival functions for the piecewise exponential and piecewise linear log-hazard models. Chapple, AG, Peak, T, Hemal, A (2020). Under Revision.
Author: Andrew G Chapple
Maintainer: Andrew G Chapple <achapp@lsuhsc.edu>

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Package cowsay updated to version 0.8.0 with previous version 0.7.0 dated 2018-09-18

Title: Messages, Warnings, Strings with Ascii Animals
Description: Allows printing of character strings as messages/warnings/etc. with ASCII animals, including cats, cows, frogs, chickens, ghosts, and more.
Author: Scott Chamberlain [aut, cre], Amanda Dobbyn [aut], Tyler Rinker [ctb], Thomas Leeper [ctb], Noam Ross [ctb], Rich FitzJohn [ctb], Carson Sievert [ctb], Kiyoko Gotanda [ctb], Andy Teucher [ctb], Karl Broman [ctb], Franz-Sebastian Krah [ctb], Lucy D'Agostino McGowan [ctb], Guangchuang Yu [ctb], Philipp Boersch-Supan [ctb], Andreas Brandmaier [ctb], Marion Louveaux [ctb]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package pins updated to version 0.3.2 with previous version 0.3.1 dated 2020-01-10

Title: Pin, Discover and Share Resources
Description: Pin remote resources into a local cache to work offline, improve speed and avoid recomputing; discover and share resources in local folders, 'GitHub', 'Kaggle' or 'RStudio Connect'. Resources can be anything from 'CSV', 'JSON', or image files to arbitrary R objects.
Author: Javier Luraschi [aut, cre], RStudio [cph]
Maintainer: Javier Luraschi <javier@rstudio.com>

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Package DHARMa updated to version 0.2.7 with previous version 0.2.6 dated 2019-11-26

Title: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models
Description: The 'DHARMa' package uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed models. Currently supported are linear and generalized linear (mixed) models from 'lme4' (classes 'lmerMod', 'glmerMod'), 'glmmTMB' and 'spaMM', generalized additive models ('gam' from 'mgcv'), 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model classes. Moreover, externally created simulations, e.g. posterior predictive simulations from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well. The resulting residuals are standardized to values between 0 and 1 and can be interpreted as intuitively as residuals from a linear regression. The package also provides a number of plot and test functions for typical model misspecification problems, such as over/underdispersion, zero-inflation, and residual spatial and temporal autocorrelation.
Author: Florian Hartig [aut, cre] (<https://orcid.org/0000-0002-6255-9059>)
Maintainer: Florian Hartig <florian.hartig@biologie.uni-regensburg.de>

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Package clere updated to version 1.2.0 with previous version 1.1.4 dated 2016-03-22

Title: Simultaneous Variables Clustering and Regression
Description: Implements an empirical Bayes approach for simultaneous variable clustering and regression. This version also (re)implements in C++ an R script proposed by Howard Bondell that fits the Pairwise Absolute Clustering and Sparsity (PACS) methodology (see Sharma et al (2013) <DOI:10.1080/15533174.2012.707849>).
Author: Loic Yengo [aut, cre], Mickaël Canouil [aut] (<https://orcid.org/0000-0002-3396-4549>)
Maintainer: Loic Yengo <loic.yengo@gmail.com>

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Package AzureVM updated to version 2.1.1 with previous version 2.1.0 dated 2019-11-03

Title: Virtual Machines in 'Azure'
Description: Functionality for working with virtual machines (VMs) in Microsoft's 'Azure' cloud: <https://azure.microsoft.com/en-us/services/virtual-machines/>. Includes facilities to deploy, startup, shutdown, and cleanly delete VMs and VM clusters. Deployment configurations can be highly customised, and can make use of existing resources as well as creating new ones. A selection of predefined configurations is provided to allow easy deployment of commonly used Linux and Windows images, including Data Science Virtual Machines. With a running VM, execute scripts and install optional extensions. Part of the 'AzureR' family of packages.
Author: Hong Ooi [aut, cre], Microsoft [cph]
Maintainer: Hong Ooi <hongooi@microsoft.com>

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Package WrightMap updated to version 1.2.2 with previous version 1.2.1 dated 2016-03-23

Title: IRT Item-Person Map with 'ConQuest' Integration
Description: A powerful yet simple graphical tool available in the field of psychometrics is the Wright Map (also known as item maps or item-person maps), which presents the location of both respondents and items on the same scale. Wright Maps are commonly used to present the results of dichotomous or polytomous item response models. The 'WrightMap' package provides functions to create these plots from item parameters and person estimates stored as R objects. Although the package can be used in conjunction with any software used to estimate the IRT model (e.g. 'TAM', 'mirt', 'eRm' or 'IRToys' in 'R', or 'Stata', 'Mplus', etc.), 'WrightMap' features special integration with 'ConQuest' to facilitate reading and plotting its output directly.The 'wrightMap' function creates Wright Maps based on person estimates and item parameters produced by an item response analysis. The 'CQmodel' function reads output files created using 'ConQuest' software and creates a set of data frames for easy data manipulation, bundled in a 'CQmodel' object. The 'wrightMap' function can take a 'CQmodel' object as input or it can be used to create Wright Maps directly from data frames of person and item parameters.
Author: David Torres Irribarra & Rebecca Freund
Maintainer: David Torres Irribarra <david@torresirribarra.me>

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Package sjstats updated to version 0.17.9 with previous version 0.17.8 dated 2020-01-21

Title: Collection of Convenient Functions for Common Statistical Computations
Description: Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like Cramer's V, Phi, or effect size statistics like Eta or Omega squared), or for which currently no functions available. Second, another focus lies on weighted variants of common statistical measures and tests like weighted standard error, mean, t-test, correlation, and more.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package knitr updated to version 1.28 with previous version 1.27 dated 2020-01-16

Title: A General-Purpose Package for Dynamic Report Generation in R
Description: Provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Adam Vogt [ctb], Alastair Andrew [ctb], Alex Zvoleff [ctb], Andre Simon [ctb] (the CSS files under inst/themes/ were derived from the Highlight package http://www.andre-simon.de), Aron Atkins [ctb], Aaron Wolen [ctb], Ashley Manton [ctb], Atsushi Yasumoto [ctb] (<https://orcid.org/0000-0002-8335-495X>), Ben Baumer [ctb], Brian Diggs [ctb], Brian Zhang [ctb], Cassio Pereira [ctb], Christophe Dervieux [ctb], David Hugh-Jones [ctb], David Robinson [ctb], Doug Hemken [ctb], Duncan Murdoch [ctb], Elio Campitelli [ctb], Emily Riederer [ctb], Fabian Hirschmann [ctb], Fitch Simeon [ctb], Forest Fang [ctb], Frank E Harrell Jr [ctb] (the Sweavel package at inst/misc/Sweavel.sty), Garrick Aden-Buie [ctb], Gregoire Detrez [ctb], Hadley Wickham [ctb], Hao Zhu [ctb], Heewon Jeon [ctb], Henrik Bengtsson [ctb], Hiroaki Yutani [ctb], Ian Lyttle [ctb], Hodges Daniel [ctb], Jake Burkhead [ctb], James Manton [ctb], Jared Lander [ctb], Jason Punyon [ctb], Javier Luraschi [ctb], Jeff Arnold [ctb], Jenny Bryan [ctb], Jeremy Ashkenas [ctb, cph] (the CSS file at inst/misc/docco-classic.css), Jeremy Stephens [ctb], Jim Hester [ctb], Joe Cheng [ctb], Johannes Ranke [ctb], John Honaker [ctb], John Muschelli [ctb], Jonathan Keane [ctb], JJ Allaire [ctb], Johan Toloe [ctb], Jonathan Sidi [ctb], Joseph Larmarange [ctb], Julien Barnier [ctb], Kaiyin Zhong [ctb], Kamil Slowikowski [ctb], Karl Forner [ctb], Kevin K. Smith [ctb], Kirill Mueller [ctb], Kohske Takahashi [ctb], Lorenz Walthert [ctb], Lucas Gallindo [ctb], Marius Hofert [ctb], Martin Modrák [ctb], Michael Chirico [ctb], Michael Friendly [ctb], Michal Bojanowski [ctb], Michel Kuhlmann [ctb], Miller Patrick [ctb], Nacho Caballero [ctb], Nick Salkowski [ctb], Niels Richard Hansen [ctb], Noam Ross [ctb], Obada Mahdi [ctb], Qiang Li [ctb], Ramnath Vaidyanathan [ctb], Richard Cotton [ctb], Robert Krzyzanowski [ctb], Romain Francois [ctb], Ruaridh Williamson [ctb], Scott Kostyshak [ctb], Sebastian Meyer [ctb], Sietse Brouwer [ctb], Simon de Bernard [ctb], Sylvain Rousseau [ctb], Taiyun Wei [ctb], Thibaut Assus [ctb], Thibaut Lamadon [ctb], Thomas Leeper [ctb], Tim Mastny [ctb], Tom Torsney-Weir [ctb], Trevor Davis [ctb], Viktoras Veitas [ctb], Weicheng Zhu [ctb], Wush Wu [ctb], Zachary Foster [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package GeneNet updated to version 1.2.14 with previous version 1.2.13 dated 2015-08-02

Title: Modeling and Inferring Gene Networks
Description: Analyzes gene expression (time series) data with focus on the inference of gene networks. In particular, GeneNet implements the methods of Schaefer and Strimmer (2005a,b,c) and Opgen-Rhein and Strimmer (2006, 2007) for learning large-scale gene association networks (including assignment of putative directions).
Author: Juliane Schaefer, Rainer Opgen-Rhein, and Korbinian Strimmer.
Maintainer: Korbinian Strimmer <strimmerlab@gmail.com>

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Package sampSurf updated to version 0.7-5 with previous version 0.7-4 dated 2017-09-27

Title: Sampling Surface Simulation for Areal Sampling Methods
Description: Sampling surface simulation is useful in the comparison of different areal sampling methods in forestry, ecology and natural resources. The sampSurf package allows the simulation of numerous sampling methods for standing trees and downed woody debris in a spatial context. It also provides an S4 class and method structure that facilitates the addition of new sampling methods.
Author: Jeffrey H. Gove
Maintainer: Jeffrey H. Gove <jgove@fs.fed.us>

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Package ropenblas updated to version 0.2.1 with previous version 0.2.0 dated 2019-12-09

Title: Download, Compile and Link 'OpenBLAS' Library with R
Description: The 'ropenblas' package (<https://prdm0.github.io/ropenblas/>) is useful for users of any 'GNU/Linux' distribution. It will be possible to download, compile and link the 'OpenBLAS' library (<https://www.openblas.net/>) with the R language, always by the same procedure, regardless of the 'GNU/Linux' distribution used. With the 'ropenblas' package it is possible to download, compile and link the latest version of the 'OpenBLAS' library even the repositories of the 'GNU/Linux' distribution used do not include the latest versions of 'OpenBLAS'. If of interest, older versions of the 'OpenBLAS' library may be considered. Linking R with an optimized version of 'BLAS' (<http://www.netlib.org/blas/>) may improve the computational performance of R code. The 'OpenBLAS' library is an optimized implementation of 'BLAS' that can be easily linked to R with the 'ropenblas' package.
Author: Pedro Rafael D. Marinho [aut, cre]
Maintainer: Pedro Rafael D. Marinho <pedro.rafael.marinho@gmail.com>

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New package pliable with initial version 1.1.1
Package: pliable
Type: Package
Title: The Pliable Lasso
Version: 1.1.1
Date: 2020-02-06
Author: Robert Tibshirani, Jerome Friedman
Maintainer: Robert Tibshirani <tibs@stanford.edu>
Depends: class, glmnet
License: GPL-3
Suggests: knitr, rmarkdown
Description: Fits a pliable lasso model. For details see Tibshirani and Friedman (2018) <arXiv:1712.00484>.
URL: https://arxiv.org/abs/1712.00484
Packaged: 2020-02-06 14:36:13 UTC; tibs
VignetteBuilder: knitr
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2020-02-06 16:50:05 UTC
RoxygenNote: 6.1.1

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Package np updated to version 0.60-10 with previous version 0.60-9 dated 2018-10-25

Title: Nonparametric Kernel Smoothing Methods for Mixed Data Types
Description: Nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, <http://www.nserc-crsng.gc.ca>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <http://www.sshrc-crsh.gc.ca>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <http://www.sharcnet.ca>).
Author: Jeffrey S. Racine [aut, cre], Tristen Hayfield [aut]
Maintainer: Jeffrey S. Racine <racinej@mcmaster.ca>

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New package MTPS with initial version 0.1.9
Package: MTPS
Type: Package
Title: Multi-Task Prediction using Stacking Algorithms
Version: 0.1.9
Authors@R: c( person("Li Xing", role=c("aut", "cre"), email="sfulxing@gmail.com"), person("Peijie Xie", role = "ctb"), person("Mary Lesperance", role = "aut"), person("Xuekui Zhang",role = c("aut")) )
Description: Simultaneous multiple outcomes prediction based on revised stacking algorithms, which enables the integration of information from predictions of individual models. An implementation of methodologies proposed in our paper: Li Xing, Mary L Lesperance, Xuekui Zhang. (2019) Bioinformatics, "Simultaneous prediction of multiple outcomes using revised stacking algorithms" <doi:10.1093/bioinformatics/btz531>.
License: GPL (>= 2)
URL: https://doi.org/10.1093/bioinformatics/btz531
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), glmnet, rpart, MASS, e1071, class
Suggests: knitr, rmarkdown, ggplot2, reshape2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-26 21:02:06 UTC; ying
Maintainer: Li Xing <sfulxing@gmail.com>
RoxygenNote: 6.1.1
Author: Li Xing [aut, cre], Peijie Xie [ctb], Mary Lesperance [aut], Xuekui Zhang [aut]
Repository: CRAN
Date/Publication: 2020-02-06 16:40:02 UTC

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New package BGGM with initial version 1.0.0
Package: BGGM
Type: Package
Title: Bayesian Gaussian Graphical Models
Version: 1.0.0
Date: 2020-01-16
Authors@R: c(person("Donald", "Williams", email = "drwwilliams@ucdavis.edu", role = c("aut", "cre")), person("Joris", "Mulder", email = "J.Mulder3@uvt.nl", role = "aut"))
Description: Fit Bayesian Gaussian graphical models. The methods are separated into two Bayesian approaches for inference: hypothesis testing and estimation. There are extensions for confirmatory hypothesis testing, comparing Gaussian graphical models, and node wise predictability. These methods were recently introduced in the Gaussian graphical model literature, including Williams (2019) <doi:10.31234/osf.io/x8dpr>, Williams and Mulder (2019) <doi:10.31234/osf.io/ypxd8>, Williams, Rast, Pericchi, and Mulder (2019) <doi:10.31234/osf.io/yt386>.
Depends: R (>= 3.5.0)
License: GPL-2
Imports: mvnfast (>= 0.2.5), foreach (>= 1.4.7), doParallel (>= 1.0.15), ggplot2 (>= 3.2.1), mvtnorm (>= 1.0.11), stringr (>= 1.4.0), ggridges (>= 0.5.1), GGally (>= 1.4.0), pracma (>= 2.2.5), network (>= 1.15), bayesplot (>= 1.7.1), sna (>= 2.5), shiny (>= 1.4.0), reshape2 (>= 1.4.3), cowplot (>= 1.0.0), stats, parallel, Matrix, reshape, MASS
Suggests: knitr, rmarkdown, dplyr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-26 19:25:59 UTC; willidon
Author: Donald Williams [aut, cre], Joris Mulder [aut]
Maintainer: Donald Williams <drwwilliams@ucdavis.edu>
Repository: CRAN
Date/Publication: 2020-02-06 16:20:22 UTC

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Package adespatial updated to version 0.3-8 with previous version 0.3-7 dated 2019-06-04

Title: Multivariate Multiscale Spatial Analysis
Description: Tools for the multiscale spatial analysis of multivariate data. Several methods are based on the use of a spatial weighting matrix and its eigenvector decomposition (Moran's Eigenvectors Maps, MEM). Several approaches are described in the review Dray et al (2012) <doi:10.1890/11-1183.1>.
Author: Stéphane Dray, David Bauman, Guillaume Blanchet, Daniel Borcard, Sylvie Clappe, Guillaume Guenard, Thibaut Jombart, Guillaume Larocque, Pierre Legendre, Naima Madi, Helene H Wagner
Maintainer: Stéphane Dray <stephane.dray@univ-lyon1.fr>

Diff between adespatial versions 0.3-7 dated 2019-06-04 and 0.3-8 dated 2020-02-06

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New package rco with initial version 1.0.0
Package: rco
Type: Package
Title: The R Code Optimizer
Version: 1.0.0
Authors@R: c( person(given = "Juan Cruz", family = "Rodriguez", role = c("aut", "cre"), email = "jcrodriguez@unc.edu.ar"), person("Yihui", "Xie", role = "ctb", email = "xie@yihui.name", comment = c(ORCID = "0000-0003-0645-5666")), person("Nicolás", "Wolovick", role = "ctb", email = "nicolasw@famaf.unc.edu.ar") )
Maintainer: Juan Cruz Rodriguez <jcrodriguez@unc.edu.ar>
Description: Automatically apply different strategies to optimize R code. 'rco' functions take R code as input, and returns R code as output.
Depends: R (>= 3.6.0)
License: GPL-3
URL: https://github.com/jcrodriguez1989/rco/
BugReports: https://github.com/jcrodriguez1989/rco/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.0.2
Suggests: covr, diffr, ggplot2, httr, knitr, microbenchmark, rstudioapi, rvest, shiny, shinythemes, testthat, xml2
NeedsCompilation: no
Packaged: 2020-01-26 14:06:47 UTC; jcrodriguez
Author: Juan Cruz Rodriguez [aut, cre], Yihui Xie [ctb] (<https://orcid.org/0000-0003-0645-5666>), Nicolás Wolovick [ctb]
Repository: CRAN
Date/Publication: 2020-02-06 16:00:03 UTC

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New package rawKS with initial version 0.1.0
Package: rawKS
Title: Easily Get True-Positive Rate and False-Positive Rate and KS Statistic
Version: 0.1.0
Authors@R: person(given = "Jiaxiang", family = "Li", role = c("aut", "cre"), email = "alex.lijiaxiang@foxmail.com", comment = c(ORCID = "https://orcid.org/0000-0003-3196-6492"))
Description: The Kolmogorov-Smirnov (K-S) statistic is a standard method to measure the model strength for credit risk scoring models. This package calculates the K–S statistic and plots the true-positive rate and false-positive rate to measure the model strength. This package was written with the credit marketer, who uses risk models in conjunction with his campaigns. The users could read more details from Thrasher (1992) <doi:10.1002/dir.4000060408> and 'pyks' <https://pypi.org/project/pyks/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, magrittr, ROCR, ggplot2, tidyr
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-26 15:09:41 UTC; lijiaxiang
Author: Jiaxiang Li [aut, cre] (<https://orcid.org/0000-0003-3196-6492>)
Maintainer: Jiaxiang Li <alex.lijiaxiang@foxmail.com>
Repository: CRAN
Date/Publication: 2020-02-06 16:00:06 UTC

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Package imagine updated to version 1.5.3 with previous version 1.5.2 dated 2019-07-15

Title: IMAGing engINEs, Tools for Application of Image Filters to Data Matrices
Description: Provides fast application of image filters to data matrices, using R and C++ algorithms.
Author: Wencheng Lau-Medrano [aut, cre]
Maintainer: Wencheng Lau-Medrano <luis.laum@gmail.com>

Diff between imagine versions 1.5.2 dated 2019-07-15 and 1.5.3 dated 2020-02-06

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Package dexter updated to version 1.0.4 with previous version 1.0.3 dated 2020-01-14

Title: Data Management and Analysis of Tests
Description: A system for the management, assessment, and psychometric analysis of data from educational and psychological tests.
Author: Gunter Maris, Timo Bechger, Jesse Koops, Ivailo Partchev
Maintainer: Jesse Koops <jesse.koops@cito.nl>

Diff between dexter versions 1.0.3 dated 2020-01-14 and 1.0.4 dated 2020-02-06

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New package danstat with initial version 0.1.0
Package: danstat
Type: Package
Title: R Client for the Statistics Denmark Databank API
Version: 0.1.0
Author: Valeri Voev
Maintainer: Valeri Voev <v_voev@yahoo.com>
Description: The purpose of the package is to enable an R function interface into the Statistics Denmark Databank API mainly for research purposes. The Statistics Denmark Databank API has four endpoints, see here for more information and testing the API in their console: <https://www.dst.dk/en/Statistik/statistikbanken/api>. This package mimics the structure of the API and provides four main functions to match the functionality of the API endpoints.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Imports: httr, jsonlite, readr
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, purrr, dplyr, ggplot2, kableExtra
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-26 07:38:14 UTC; dkvaravo
Repository: CRAN
Date/Publication: 2020-02-06 15:50:02 UTC

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New package slider with initial version 0.1.0
Package: slider
Title: Sliding Window Functions
Version: 0.1.0
Authors@R: c(person(given = "Davis", family = "Vaughan", role = c("aut", "cre"), email = "davis@rstudio.com"), person(given = "RStudio", role = "cph"))
Description: Provides type-stable rolling window functions over any R data type. Cumulative and expanding windows are also supported. For more advanced usage, an index can be used as a secondary vector that defines how sliding windows are to be created.
License: MIT + file LICENSE
URL: https://github.com/DavisVaughan/slider
BugReports: https://github.com/DavisVaughan/slider/issues
Depends: R (>= 3.2)
Imports: glue, rlang (>= 0.4.1), vctrs (>= 0.2.2), warp
Suggests: covr, dplyr (>= 0.8.3), knitr, lubridate, rmarkdown, testthat (>= 2.1.0), xml2
LinkingTo: vctrs (>= 0.2.2)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Collate: 'block.R' 'conditions.R' 'hop-common.R' 'hop-index-common.R' 'hop-index.R' 'hop-index2.R' 'hop.R' 'hop2.R' 'names.R' 'phop-index.R' 'phop.R' 'slide-index2.R' 'pslide-index.R' 'slide-period2.R' 'pslide-period.R' 'slide2.R' 'pslide.R' 'slide-common.R' 'slide-index-common.R' 'slide-index.R' 'slide-period-common.R' 'slide-period.R' 'slide.R' 'slider-package.R' 'utils.R' 'zzz.R'
NeedsCompilation: yes
Packaged: 2020-02-06 13:43:29 UTC; davis
Author: Davis Vaughan [aut, cre], RStudio [cph]
Maintainer: Davis Vaughan <davis@rstudio.com>
Repository: CRAN
Date/Publication: 2020-02-06 14:10:02 UTC

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Package HRM updated to version 1.2.1 with previous version 1.0.2 dated 2018-10-17

Title: High-Dimensional Repeated Measures
Description: Methods for testing main and interaction effects in possibly high-dimensional parametric or nonparametric repeated measures in factorial designs for univariate or multivariate data. The observations of the subjects are assumed to be multivariate normal if using the parametric test. The nonparametric version tests with regard to nonparametric relative effects (based on pseudo-ranks). It is possible to use up to 2 whole- and 3 subplot factors.
Author: Martin Happ [aut, cre] (<https://orcid.org/0000-0003-0009-2665>), Harrar W. Solomon [aut], Arne C. Bathke [aut]
Maintainer: Martin Happ <martin.happ@aon.at>

Diff between HRM versions 1.0.2 dated 2018-10-17 and 1.2.1 dated 2020-02-06

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Package errorist updated to version 0.0.3 with previous version 0.0.2 dated 2019-01-07

Title: Automatically Search Errors or Warnings
Description: Provides environment hooks that obtain errors and warnings which occur during the execution of code to automatically search for solutions.
Author: James Balamuta [aut, cre, cph] (<https://orcid.org/0000-0003-2826-8458>)
Maintainer: James Balamuta <balamut2@illinois.edu>

Diff between errorist versions 0.0.2 dated 2019-01-07 and 0.0.3 dated 2020-02-06

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 12 files changed, 121 insertions(+), 75 deletions(-)

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Package brglm2 updated to version 0.6.1 with previous version 0.6.0 dated 2019-11-08

Title: Bias Reduction in Generalized Linear Models
Description: Estimation and inference from generalized linear models based on various methods for bias reduction and maximum penalized likelihood with powers of the Jeffreys prior as penalty. The 'brglmFit' fitting method can achieve reduction of estimation bias by solving either the mean bias-reducing adjusted score equations in Firth (1993) <doi:10.1093/biomet/80.1.27> and Kosmidis and Firth (2009) <doi:10.1093/biomet/asp055>, or the median bias-reduction adjusted score equations in Kenne et al. (2016) <arXiv:1604.04768>, or through the direct subtraction of an estimate of the bias of the maximum likelihood estimator from the maximum likelihood estimates as in Cordeiro and McCullagh (1991) <http://www.jstor.org/stable/2345592>. See Kosmidis et al (2019) <doi:10.1007/s11222-019-09860-6> for more details. Estimation in all cases takes place via a quasi Fisher scoring algorithm, and S3 methods for the construction of of confidence intervals for the reduced-bias estimates are provided. In the special case of generalized linear models for binomial and multinomial responses (both ordinal and nominal), the adjusted score approaches return estimates with improved frequentist properties, that are also always finite, even in cases where the maximum likelihood estimates are infinite (e.g. complete and quasi-complete separation). 'brglm2' also provides pre-fit and post-fit methods for detecting separation and infinite maximum likelihood estimates in binomial response generalized linear models.
Author: Ioannis Kosmidis [aut, cre] (<https://orcid.org/0000-0003-1556-0302>), Kjell Konis [ctb], Euloge Clovis Kenne Pagui [ctb], Nicola Sartori [ctb]
Maintainer: Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>

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Package HaDeX updated to version 1.1 with previous version 1.0 dated 2019-08-30

Title: Analysis and Visualisation of Hydrogen/Deuterium Exchange Mass Spectrometry Data
Description: Functions for processing, analysis and visualization of Hydrogen Deuterium eXchange monitored by Mass Spectrometry experiments (HDX-MS). 'HaDeX' introduces a new standardized and reproducible workflow for the analysis of the HDX-MS data, including novel uncertainty intervals. Additionally, it covers data exploration, quality control and generation of publication-quality figures. All functionalities are also available in the in-built 'Shiny' app.
Author: Weronika Puchala [cre, aut] (<https://orcid.org/0000-0003-2163-1429>), Michal Burdukiewicz [aut] (<https://orcid.org/0000-0001-8926-582X>), Dominik Rafacz [ctb]
Maintainer: Weronika Puchala <puchala.weronika@gmail.com>

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Package evolqg updated to version 0.2-7 with previous version 0.2-6 dated 2019-04-08

Title: Tools for Evolutionary Quantitative Genetics
Description: Provides functions for covariance matrix comparisons, estimation of repeatabilities in measurements and matrices, and general evolutionary quantitative genetics tools.
Author: Ana Paula Assis, Diogo Melo, Edgar Zanella, Fabio Andrade Machado, Guilherme Garcia
Maintainer: Diogo Melo <diogro@usp.br>

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Package RcppProgress updated to version 0.4.2 with previous version 0.4.1 dated 2018-05-11

Title: An Interruptible Progress Bar with OpenMP Support for C++ in R Packages
Description: Allows to display a progress bar in the R console for long running computations taking place in c++ code, and support for interrupting those computations even in multithreaded code, typically using OpenMP.
Author: Karl Forner <karl.forner@gmail.com>
Maintainer: Karl Forner <karl.forner@gmail.com>

Diff between RcppProgress versions 0.4.1 dated 2018-05-11 and 0.4.2 dated 2020-02-06

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Package PerformanceAnalytics updated to version 2.0.4 with previous version 1.5.3 dated 2019-06-23

Title: Econometric Tools for Performance and Risk Analysis
Description: Collection of econometric functions for performance and risk analysis. In addition to standard risk and performance metrics, this package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.
Author: Brian G. Peterson [cre, aut, cph], Peter Carl [aut, cph], Kris Boudt [ctb, cph], Ross Bennett [ctb], Joshua Ulrich [ctb], Eric Zivot [ctb], Dries Cornilly [ctb], Eric Hung [ctb], Matthieu Lestel [ctb], Kyle Balkissoon [ctb], Diethelm Wuertz [ctb], Anthony Alexander Christidis [ctb], R. Douglas Martin [ctb], Zeheng 'Zenith' Zhou [ctb], Justin M. Shea [ctb]
Maintainer: Brian G. Peterson <brian@braverock.com>

Diff between PerformanceAnalytics versions 1.5.3 dated 2019-06-23 and 2.0.4 dated 2020-02-06

 PerformanceAnalytics-1.5.3/PerformanceAnalytics/tests/testthat                                                      |only
 PerformanceAnalytics-1.5.3/PerformanceAnalytics/tests/testthat.R                                                    |only
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/DESCRIPTION                                                         |   29 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/MD5                                                                 |  482 +-
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/NAMESPACE                                                           |    7 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/NEWS                                                                |   31 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/ActivePremium.R                                                   |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/AdjustedSharpeRatio.R                                             |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/AppraisalRatio.R                                                  |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/BernadoLedoitratio.R                                              |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/BurkeRatio.R                                                      |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/CAPM.alpha.R                                                      |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/CAPM.beta.R                                                       |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/CAPM.epsilon.R                                                    |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/CAPM.jensenAlpha.R                                                |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/CAPM.utils.R                                                      |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/CalmarRatio.R                                                     |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/CoMoments.R                                                       |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/DRatio.R                                                          |    2 
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 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/DrawdownPeak.R                                                    |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Drawdowns.R                                                       |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/ES.R                                                              |   63 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/FamaBeta.R                                                        |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Frequency.R                                                       |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/HerfindahlIndex.R                                                 |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/HurstIndex.R                                                      |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/InformationRatio.R                                                |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Kappa.R                                                           |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/KellyRatio.R                                                      |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/M2Sortino.R                                                       |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/MSquared.R                                                        |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/MSquaredExcess.R                                                  |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/MarketTiming.R                                                    |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/MartinRatio.R                                                     |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/MeanAbsoluteDeviation.R                                           |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/MinTRL.R                                                          |only
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/MultivariateMoments.R                                             |    4 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/NetSelectivity.R                                                  |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Omega.R                                                           |   41 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/OmegaExcessReturn.R                                               |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/OmegaSharpeRatio.R                                                |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/PainIndex.R                                                       |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/PainRatio.R                                                       |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/PortfolioRisk.R                                                   |    4 
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 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Return.Geltner.R                                                  |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Return.annualized.R                                               |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Return.calculate.R                                                |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Return.clean.R                                                    |    9 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Return.cumulative.R                                               |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Return.excess.R                                                   |    2 
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 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Return.read.R                                                     |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Return.relative.R                                                 |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/Selectivity.R                                                     |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/SemiDeviation.R                                                   |  100 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/SharpeRatio.R                                                     |   45 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/SharpeRatio.annualized.R                                          |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/SkewnessKurtosisRatio.R                                           |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/SmoothingIndex.R                                                  |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/SortinoRatio.R                                                    |   70 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/SpecificRisk.R                                                    |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/StdDev.R                                                          |   65 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/StdDev.annualized.R                                               |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/SystematicRisk.R                                                  |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/TotalRisk.R                                                       |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/TrackingError.R                                                   |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/TreynorRatio.R                                                    |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/UlcerIndex.R                                                      |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/UpDownRatios.R                                                    |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/UpsideFrequency.R                                                 |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/UpsidePotentialRatio.R                                            |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/UpsideRisk.R                                                      |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/VaR.Marginal.R                                                    |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/VaR.R                                                             |   91 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/VolatilitySkewness.R                                              |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/apply.fromstart.R                                                 |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/apply.rolling.R                                                   |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/chart.ACF.R                                                       |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/chart.ACFplus.R                                                   |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/chart.Bar.R                                                       |    2 
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 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/chart.CumReturns.R                                                |   25 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/chart.Drawdown.R                                                  |   35 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/chart.ECDF.R                                                      |    2 
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 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/chart.QQPlot.R                                                    |    2 
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 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/chart.Scatter.R                                                   |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/chart.SnailTrail.R                                                |    2 
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 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/charts.Bar.R                                                      |    2 
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 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/charts.RollingPerformance.R                                       |    5 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/charts.RollingRegression.R                                        |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/charts.TimeSeries.R                                               |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/checkData.R                                                       |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/findDrawdowns.R                                                   |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/kurtosis.R                                                        |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/legend.R                                                          |    5 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/lpm.R                                                             |   51 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/maxDrawdown.R                                                     |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/mean.utils.R                                                      |   74 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/na.skip.R                                                         |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/replaceTabs.R                                                     |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/skewness.R                                                        |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/sortDrawdowns.R                                                   |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.AnnualizedReturns.R                                         |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.Arbitrary.R                                                 |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.Autocorrelation.R                                           |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.CAPM.R                                                      |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.CalendarReturns.R                                           |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.CaptureRatios.R                                             |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.Correlation.R                                               |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.Distributions.R                                             |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.DownsideRisk.R                                              |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.DownsideRiskRatio.R                                         |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.Drawdowns.R                                                 |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.DrawdownsRatio.R                                            |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.HigherMoments.R                                             |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.InformationRatio.R                                          |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.MonthlyReturns.R                                            |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.RollingPeriods.R                                            |    2 
 PerformanceAnalytics-2.0.4/PerformanceAnalytics/R/table.SpecificRisk.R                                              |    2 
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Permanent link

Package NPflow updated to version 0.13.3 with previous version 0.13.1 dated 2017-08-02

Title: Bayesian Nonparametrics for Automatic Gating of Flow-Cytometry Data
Description: Dirichlet process mixture of multivariate normal, skew normal or skew t-distributions modeling oriented towards flow-cytometry data preprocessing applications. Method is detailed in: Hejblum, Alkhassimn, Gottardo, Caron & Thiebaut (2019) <doi: 10.1214/18-AOAS1209>.
Author: Boris P Hejblum [aut, cre], Chariff Alkhassim [aut], Francois Caron [aut]
Maintainer: Boris P Hejblum <boris.hejblum@u-bordeaux.fr>

Diff between NPflow versions 0.13.1 dated 2017-08-02 and 0.13.3 dated 2020-02-06

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More information about NPflow at CRAN
Permanent link

New package multimark with initial version 2.1.2
Package: multimark
Type: Package
Title: Capture-Mark-Recapture Analysis using Multiple Non-Invasive Marks
Version: 2.1.2
Date: 2020-02-05
Depends: R (>= 3.2.1)
Imports: parallel, Matrix, coda, statmod, RMark, Brobdingnag, mvtnorm, graphics, methods, stats, utils, prodlim, sp, raster
Authors@R: c(person("Brett T.", "McClintock", email = "brett.mcclintock@noaa.gov",role = c("aut", "cre")),person("Acho", "Arnold",role = c("ctb","cph"), comment = "C original matrix library, https://github.com/najela/matrix.h"),person("Barry", "Brown",role = "ctb", comment = "Fortran original ranlib library"),person("James", "Lovato",role = "ctb", comment = "Fortran original ranlib library"),person("John", "Burkardt",role = "ctb", comment = "C original ranlib library, http://people.sc.fsu.edu/~jburkardt/c_src/ranlib"),person("Cleve", "Moler",role = "ctb", comment = "C original linpack library, http://www.kkant.net/geist/ranlib/"),person("Arjun", "Gopalaswamy",role = "ctb", comment = "modified snippets of R package SPACECAP code"))
Description: Traditional and spatial capture-mark-recapture analysis with multiple non-invasive marks. The models implemented in 'multimark' combine encounter history data arising from two different non-invasive ``marks'', such as images of left-sided and right-sided pelage patterns of bilaterally asymmetrical species, to estimate abundance and related demographic parameters while accounting for imperfect detection. Bayesian models are specified using simple formulae and fitted using Markov chain Monte Carlo. Addressing deficiencies in currently available software, 'multimark' also provides a user-friendly interface for performing Bayesian multimodel inference using non-spatial or spatial capture-recapture data consisting of a single conventional mark or multiple non-invasive marks.
Suggests: testthat
License: GPL-2
LazyData: yes
ByteCompile: TRUE
RoxygenNote: 7.0.2
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-02-06 00:22:53 UTC; brettmcclintock
Author: Brett T. McClintock [aut, cre], Acho Arnold [ctb, cph] (C original matrix library, https://github.com/najela/matrix.h), Barry Brown [ctb] (Fortran original ranlib library), James Lovato [ctb] (Fortran original ranlib library), John Burkardt [ctb] (C original ranlib library, http://people.sc.fsu.edu/~jburkardt/c_src/ranlib), Cleve Moler [ctb] (C original linpack library, http://www.kkant.net/geist/ranlib/), Arjun Gopalaswamy [ctb] (modified snippets of R package SPACECAP code)
Maintainer: Brett T. McClintock <brett.mcclintock@noaa.gov>
Repository: CRAN
Date/Publication: 2020-02-06 12:10:02 UTC

More information about multimark at CRAN
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Package Matching updated to version 4.9-7 with previous version 4.9-6 dated 2019-05-07

Title: Multivariate and Propensity Score Matching with Balance Optimization
Description: Provides functions for multivariate and propensity score matching and for finding optimal balance based on a genetic search algorithm. A variety of univariate and multivariate metrics to determine if balance has been obtained are also provided.
Author: Jasjeet Singh Sekhon <sekhon@berkeley.edu>
Maintainer: Jasjeet Singh Sekhon <sekhon@berkeley.edu>

Diff between Matching versions 4.9-6 dated 2019-05-07 and 4.9-7 dated 2020-02-06

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Package hgm updated to version 1.18 with previous version 1.17 dated 2017-04-01

Title: Holonomic Gradient Method and Gradient Descent
Description: The holonomic gradient method (HGM, hgm) gives a way to evaluate normalization constants of unnormalized probability distributions by utilizing holonomic systems of differential or difference equations. The holonomic gradient descent (HGD, hgd) gives a method to find maximal likelihood estimates by utilizing the HGM.
Author: Nobuki Takayama, Tamio Koyama, Tomonari Sei, Hiromasa Nakayama, Kenta Nishiyama
Maintainer: Nobuki Takayama <takayama@math.kobe-u.ac.jp>

Diff between hgm versions 1.17 dated 2017-04-01 and 1.18 dated 2020-02-06

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More information about hgm at CRAN
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Package Buddle updated to version 2.0 with previous version 1.0 dated 2018-12-21

Title: A Deep Learning for Statistical Classification and Regression Analysis
Description: Statistical classification and regression have been popular among various fields and stayed in the limelight of scientists of those fields. Examples of the fields include clinical trials where the statistical classification of patients is indispensable to predict the clinical courses of diseases. Considering the negative impact of diseases on performing daily tasks, correctly classifying patients based on the clinical information is vital in that we need to identify patients of the high-risk group to develop a severe state and arrange medical treatment for them at an opportune moment. Deep learning - a part of artificial intelligence - has gained much attention, and research on it burgeons during past decades: see, e.g, Kazemi and Mirroshandel (2018) <DOI:10.1016/j.artmed.2017.12.001>. It is a veritable technique which was originally designed for the classification, and hence, the Buddle package can provide sublime solutions to various challenging classification and regression problems encountered in the clinical trials. The Buddle package is based on the back-propagation algorithm - together with various powerful techniques such as batch normalization and dropout - which performs a multi-layer feed-forward neural network: see Krizhevsky et. al (2017) <DOI:10.1145/3065386>, Schmidhuber (2015) <DOI:10.1016/j.neunet.2014.09.003> and LeCun et al. (1998) <DOI:10.1109/5.726791> for more details. This package contains two main functions: TrainBuddle() and FetchBuddle(). TrainBuddle() builds a feed-forward neural network model and trains the model. FetchBuddle() recalls the trained model which is the output of TrainBuddle(), classifies or regresses given data, and make a final prediction for the data.
Author: Jiwoong Kim <jwboys26 at gmail.com>
Maintainer: Jiwoong Kim <jwboys26@gmail.com>

Diff between Buddle versions 1.0 dated 2018-12-21 and 2.0 dated 2020-02-06

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More information about Buddle at CRAN
Permanent link

Package TreeSearch updated to version 0.4.0 with previous version 0.3.2 dated 2019-06-03

Title: Phylogenetic Tree Search Using Custom Optimality Criteria
Description: Searches for phylogenetic trees that are optimal using a user-defined criterion. Handles inapplicable data using the algorithm of Brazeau, Guillerme and Smith (2019) <doi:10.1093/sysbio/syy083>. Implements Profile Parsimony (Faith and Trueman, 2001) <doi:10.1080/10635150118627>, and Successive Approximations (Farris, 1969) <doi:10.2307/2412182>.
Author: Martin R. Smith [aut, cre, cph] (<https://orcid.org/0000-0001-5660-1727>), Martin Brazeau [cph] (<https://orcid.org/0000-0002-0650-1282>)
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

Diff between TreeSearch versions 0.3.2 dated 2019-06-03 and 0.4.0 dated 2020-02-06

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More information about TreeSearch at CRAN
Permanent link

New package ipmisc with initial version 1.0.0
Type: Package
Package: ipmisc
Title: Miscellaneous Functions for Data Cleaning and Analysis
Version: 1.0.0
Authors@R: person(given = "Indrajeet", family = "Patil", role = c("aut", "cre"), email = "patilindrajeet.science@gmail.com", comment = c(ORCID = "0000-0003-1995-6531"))
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>
Description: Provides functions needed for data cleaning and formatting and forms data cleaning and wrangling backend for the following packages: 'ggstatsplot', 'groupedstats', 'pairwiseComparisons', and 'statsExpressions' packages.
License: GPL-3 | file LICENSE
URL: https://indrajeetpatil.github.io/ipmisc/, https://github.com/IndrajeetPatil/ipmisc
BugReports: https://github.com/IndrajeetPatil/ipmisc/issues
Depends: R (>= 3.5.0)
Imports: crayon (>= 1.3.4), dplyr (>= 0.8.3), broomExtra, rlang (>= 0.4.2), rstudioapi, tibble (>= 2.0.1), tidyr (>= 1.0.0), zeallot
Suggests: ggplot2, knitr, rmarkdown, spelling, testthat
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.0.2.9000
NeedsCompilation: no
Packaged: 2020-01-25 21:28:00 UTC; inp099
Author: Indrajeet Patil [aut, cre] (<https://orcid.org/0000-0003-1995-6531>)
Repository: CRAN
Date/Publication: 2020-02-06 11:30:02 UTC

More information about ipmisc at CRAN
Permanent link

Package coveffectsplot updated to version 0.0.5 with previous version 0.0.4 dated 2019-10-09

Title: Produce Forest Plots to Visualize Covariate Effects
Description: Produce forest plots to visualize covariate effects using either the command line or an interactive 'Shiny' application.
Author: Samer Mouksassi [aut, cre] (<https://orcid.org/0000-0002-7152-6654>), Dean Attali [ctb]
Maintainer: Samer Mouksassi <samermouksassi@gmail.com>

Diff between coveffectsplot versions 0.0.4 dated 2019-10-09 and 0.0.5 dated 2020-02-06

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Package validatetools updated to version 0.5.0 with previous version 0.4.7 dated 2019-12-19

Title: Checking and Simplifying Validation Rule Sets
Description: Rule sets with validation rules may contain redundancies or contradictions. Functions for finding redundancies and problematic rules are provided, given a set a rules formulated with 'validate'.
Author: Edwin de Jonge [aut, cre] (<https://orcid.org/0000-0002-6580-4718>), Mark van der Loo [aut], Jacco Daalmans [ctb]
Maintainer: Edwin de Jonge <edwindjonge@gmail.com>

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Package tsutils updated to version 0.9.2 with previous version 0.9.0 dated 2019-01-11

Title: Time Series Exploration, Modelling and Forecasting
Description: Includes: (i) tests and visualisations that can help the modeller explore time series components and perform decomposition; (ii) modelling shortcuts, such as functions to construct lagmatrices and seasonal dummy variables of various forms; (iii) an implementation of the Theta method; (iv) tools to facilitate the design of the forecasting process, such as ABC-XYZ analyses; and (v) "quality of life" functions, such as treating time series for trailing and leading values.
Author: Nikolaos Kourentzes [aut, cre], Ivan Svetunkov [ctb], Oliver Schaer [ctb]
Maintainer: Nikolaos Kourentzes <nikolaos@kourentzes.com>

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Package soundgen updated to version 1.6.2 with previous version 1.6.1 dated 2020-01-22

Title: Parametric Voice Synthesis
Description: Tools for sound synthesis and acoustic analysis. Performs parametric synthesis of sounds with harmonic and noise components such as animal vocalizations or human voice. Also includes tools for spectral analysis, pitch tracking, audio segmentation, self-similarity matrices, morphing, etc.
Author: Andrey Anikin [aut, cre]
Maintainer: Andrey Anikin <rty.anik@rambler.ru>

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Package searcher updated to version 0.0.5 with previous version 0.0.4 dated 2019-07-05

Title: Query Search Interfaces
Description: Provides a search interface to look up terms on 'Google', 'Bing', 'DuckDuckGo', 'Startpage', 'Twitter', 'StackOverflow', 'RStudio Community', 'GitHub', and 'BitBucket'. Upon searching, a browser window will open with the aforementioned search results.
Author: James Balamuta [aut, cre] (<https://orcid.org/0000-0003-2826-8458>)
Maintainer: James Balamuta <balamut2@illinois.edu>

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Package Rvcg updated to version 0.19 with previous version 0.18 dated 2018-09-28

Title: Manipulations of Triangular Meshes Based on the 'VCGLIB' API
Description: Operations on triangular meshes based on 'VCGLIB'. This package integrates nicely with the R-package 'rgl' to render the meshes processed by 'Rvcg'. The Visualization and Computer Graphics Library (VCG for short) is an open source portable C++ templated library for manipulation, processing and displaying with OpenGL of triangle and tetrahedral meshes. The library, composed by more than 100k lines of code, is released under the GPL license, and it is the base of most of the software tools of the Visual Computing Lab of the Italian National Research Council Institute ISTI <http://vcg.isti.cnr.it>, like 'metro' and 'MeshLab'. The 'VCGLIB' source is pulled from trunk <https://github.com/cnr-isti-vclab/vcglib> and patched to work with options determined by the configure script as well as to work with the header files included by 'RcppEigen'.
Author: Stefan Schlager [aut, cre, cph], Girinon Francois [ctb]
Maintainer: Stefan Schlager <zarquon42@gmail.com>

Diff between Rvcg versions 0.18 dated 2018-09-28 and 0.19 dated 2020-02-06

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 Rvcg-0.19/Rvcg/DESCRIPTION                                                                          |    8 
 Rvcg-0.19/Rvcg/MD5                                                                                  |  458 -
 Rvcg-0.19/Rvcg/NAMESPACE                                                                            |    1 
 Rvcg-0.19/Rvcg/R/Rvcg-package.R                                                                     |    4 
 Rvcg-0.19/Rvcg/R/vcgBorder.r                                                                        |    1 
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 Rvcg-0.19/Rvcg/R/vcgClost.r                                                                         |    1 
 Rvcg-0.19/Rvcg/R/vcgCreateKD.r                                                                      |   13 
 Rvcg-0.19/Rvcg/R/vcgCurve.r                                                                         |    2 
 Rvcg-0.19/Rvcg/R/vcgImport.r                                                                        |   10 
 Rvcg-0.19/Rvcg/R/vcgIsolated.r                                                                      |   40 
 Rvcg-0.19/Rvcg/R/vcgMeshres.r                                                                       |    1 
 Rvcg-0.19/Rvcg/R/vcgMetro.r                                                                         |   15 
 Rvcg-0.19/Rvcg/R/vcgPlyRead.r                                                                       |    2 
 Rvcg-0.19/Rvcg/R/vcgPlyWrite.r                                                                      |   27 
 Rvcg-0.19/Rvcg/R/vcgQEdecim.r                                                                       |    1 
 Rvcg-0.19/Rvcg/R/vcgSmooth.r                                                                        |    1 
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 Rvcg-0.19/Rvcg/man/Rvcg-package.Rd                                                                  |    4 
 Rvcg-0.19/Rvcg/man/vcgBorder.Rd                                                                     |    2 
 Rvcg-0.19/Rvcg/man/vcgClean.Rd                                                                      |    2 
 Rvcg-0.19/Rvcg/man/vcgClost.Rd                                                                      |    6 
 Rvcg-0.19/Rvcg/man/vcgCurve.Rd                                                                      |    2 
 Rvcg-0.19/Rvcg/man/vcgImport.Rd                                                                     |    2 
 Rvcg-0.19/Rvcg/man/vcgIsolated.Rd                                                                   |    2 
 Rvcg-0.19/Rvcg/man/vcgMeshres.Rd                                                                    |    3 
 Rvcg-0.19/Rvcg/man/vcgObjWrite.Rd                                                                   |    1 
 Rvcg-0.19/Rvcg/man/vcgOffWrite.Rd                                                                   |    1 
 Rvcg-0.19/Rvcg/man/vcgPlyRead.Rd                                                                    |    2 
 Rvcg-0.19/Rvcg/man/vcgPlyWrite.Rd                                                                   |    2 
 Rvcg-0.19/Rvcg/man/vcgQEdecim.Rd                                                                    |    2 
 Rvcg-0.19/Rvcg/man/vcgSmooth.Rd                                                                     |    2 
 Rvcg-0.19/Rvcg/man/vcgStlWrite.Rd                                                                   |    1 
 Rvcg-0.19/Rvcg/man/vcgVolume.Rd                                                                     |only
 Rvcg-0.19/Rvcg/man/vcgWrlWrite.Rd                                                                   |    1 
 Rvcg-0.19/Rvcg/src/Makevars                                                                         |    2 
 Rvcg-0.19/Rvcg/src/ROneRing.cpp                                                                     |   26 
 Rvcg-0.19/Rvcg/src/RQEdecim.cpp                                                                     |    2 
 Rvcg-0.19/Rvcg/src/RallRead.cpp                                                                     |   47 
 Rvcg-0.19/Rvcg/src/Rballpivot.cpp                                                                   |  100 
 Rvcg-0.19/Rvcg/src/Rclean.cpp                                                                       |   85 
 Rvcg-0.19/Rvcg/src/Rcurvature.cpp                                                                   |   40 
 Rvcg-0.19/Rvcg/src/Rexport.cpp                                                                      |   32 
 Rvcg-0.19/Rvcg/src/RgetEdge.cpp                                                                     |   18 
 Rvcg-0.19/Rvcg/src/Rintersect.cpp                                                                   |    2 
 Rvcg-0.19/Rvcg/src/Risolated.cpp                                                                    |   66 
 Rvcg-0.19/Rvcg/src/Rkmeans.cpp                                                                      |   10 
 Rvcg-0.19/Rvcg/src/Rmeshres.cpp                                                                     |    4 
 Rvcg-0.19/Rvcg/src/Rmeshvol.cpp                                                                     |only
 Rvcg-0.19/Rvcg/src/Rsample.cpp                                                                      |    4 
 Rvcg-0.19/Rvcg/src/Rsubdivision.cpp                                                                 |   35 
 Rvcg-0.19/Rvcg/src/RvcgIO.h                                                                         |   12 
 Rvcg-0.19/Rvcg/src/init.c                                                                           |    2 
 Rvcg-0.19/Rvcg/src/typedef.h                                                                        |   13 
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 Rvcg-0.19/Rvcg/src/vcglib/vcg/complex/all_types.h                                                   |    1 
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 Rvcg-0.19/Rvcg/src/vcglib/wrap/dae/colladaformat.h                                                  |    2 
 Rvcg-0.19/Rvcg/src/vcglib/wrap/dae/util_dae.h                                                       |    1 
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 Rvcg-0.19/Rvcg/src/vcglib/wrap/gui/trackball.cpp                                                    |    5 
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 Rvcg-0.19/Rvcg/src/vcglib/wrap/system/qgetopt.cpp                                                   |    9 
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Package opentripplanner updated to version 0.2.0.8 with previous version 0.2.0.7 dated 2020-02-04

Title: Setup and connect to 'OpenTripPlanner'
Description: Setup and connect to 'OpenTripPlanner' (OTP) <http://www.opentripplanner.org/>. OTP is an open source platform for multi-modal and multi-agency journey planning written in 'Java'. The package allows you to manage a local version or connect to remote OTP server. This package has been peer-reviewed by rOpenSci (v. 0.2.0.0).
Author: Malcolm Morgan [aut, cre] (<https://orcid.org/0000-0002-9488-9183>), Marcus Young [aut] (<https://orcid.org/0000-0003-4627-1116>), Robin Lovelace [aut] (<https://orcid.org/0000-0001-5679-6536>), Layik Hama [ctb] (<https://orcid.org/0000-0003-1912-4890>)
Maintainer: Malcolm Morgan <m.morgan1@leeds.ac.uk>

Diff between opentripplanner versions 0.2.0.7 dated 2020-02-04 and 0.2.0.8 dated 2020-02-06

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 8 files changed, 28 insertions(+), 24 deletions(-)

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New package PrevMap with initial version 1.5.3
Package: PrevMap
Type: Package
Title: Geostatistical Modelling of Spatially Referenced Prevalence Data
Version: 1.5.3
Date: 2020-02-05
Author: Emanuele Giorgi, Peter J. Diggle
Maintainer: Emanuele Giorgi <e.giorgi@lancaster.ac.uk>
Imports: splancs, lme4, truncnorm, methods, numDeriv
Depends: maxLik, raster, pdist, Matrix
Description: Provides functions for both likelihood-based and Bayesian analysis of spatially referenced prevalence data. For a tutorial on the use of the R package, see Giorgi and Diggle (2017) <doi:10.18637/jss.v078.i08>.
Encoding: UTF-8
LazyData: true
License: GPL (>= 2)
Suggests: geoR, R.rsp, INLA, knitr, rmarkdown
Additional_repositories: https://inla.r-inla-download.org/R/testing/
RoxygenNote: 7.0.2
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2020-02-06 09:13:32 UTC; emanuele
Repository: CRAN
Date/Publication: 2020-02-06 10:30:09 UTC

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New package onemapsgapi with initial version 1.0.0
Package: onemapsgapi
Type: Package
Title: R Wrapper for the 'OneMap.Sg API'
Version: 1.0.0
Authors@R: person("Jolene", "Lim", email = "jyl2187@columbia.edu", role = c("aut", "cre"))
Maintainer: Jolene Lim <jyl2187@columbia.edu>
Description: An R wrapper for the 'OneMap.Sg' API <https://docs.onemap.sg/>. Functions help users query data from the API and return raw JSON data in "tidy" formats. Support is also available for users to retrieve data from multiple API calls and integrate results into single dataframes, without needing to clean and merge the data themselves. This package is best suited for users who would like to perform analyses with Singapore's spatial data without having to perform excessive data cleaning.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: rlang, httr, dplyr, purrr, stringr, tidyr, future, furrr
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown, sf, rgdal, sp
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-25 19:55:45 UTC; jolene
Author: Jolene Lim [aut, cre]
Repository: CRAN
Date/Publication: 2020-02-06 11:00:02 UTC

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Package msma updated to version 2.1 with previous version 2.0 dated 2019-09-01

Title: Multiblock Sparse Multivariable Analysis
Description: Several functions can be used to analyze multiblock multivariable data. If the input is a single matrix, then principal components analysis (PCA) is implemented. If the input is a list of matrices, then multiblock PCA is implemented. If the input is two matrices, for exploratory and objective variables, then partial least squares (PLS) analysis is implemented. If the input is two lists of matrices, for exploratory and objective variables, then multiblock PLS analysis is implemented. Additionally, if an extra outcome variable is specified, then a supervised version of the methods above is implemented. For each method, sparse modeling is also incorporated. Functions for selecting the number of components and regularized parameters are also provided.
Author: Atsushi Kawaguchi
Maintainer: Atsushi Kawaguchi <kawa_a24@yahoo.co.jp>

Diff between msma versions 2.0 dated 2019-09-01 and 2.1 dated 2020-02-06

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Package matahari updated to version 0.1.3 with previous version 0.1.2 dated 2019-12-10

Title: Spy on Your R Session
Description: Conveniently log everything you type into the R console. Logs are are stored as tidy data frames which can then be analyzed using 'tidyverse' style tools.
Author: Sean Kross [aut, cre] (<https://orcid.org/0000-0001-5215-0316>), Lucy D'Agostino McGowan [aut] (<https://orcid.org/0000-0001-7297-9359>), Jeff Leek [ldr] (<https://orcid.org/0000-0002-2873-2671>)
Maintainer: Sean Kross <sean@seankross.com>

Diff between matahari versions 0.1.2 dated 2019-12-10 and 0.1.3 dated 2020-02-06

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New package lcars with initial version 0.3.1
Package: lcars
Title: LCARS Aesthetic for Shiny
Version: 0.3.1
Authors@R: person("Matthew", "Leonawicz", email = "matt_leonawicz@esource.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9452-2771"))
Description: Provides Shiny widgets and theme that support a 'Library Computer Access/Retrieval System' (LCARS) aesthetic for Shiny apps. The package also includes functions for adding a minimal LCARS theme to static 'ggplot2' graphs. More details about LCARS can be found at <https://en.wikipedia.org/wiki/LCARS>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/leonawicz/lcars
BugReports: https://github.com/leonawicz/lcars/issues
Depends: R (>= 3.5.0)
Imports: grid, ggplot2, shiny, trekcolors
Suggests: testthat, knitr, rmarkdown, covr, png, ggrepel, showtext
VignetteBuilder: knitr
Language: en-US
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-25 01:40:35 UTC; Matt
Author: Matthew Leonawicz [aut, cre] (<https://orcid.org/0000-0001-9452-2771>)
Maintainer: Matthew Leonawicz <matt_leonawicz@esource.com>
Repository: CRAN
Date/Publication: 2020-02-06 10:50:02 UTC

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New package googleCloudRunner with initial version 0.1.1
Package: googleCloudRunner
Type: Package
Title: R Scripts in the Google Cloud via Cloud Run, Cloud Build and Cloud Scheduler
Version: 0.1.1
Authors@R: c(person("Mark", "Edmondson", email = "r@sunholo.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8434-3881")), person("Sunholo Ltd", role = "cph"))
Description: Tools to easily enable R scripts in the Google Cloud Platform. Utilise cloud services such as Cloud Run <https://cloud.run> for R over HTTP, Cloud Build <https://cloud.google.com/cloud-build/> for Continuous Delivery and Integration services and Cloud Scheduler <https://cloud.google.com/scheduler/> for scheduled scripts.
URL: https://code.markedmondson.me/googleCloudRunner
BugReports: https://github.com/MarkEdmondson1234/googleCloudRunner/issues
Depends: R (>= 3.3.0)
Imports: assertthat (>= 0.2.0), googleAuthR (>= 1.1.1), googleCloudStorageR (>= 0.5.1), httr (>= 1.4.1), jsonlite (>= 1.5), methods, openssl (>= 1.4.1), stats, utils, yaml (>= 2.2.0)
Suggests: knitr, miniUI, plumber, rmarkdown, shiny, testthat (>= 2.1.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-01-25 01:39:54 UTC; mark
Author: Mark Edmondson [aut, cre] (<https://orcid.org/0000-0002-8434-3881>), Sunholo Ltd [cph]
Maintainer: Mark Edmondson <r@sunholo.com>
Repository: CRAN
Date/Publication: 2020-02-06 10:50:06 UTC

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Package dint updated to version 2.1.3 with previous version 2.1.2 dated 2020-01-07

Title: A Toolkit for Year-Quarter, Year-Month and Year-Isoweek Dates
Description: S3 classes and methods to create and work with year-quarter, year-month and year-isoweek vectors. Basic arithmetic operations (such as adding and subtracting) are supported, as well as formatting and converting to and from standard R date types.
Author: Stefan Fleck [aut, cre] (<https://orcid.org/0000-0003-3344-9851>)
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>

Diff between dint versions 2.1.2 dated 2020-01-07 and 2.1.3 dated 2020-02-06

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New package coalitions with initial version 0.6.12
Package: coalitions
Type: Package
Title: Bayesian "Now-Cast" Estimation of Event Probabilities in Multi-Party Democracies
Version: 0.6.12
Authors@R: c( person("Andreas", "Bender", , "bender.at.R@gmail.com", role = c("aut", "cre"), comment=c(ORCID = "0000-0001-5628-8611")), person("Alexander", "Bauer", , "alexander.bauer@stat.uni-muenchen.de", role=c("aut"), comment=c(ORCID = "0000-0003-3495-5131")))
Maintainer: Andreas Bender <bender.at.R@gmail.com>
Description: An implementation of a Bayesian framework for the opinion poll based estimation of event probabilities in multi-party electoral systems (Bender and Bauer (2018) <doi:10.21105/joss.00606>).
Depends: R (>= 3.2.1)
Imports: checkmate, gtools, rvest, xml2, jsonlite, RCurl, rlang, magrittr, lubridate, stringr, tidyr (>= 1.0.0), purrr (> 0.2.2), dplyr (> 0.5.0), ggplot2
Suggests: testthat, covr, knitr, rmarkdown, pkgdown
Encoding: UTF-8
License: MIT + file LICENSE
URL: http://adibender.github.io/coalitions/
BugReports: https://github.com/adibender/coalitions/issues
RoxygenNote: 7.0.2
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2020-02-05 22:04:25 UTC; abhs
Author: Andreas Bender [aut, cre] (<https://orcid.org/0000-0001-5628-8611>), Alexander Bauer [aut] (<https://orcid.org/0000-0003-3495-5131>)
Repository: CRAN
Date/Publication: 2020-02-06 10:10:06 UTC

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New package ck37r with initial version 1.0.3
Package: ck37r
Title: Chris Kennedy's R Toolkit
Version: 1.0.3
Authors@R: person(given = "Chris", family = "Kennedy", email = "chrisken@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7444-2766"))
Description: Toolkit for statistical, machine learning, and targeted learning analyses. Functionality includes loading & auto-installing packages, standardizing datasets, creating missingness indicators, imputing missing values, creating multicore or multinode clusters, automatic SLURM integration, enhancing SuperLearner and TMLE with automatic parallelization, and many other SuperLearner analysis & plotting enhancements.
URL: https://github.com/ck37/ck37r
BugReports: https://github.com/ck37/ck37r/issues
Depends: R (>= 3.1.0)
Imports: caret, checkmate, crayon, cvAUC, doParallel, foreach, future.apply, ggplot2, h2o, methods, parallel, precrec, pryr, reader, RhpcBLASctl, ROCR, rpart.plot, stringr, SuperLearner, tmle, weights
Suggests: data.table, dplyr, glmnet, lintr, MASS, magrittr, mgcv, microbenchmark, mlbench, randomForest, RANN, slam, testthat, xgboost
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-02-06 06:38:00 UTC; chris
Author: Chris Kennedy [aut, cre] (<https://orcid.org/0000-0001-7444-2766>)
Maintainer: Chris Kennedy <chrisken@gmail.com>
Repository: CRAN
Date/Publication: 2020-02-06 10:50:11 UTC

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New package bda with initial version 14.1.4
Package: bda
Version: 14.1.4
Date: 2020-01-24
Title: Binned Data Analysis
Author: Bin Wang <bwang831@gmail.com>
Maintainer: Bin Wang <bwang831@gmail.com>
Depends: R (>= 2.10.0)
Description: Algorithms developed for binned data analysis, gene expression data analysis and measurement error models for ordinal data analysis.
License: Unlimited
NeedsCompilation: yes
Packaged: 2020-01-25 04:39:03 UTC; bwang
Repository: CRAN
Date/Publication: 2020-02-06 10:50:14 UTC

More information about bda at CRAN
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New package Bayesiangammareg with initial version 0.1.0
Package: Bayesiangammareg
Type: Package
Title: Bayesian Gamma Regression: Joint Mean and Shape Modeling
Version: 0.1.0
Date: 2020-01-24
Authors@R: c(person("Arturo", "Camargo Lozano" , email ="bacamargol@unal.edu.co", role = c("aut", "cre")), person("Edilberto", "Cepeda Cuervo", email ="ecepedac@unal.edu.co", role = "aut") )
Author: Arturo Camargo Lozano [aut, cre], Edilberto Cepeda Cuervo [aut]
Maintainer: Arturo Camargo Lozano <bacamargol@unal.edu.co>
Description: Adjust the Gamma regression models from a Bayesian perspective described by Cepeda and Urdinola (2012) <doi:10.1080/03610918.2011.600500>, modeling the parameters of mean and shape and using different link functions for the parameter associated to the mean. And calculates different adjustment statistics such as the Akaike information criterion and Bayesian information criterion.
Depends: R (>= 3.1.1), mvtnorm
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2020-01-25 01:32:05 UTC; ARTURO
Repository: CRAN
Date/Publication: 2020-02-06 10:50:17 UTC
URL: https://www.r-project.org

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Package vcfR updated to version 1.10.0 with previous version 1.9.0 dated 2020-01-10

Title: Manipulate and Visualize VCF Data
Description: Facilitates easy manipulation of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices of data. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file (*.vcf.gz). It also may be converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and familiar R software.
Author: Brian J. Knaus [cre, aut] (<https://orcid.org/0000-0003-1665-4343>), Niklaus J. Grunwald [aut] (<https://orcid.org/0000-0003-1656-7602>), Eric C. Anderson [ctb], David J. Winter [ctb], Zhian N. Kamvar [ctb] (<https://orcid.org/0000-0003-1458-7108>), Javier F. Tabima [ctb] (<https://orcid.org/0000-0002-3603-2691>)
Maintainer: Brian J. Knaus <briank.lists@gmail.com>

Diff between vcfR versions 1.9.0 dated 2020-01-10 and 1.10.0 dated 2020-02-06

 DESCRIPTION                    |    6 -
 MD5                            |   36 ++++-----
 R/chromR_functions.R           |    2 
 R/io_vcfR.R                    |    2 
 R/proc_chromR.R                |    4 -
 R/ranking.R                    |    2 
 R/summary_tables.R             |    2 
 R/vcfR_conversion.R            |    2 
 R/vcfR_to_tidy_functions.R     |  153 +++++++++++++++++++++++++----------------
 R/windowing.R                  |    2 
 inst/doc/converting_data.R     |   26 +++---
 inst/doc/converting_data.html  |   14 +--
 inst/doc/intro_to_vcfR.R       |   20 ++---
 inst/doc/intro_to_vcfR.html    |   26 +++---
 inst/doc/vcf_data.R            |   16 ++--
 inst/doc/vcf_data.html         |   94 +++++++++++--------------
 inst/doc/workflow.html         |   12 +--
 man/proc_chromR.Rd             |    2 
 tests/testthat/test_vcfRtidy.R |    3 
 19 files changed, 223 insertions(+), 201 deletions(-)

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Package umx updated to version 3.0.6 with previous version 3.0.5 dated 2019-12-06

Title: Structural Equation and Twin Modeling in R
Description: Quickly create, run, and report structural equation and twin models. See '?umx' for help, and umx_open_CRAN_page("umx") for NEWS.
Author: Timothy C. Bates [aut, cre] (<https://orcid.org/0000-0002-1153-9007>), Joshua N. Pritikin [ctb], Michael C. Neale [ctb], Hermine Maes [ctb]
Maintainer: Timothy C. Bates <timothy.c.bates@gmail.com>

Diff between umx versions 3.0.5 dated 2019-12-06 and 3.0.6 dated 2020-02-06

 umx-3.0.5/umx/man/umx_nice_data.Rd                      |only
 umx-3.0.5/umx/man/umx_pb_note.Rd                        |only
 umx-3.0.6/umx/DESCRIPTION                               |   27 -
 umx-3.0.6/umx/MD5                                       |  407 ++++++++--------
 umx-3.0.6/umx/NAMESPACE                                 |    9 
 umx-3.0.6/umx/NEWS.md                                   |   17 
 umx-3.0.6/umx/R/build_run_modify.R                      |  161 +++---
 umx-3.0.6/umx/R/fit_and_reporting.R                     |   30 -
 umx-3.0.6/umx/R/lavanify2ram.R                          |  104 +++-
 umx-3.0.6/umx/R/misc_and_utility.R                      |  176 +++---
 umx-3.0.6/umx/R/tmx.R                                   |    3 
 umx-3.0.6/umx/R/umxDoC.R                                |only
 umx-3.0.6/umx/R/umxIPnew.R                              |    2 
 umx-3.0.6/umx/R/umxPower.R                              |   10 
 umx-3.0.6/umx/R/umx_build_polychoricMatrix3.R           |   27 -
 umx-3.0.6/umx/R/umx_build_umxACEcov_fixed.R             |   10 
 umx-3.0.6/umx/R/umx_build_umxACEv.R                     |    4 
 umx-3.0.6/umx/R/umx_build_umxGxEbiv.R                   |    8 
 umx-3.0.6/umx/R/umx_build_umxSexLim.R                   |    7 
 umx-3.0.6/umx/R/umx_build_umxSimplex.R                  |    7 
 umx-3.0.6/umx/R/umx_nice_data.R                         |   22 
 umx-3.0.6/umx/R/xmu.R                                   |   32 -
 umx-3.0.6/umx/R/xmu_make_top_twin_models.R              |   67 +-
 umx-3.0.6/umx/inst/WORDLIST                             |    8 
 umx-3.0.6/umx/man/FishersMethod.Rd                      |   19 
 umx-3.0.6/umx/man/SE_from_p.Rd                          |    9 
 umx-3.0.6/umx/man/figures/DoC.pdf                       |only
 umx-3.0.6/umx/man/figures/DoC.png                       |only
 umx-3.0.6/umx/man/figures/umx_help_figures.graffle      |binary
 umx-3.0.6/umx/man/install.OpenMx.Rd                     |   14 
 umx-3.0.6/umx/man/loadings.MxModel.Rd                   |    9 
 umx-3.0.6/umx/man/oddsratio.Rd                          |    9 
 umx-3.0.6/umx/man/power.ACE.test.Rd                     |   15 
 umx-3.0.6/umx/man/qm.Rd                                 |   14 
 umx-3.0.6/umx/man/reliability.Rd                        |    9 
 umx-3.0.6/umx/man/tmx_is.identified.Rd                  |   13 
 umx-3.0.6/umx/man/tmx_show.Rd                           |   15 
 umx-3.0.6/umx/man/umx.Rd                                |   65 +-
 umx-3.0.6/umx/man/umxACE.Rd                             |   31 -
 umx-3.0.6/umx/man/umxACE_cov_fixed.Rd                   |    9 
 umx-3.0.6/umx/man/umxACEcov.Rd                          |   10 
 umx-3.0.6/umx/man/umxACEv.Rd                            |   10 
 umx-3.0.6/umx/man/umxAPA.Rd                             |   10 
 umx-3.0.6/umx/man/umxBrownie.Rd                         |   14 
 umx-3.0.6/umx/man/umxCP.Rd                              |   10 
 umx-3.0.6/umx/man/umxConfint.Rd                         |    2 
 umx-3.0.6/umx/man/umxCov2cor.Rd                         |    9 
 umx-3.0.6/umx/man/umxDiagnose.Rd                        |    3 
 umx-3.0.6/umx/man/umxDoC.Rd                             |only
 umx-3.0.6/umx/man/umxEquate.Rd                          |    4 
 umx-3.0.6/umx/man/umxFactor.Rd                          |   30 -
 umx-3.0.6/umx/man/umxFactorScores.Rd                    |   12 
 umx-3.0.6/umx/man/umxGetParameters.Rd                   |   12 
 umx-3.0.6/umx/man/umxGxE.Rd                             |   22 
 umx-3.0.6/umx/man/umxGxE_window.Rd                      |    4 
 umx-3.0.6/umx/man/umxGxEbiv.Rd                          |    8 
 umx-3.0.6/umx/man/umxHetCor.Rd                          |   13 
 umx-3.0.6/umx/man/umxIP.Rd                              |    6 
 umx-3.0.6/umx/man/umxJiggle.Rd                          |    5 
 umx-3.0.6/umx/man/umxLabel.Rd                           |    5 
 umx-3.0.6/umx/man/umxLav2RAM.Rd                         |   18 
 umx-3.0.6/umx/man/umxModel.Rd                           |   12 
 umx-3.0.6/umx/man/umxModify.Rd                          |    4 
 umx-3.0.6/umx/man/umxParameters.Rd                      |   14 
 umx-3.0.6/umx/man/umxPlotCP.Rd                          |    4 
 umx-3.0.6/umx/man/umxPlotDoC.Rd                         |only
 umx-3.0.6/umx/man/umxPower.Rd                           |    3 
 umx-3.0.6/umx/man/umxRAM.Rd                             |    6 
 umx-3.0.6/umx/man/umxRAM2Lav.Rd                         |only
 umx-3.0.6/umx/man/umxReduce.Rd                          |   15 
 umx-3.0.6/umx/man/umxReduceACE.Rd                       |    4 
 umx-3.0.6/umx/man/umxReduceGxE.Rd                       |    8 
 umx-3.0.6/umx/man/umxRotate.MxModelCP.Rd                |    8 
 umx-3.0.6/umx/man/umxSexLim.Rd                          |    9 
 umx-3.0.6/umx/man/umxSimplex.Rd                         |    9 
 umx-3.0.6/umx/man/umxSummarizeTwinData.Rd               |    3 
 umx-3.0.6/umx/man/umxSummaryACE.Rd                      |    3 
 umx-3.0.6/umx/man/umxSummaryACEcov.Rd                   |    3 
 umx-3.0.6/umx/man/umxSummaryACEv.Rd                     |    3 
 umx-3.0.6/umx/man/umxSummaryCP.Rd                       |    3 
 umx-3.0.6/umx/man/umxSummaryDoC.Rd                      |only
 umx-3.0.6/umx/man/umxSummaryGxE.Rd                      |    3 
 umx-3.0.6/umx/man/umxSummaryGxEbiv.Rd                   |    3 
 umx-3.0.6/umx/man/umxSummaryIP.Rd                       |    3 
 umx-3.0.6/umx/man/umxSummarySexLim.Rd                   |    3 
 umx-3.0.6/umx/man/umxSummarySimplex.Rd                  |    3 
 umx-3.0.6/umx/man/umxSuperModel.Rd                      |    4 
 umx-3.0.6/umx/man/umxThresholdMatrix.Rd                 |    4 
 umx-3.0.6/umx/man/umxValues.Rd                          |    5 
 umx-3.0.6/umx/man/umxVersion.Rd                         |   12 
 umx-3.0.6/umx/man/umxWeightedAIC.Rd                     |   19 
 umx-3.0.6/umx/man/umx_APA_pval.Rd                       |   69 ++
 umx-3.0.6/umx/man/umx_aggregate.Rd                      |   11 
 umx-3.0.6/umx/man/umx_apply.Rd                          |    9 
 umx-3.0.6/umx/man/umx_array_shift.Rd                    |   12 
 umx-3.0.6/umx/man/umx_as_numeric.Rd                     |    4 
 umx-3.0.6/umx/man/umx_cont_2_quantiles.Rd               |   30 -
 umx-3.0.6/umx/man/umx_cor.Rd                            |   17 
 umx-3.0.6/umx/man/umx_explode.Rd                        |    3 
 umx-3.0.6/umx/man/umx_explode_twin_names.Rd             |    3 
 umx-3.0.6/umx/man/umx_find_object.Rd                    |   14 
 umx-3.0.6/umx/man/umx_fun_mean_sd.Rd                    |   69 ++
 umx-3.0.6/umx/man/umx_get_bracket_addresses.Rd          |   62 ++
 umx-3.0.6/umx/man/umx_get_checkpoint.Rd                 |    3 
 umx-3.0.6/umx/man/umx_get_options.Rd                    |    3 
 umx-3.0.6/umx/man/umx_grep.Rd                           |    3 
 umx-3.0.6/umx/man/umx_is_cov.Rd                         |    3 
 umx-3.0.6/umx/man/umx_long2wide.Rd                      |   10 
 umx-3.0.6/umx/man/umx_lower2full.Rd                     |    4 
 umx-3.0.6/umx/man/umx_make.Rd                           |   70 ++
 umx-3.0.6/umx/man/umx_make_MR_data.Rd                   |    4 
 umx-3.0.6/umx/man/umx_make_TwinData.Rd                  |    6 
 umx-3.0.6/umx/man/umx_make_fake_data.Rd                 |    4 
 umx-3.0.6/umx/man/umx_make_raw_from_cov.Rd              |    4 
 umx-3.0.6/umx/man/umx_make_twin_data_nice.Rd            |only
 umx-3.0.6/umx/man/umx_means.Rd                          |    9 
 umx-3.0.6/umx/man/umx_msg.Rd                            |   10 
 umx-3.0.6/umx/man/umx_names.Rd                          |   16 
 umx-3.0.6/umx/man/umx_object_as_str.Rd                  |    3 
 umx-3.0.6/umx/man/umx_open_CRAN_page.Rd                 |   12 
 umx-3.0.6/umx/man/umx_pad.Rd                            |   11 
 umx-3.0.6/umx/man/umx_paste_names.Rd                    |    2 
 umx-3.0.6/umx/man/umx_polychoric.Rd                     |    6 
 umx-3.0.6/umx/man/umx_polypairwise.Rd                   |    6 
 umx-3.0.6/umx/man/umx_polytriowise.Rd                   |    6 
 umx-3.0.6/umx/man/umx_print.Rd                          |   24 
 umx-3.0.6/umx/man/umx_r_test.Rd                         |    9 
 umx-3.0.6/umx/man/umx_read_lower.Rd                     |    4 
 umx-3.0.6/umx/man/umx_rename.Rd                         |    4 
 umx-3.0.6/umx/man/umx_reorder.Rd                        |    4 
 umx-3.0.6/umx/man/umx_residualize.Rd                    |    2 
 umx-3.0.6/umx/man/umx_rot.Rd                            |    3 
 umx-3.0.6/umx/man/umx_round.Rd                          |    9 
 umx-3.0.6/umx/man/umx_scale.Rd                          |    9 
 umx-3.0.6/umx/man/umx_scale_wide_twin_data.Rd           |    2 
 umx-3.0.6/umx/man/umx_score_scale.Rd                    |   54 +-
 umx-3.0.6/umx/man/umx_select_valid.Rd                   |    4 
 umx-3.0.6/umx/man/umx_set_auto_plot.Rd                  |    3 
 umx-3.0.6/umx/man/umx_set_auto_run.Rd                   |    3 
 umx-3.0.6/umx/man/umx_set_checkpoint.Rd                 |    3 
 umx-3.0.6/umx/man/umx_set_condensed_slots.Rd            |    3 
 umx-3.0.6/umx/man/umx_set_cores.Rd                      |    3 
 umx-3.0.6/umx/man/umx_set_data_variance_check.Rd        |    3 
 umx-3.0.6/umx/man/umx_set_mvn_optimization_options.Rd   |    3 
 umx-3.0.6/umx/man/umx_set_optimizer.Rd                  |    3 
 umx-3.0.6/umx/man/umx_set_plot_file_suffix.Rd           |    3 
 umx-3.0.6/umx/man/umx_set_plot_format.Rd                |    3 
 umx-3.0.6/umx/man/umx_set_separator.Rd                  |    3 
 umx-3.0.6/umx/man/umx_set_silent.Rd                     |    3 
 umx-3.0.6/umx/man/umx_set_table_format.Rd               |    3 
 umx-3.0.6/umx/man/umx_stack.Rd                          |    4 
 umx-3.0.6/umx/man/umx_standardize.Rd                    |   10 
 umx-3.0.6/umx/man/umx_string_to_algebra.Rd              |   62 ++
 umx-3.0.6/umx/man/umx_time.Rd                           |   11 
 umx-3.0.6/umx/man/umx_trim.Rd                           |    2 
 umx-3.0.6/umx/man/umx_var.Rd                            |    9 
 umx-3.0.6/umx/man/umx_wide2long.Rd                      |    7 
 umx-3.0.6/umx/man/umx_write_to_clipboard.Rd             |    8 
 umx-3.0.6/umx/man/xmuHasSquareBrackets.Rd               |   10 
 umx-3.0.6/umx/man/xmuLabel_MATRIX_Model.Rd              |   10 
 umx-3.0.6/umx/man/xmuLabel_Matrix.Rd                    |   10 
 umx-3.0.6/umx/man/xmuLabel_RAM_Model.Rd                 |   10 
 umx-3.0.6/umx/man/xmuMI.Rd                              |   10 
 umx-3.0.6/umx/man/xmuMakeDeviationThresholdsMatrices.Rd |   10 
 umx-3.0.6/umx/man/xmuMakeOneHeadedPathsFromPathList.Rd  |   10 
 umx-3.0.6/umx/man/xmuMakeTwoHeadedPathsFromPathList.Rd  |   10 
 umx-3.0.6/umx/man/xmuMaxLevels.Rd                       |   10 
 umx-3.0.6/umx/man/xmuMinLevels.Rd                       |   10 
 umx-3.0.6/umx/man/xmuPropagateLabels.Rd                 |   10 
 umx-3.0.6/umx/man/xmuRAM2Ordinal.Rd                     |   62 ++
 umx-3.0.6/umx/man/xmu_CI_merge.Rd                       |   10 
 umx-3.0.6/umx/man/xmu_CI_stash.Rd                       |   10 
 umx-3.0.6/umx/man/xmu_DF_to_mxData_TypeCov.Rd           |   10 
 umx-3.0.6/umx/man/xmu_PadAndPruneForDefVars.Rd          |   10 
 umx-3.0.6/umx/man/xmu_assemble_twin_supermodel.Rd       |   10 
 umx-3.0.6/umx/man/xmu_cell_is_on.Rd                     |   70 ++
 umx-3.0.6/umx/man/xmu_check_levels_identical.Rd         |   10 
 umx-3.0.6/umx/man/xmu_check_needs_means.Rd              |   10 
 umx-3.0.6/umx/man/xmu_check_variance.Rd                 |   10 
 umx-3.0.6/umx/man/xmu_clean_label.Rd                    |   10 
 umx-3.0.6/umx/man/xmu_data_swap_a_block.Rd              |    4 
 umx-3.0.6/umx/man/xmu_describe_data_WLS.Rd              |   10 
 umx-3.0.6/umx/man/xmu_dot_make_paths.Rd                 |   10 
 umx-3.0.6/umx/man/xmu_dot_make_residuals.Rd             |   10 
 umx-3.0.6/umx/man/xmu_dot_maker.Rd                      |   10 
 umx-3.0.6/umx/man/xmu_dot_move_ranks.Rd                 |   10 
 umx-3.0.6/umx/man/xmu_dot_rank_str.Rd                   |   10 
 umx-3.0.6/umx/man/xmu_get_CI.Rd                         |   10 
 umx-3.0.6/umx/man/xmu_lavaan_process_group.Rd           |   10 
 umx-3.0.6/umx/man/xmu_make_bin_cont_pair_data.Rd        |   10 
 umx-3.0.6/umx/man/xmu_make_mxData.Rd                    |   10 
 umx-3.0.6/umx/man/xmu_make_top_twin.Rd                  |   10 
 umx-3.0.6/umx/man/xmu_match.arg.Rd                      |   73 ++
 umx-3.0.6/umx/man/xmu_name_from_lavaan_str.Rd           |   10 
 umx-3.0.6/umx/man/xmu_safe_run_summary.Rd               |   18 
 umx-3.0.6/umx/man/xmu_set_sep_from_suffix.Rd            |   10 
 umx-3.0.6/umx/man/xmu_show_fit_or_comparison.Rd         |   10 
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Package nlme updated to version 3.1-144 with previous version 3.1-143 dated 2019-12-10

Title: Linear and Nonlinear Mixed Effects Models
Description: Fit and compare Gaussian linear and nonlinear mixed-effects models.
Author: José Pinheiro [aut] (S version), Douglas Bates [aut] (up to 2007), Saikat DebRoy [ctb] (up to 2002), Deepayan Sarkar [ctb] (up to 2005), EISPACK authors [ctb] (src/rs.f), Siem Heisterkamp [ctb] (Author fixed sigma), Bert Van Willigen [ctb] (Programmer fixed sigma), R-core [aut, cre]
Maintainer: R-core <R-core@R-project.org>

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Package LaplacesDemon updated to version 16.1.4 with previous version 16.1.1 dated 2018-06-30

Title: Complete Environment for Bayesian Inference
Description: Provides a complete environment for Bayesian inference using a variety of different samplers (see ?LaplacesDemon for an overview). The README describes the history of the package development process.
Author: Byron Hall [aut], Martina Hall [aut], Statisticat, LLC [aut], Eric Brown [ctb], Richard Hermanson [ctb], Emmanuel Charpentier [ctb], Daniel Heck [ctb], Stephane Laurent [ctb], Quentin F. Gronau [ctb], Henrik Singmann [cre]
Maintainer: Henrik Singmann <singmann+LaplacesDemon@gmail.com>

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Package hypergate updated to version 0.8.3 with previous version 0.8.1 dated 2019-04-17

Title: Machine Learning of Hyperrectangular Gating Strategies for High-Dimensional Cytometry
Description: Given a high-dimensional dataset that typically represents a cytometry dataset, and a subset of the datapoints, this algorithm outputs an hyperrectangle so that datapoints within the hyperrectangle best correspond to the specified subset. In essence, this allows the conversion of clustering algorithms' outputs to gating strategies outputs.
Author: Etienne Becht [cre, aut], Samuel Granjeaud [ctb]
Maintainer: Etienne Becht <etienne.becht@protonmail.com>

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Package errorlocate updated to version 0.3.0 with previous version 0.2.0 dated 2019-07-01

Title: Locate Errors with Validation Rules
Description: Errors in data can be located and removed using validation rules from package 'validate'.
Author: Edwin de Jonge [aut, cre] (<https://orcid.org/0000-0002-6580-4718>), Mark van der Loo [aut]
Maintainer: Edwin de Jonge <edwindjonge@gmail.com>

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Package emba updated to version 0.1.2 with previous version 0.1.1 dated 2019-10-21

Title: Ensemble Boolean Model Biomarker Analysis
Description: Analysis and visualization of an ensemble of boolean models for biomarker discovery in cancer cell networks. The package allows to easily import the data results of a software pipeline that predicts synergistic drug combinations in cancer cell lines, developed by the DrugLogics research group in NTNU. It has generic functions that can be used to split a boolean model dataset to model groups with regards to the models predictive performance (number of true positive predictions or Matthews correlation coefficient score) or synergy prediction based on a given set of observed synergies and find the average activity difference per network node between all group pairs. Thus, given user-specific thresholds, important nodes (biomarkers) can be accessed in the sense that they make the models predict specific synergies (synergy biomarkers) or have better performance in general (performance biomarkers). Lastly, if the boolean models have a specific equation form and differ only in their link operator, link operator biomarkers can also be assessed.
Author: John Zobolas [aut, cph, cre] (<https://orcid.org/0000-0002-3609-8674>)
Maintainer: John Zobolas <bblodfon@gmail.com>

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Package VIMGUI (with last version 0.10.0) was removed from CRAN

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

2016-10-18 0.10.0
2013-10-11 0.9.0

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Package PKconverter updated to version 1.5 with previous version 1.3 dated 2018-12-03

Title: The Parameter Converter of the Pharmacokinetic Models
Description: Pharmacokinetics is the study of drug absorption, distribution, metabolism, and excretion. The pharmacokinetics model explains that how the drug concentration change as the drug moves through the different compartments of the body. For pharmacokinetic modeling and analysis, it is essential to understand the basic pharmacokinetic parameters. All parameters are considered, but only some of parameters are used in the model. Therefore, we need to convert the estimated parameters to the other parameters after fitting the specific pharmacokinetic model. This package is developed to help this converting work. For more detailed explanation of pharmacokinetic parameters, see "Gabrielsson and Weiner" (2007), "ISBN-10: 9197651001"; "Benet and Zia-Amirhosseini" (1995) <DOI: 10.1177/019262339502300203>; "Mould and Upton" (2012) <DOI: 10.1038/psp.2012.4>; "Mould and Upton" (2013) <DOI: 10.1038/psp.2013.14>.
Author: Eun-Kyung Lee, Hye-sun Cho
Maintainer: Eun-Kyung Lee <lee.eunk@gmail.com>

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Package spBayes updated to version 0.4-3 with previous version 0.4-2 dated 2019-03-07

Title: Univariate and Multivariate Spatial-Temporal Modeling
Description: Fits univariate and multivariate spatio-temporal random effects models for point-referenced data using Markov chain Monte Carlo (MCMC). Details are given in Finley, Banerjee, and Gelfand (2015) <doi:10.18637/jss.v063.i13> and Finley, Banerjee, and Cook (2014) <doi:10.1111/2041-210X.12189>.
Author: Andrew Finley [aut, cre], Sudipto Banerjee [aut]
Maintainer: Andrew Finley <finleya@msu.edu>

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Package shazam updated to version 0.2.3 with previous version 0.2.2 dated 2019-12-16

Title: Immunoglobulin Somatic Hypermutation Analysis
Description: Provides a computational framework for analyzing mutations in immunoglobulin (Ig) sequences. Includes methods for Bayesian estimation of antigen-driven selection pressure, mutational load quantification, building of somatic hypermutation (SHM) models, and model-dependent distance calculations. Also includes empirically derived models of SHM for both mice and humans. Citations: Gupta and Vander Heiden, et al (2015) <doi:10.1093/bioinformatics/btv359>, Yaari, et al (2012) <doi:10.1093/nar/gks457>, Yaari, et al (2013) <doi:10.3389/fimmu.2013.00358>, Cui, et al (2016) <doi:10.4049/jimmunol.1502263>.
Author: Mohamed Uduman [aut], Gur Yaari [aut], Namita Gupta [aut], Jason Vander Heiden [aut, cre], Ang Cui [ctb], Susanna Marquez [ctb], Julian Zhou [ctb], Nima Nouri [ctb], Steven Kleinstein [aut, cph]
Maintainer: Jason Vander Heiden <jason.vanderheiden@yale.edu>

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Package RandomFields updated to version 3.3.8 with previous version 3.3.7 dated 2019-12-12

Title: Simulation and Analysis of Random Fields
Description: Methods for the inference on and the simulation of Gaussian fields are provided, as well as methods for the simulation of extreme value random fields. Main geostatistical parts are based on the books by Christian Lantuejoul <doi:10.1007/978-3-662-04808-5>, Jean-Paul Chiles and Pierre Delfiner <doi:10.1002/9781118136188> and Noel A. Cressie <doi:10.1002/9781119115151>. For the extreme value random fields see Oesting, Schlather, Schillings (2019) <doi.org/10.1002/sta4.228> and Schlather (2002) <doi.org/10.1023/A:1020977924878>.
Author: Martin Schlather [aut, cre], Alexander Malinowski [aut], Marco Oesting [aut], Daphne Boecker [aut], Kirstin Strokorb [aut], Sebastian Engelke [aut], Johannes Martini [aut], Felix Ballani [aut], Olga Moreva [aut], Jonas Auel[ctr], Peter Menck [ctr], Sebastian Gross [ctr], Ulrike Ober [ctb], Paulo Ribeiro [ctb], Brian D. Ripley [ctb], Richard Singleton [ctb], Ben Pfaff [ctb], R Core Team [ctb]
Maintainer: Martin Schlather <schlather@math.uni-mannheim.de>

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Package mvSLOUCH updated to version 2.3 with previous version 2.2 dated 2020-01-12

Title: Multivariate Stochastic Linear Ornstein-Uhlenbeck Models for Phylogenetic Comparative Hypotheses
Description: Fits multivariate Ornstein-Uhlenbeck types of models to continues trait data from species related by a common evolutionary history. See K. Bartoszek, J, Pienaar, P. Mostad, S. Andersson, T. F.Hansen (2012) <doi:10.1016/j.jtbi.2012.08.005>. The suggested PCMBaseCpp package (which significantly speeds up the likelihood calculations) can be obtained from <https://github.com/venelin/PCMBaseCpp/>.
Author: Krzysztof Bartoszek <krzbar@protonmail.ch>
Maintainer: Krzysztof Bartoszek <krzbar@protonmail.ch>

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Package longmemo updated to version 1.1-2 with previous version 1.1-1 dated 2018-09-14

Title: Statistics for Long-Memory Processes (Book Jan Beran), and Related Functionality
Description: Datasets and Functionality from 'Jan Beran' (1994). Statistics for Long-Memory Processes; Chapman & Hall. Estimation of Hurst (and more) parameters for fractional Gaussian noise, 'fARIMA' and 'FEXP' models.
Author: S scripts originally by Jan Beran <jan.beran@uni-konstanz.de>; Datasets via Brandon Whitcher <brandon@stat.washington.edu>. Toplevel R functions and much more by Martin Maechler.
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

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Package copula updated to version 0.999-20 with previous version 0.999-19.1 dated 2019-04-22

Title: Multivariate Dependence with Copulas
Description: Classes (S4) of commonly used elliptical, Archimedean, extreme-value and other copula families, as well as their rotations, mixtures and asymmetrizations. Nested Archimedean copulas, related tools and special functions. Methods for density, distribution, random number generation, bivariate dependence measures, Rosenblatt transform, Kendall distribution function, perspective and contour plots. Fitting of copula models with potentially partly fixed parameters, including standard errors. Serial independence tests, copula specification tests (independence, exchangeability, radial symmetry, extreme-value dependence, goodness-of-fit) and model selection based on cross-validation. Empirical copula, smoothed versions, and non-parametric estimators of the Pickands dependence function.
Author: Marius Hofert [aut] (<https://orcid.org/0000-0001-8009-4665>), Ivan Kojadinovic [aut] (<https://orcid.org/0000-0002-2903-1543>), Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>), Jun Yan [aut] (<https://orcid.org/0000-0003-4401-7296>), Johanna G. Nešlehová [ctb] (evTestK(), <https://orcid.org/0000-0001-9634-4796>)
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

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Package analogue updated to version 0.17-4 with previous version 0.17-3 dated 2019-05-11

Title: Analogue and Weighted Averaging Methods for Palaeoecology
Description: Fits Modern Analogue Technique and Weighted Averaging transfer function models for prediction of environmental data from species data, and related methods used in palaeoecology.
Author: Gavin L. Simpson [aut, cre] (<https://orcid.org/0000-0002-9084-8413>), Jari Oksanen [aut]
Maintainer: Gavin L. Simpson <ucfagls@gmail.com>

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Package AER updated to version 1.2-9 with previous version 1.2-8 dated 2019-11-08

Title: Applied Econometrics with R
Description: Functions, data sets, examples, demos, and vignettes for the book Christian Kleiber and Achim Zeileis (2008), Applied Econometrics with R, Springer-Verlag, New York. ISBN 978-0-387-77316-2. (See the vignette "AER" for a package overview.)
Author: Christian Kleiber [aut] (<https://orcid.org/0000-0002-6781-4733>), Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>)
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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Package rorcid updated to version 0.6.4 with previous version 0.6.0 dated 2020-01-28

Title: Interface to the 'Orcid.org' API
Description: Client for the 'Orcid.org' API (<https://orcid.org/>). Functions included for searching for people, searching by 'DOI', and searching by 'Orcid' 'ID'.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), rOpenSci [fnd] (https://ropensci.org/)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package rDEA updated to version 1.2-6 with previous version 1.2-5 dated 2016-11-25

Title: Robust Data Envelopment Analysis (DEA) for R
Description: Data Envelopment Analysis for R, estimating robust DEA scores without and with environmental variables and doing returns-to-scale tests.
Author: Jaak Simm [aut, cre], Galina Besstremyannaya [aut]
Maintainer: Jaak Simm <jaak.simm@gmail.com>

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Package NetworkChange updated to version 0.6 with previous version 0.5 dated 2019-05-08

Title: Bayesian Package for Network Changepoint Analysis
Description: Network changepoint analysis for undirected network data. The package implements a hidden Markov network change point model (Park and Sohn 2019). Functions for break number detection using the approximate marginal likelihood and WAIC are also provided.
Author: Jong Hee Park [aut,cre], Yunkyu Sohn [aut]
Maintainer: Jong Hee Park <jongheepark@snu.ac.kr>

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Package l0ara updated to version 0.1.6 with previous version 0.1.5 dated 2017-07-23

Title: Sparse Generalized Linear Model with L0 Approximation for Feature Selection
Description: An efficient procedure for feature selection for generalized linear models with L0 penalty, including linear, logistic, Poisson, gamma, inverse Gaussian regression. Adaptive ridge algorithms are used to fit the models.
Author: Wenchuan Guo, Shujie Ma, Zhenqiu Liu
Maintainer: Wenchuan Guo <wguo007@ucr.edu>

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Package junr (with last version 0.1.3) was removed from CRAN

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

2017-12-11 0.1.3
2017-08-09 0.1.2
2016-05-13 0.1.1
2016-03-28 0.1.0

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