Fri, 08 Mar 2019

Package knitr updated to version 1.22 with previous version 1.21 dated 2018-12-10

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], Ben Baumer [ctb], Brian Diggs [ctb], Brian Zhang [ctb], Cassio Pereira [ctb], Christophe Dervieux [ctb], David Hugh-Jones [ctb], David Robinson [ctb], Donald Arseneau [ctb, cph] (the framed package at inst/misc/framed.sty), 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], Martin Modrák [ctb], Michael Chirico [ctb], Michael Friendly [ctb], Michal Bojanowski [ctb], Michel Kuhlmann [ctb], Nacho Caballero [ctb], Nick Salkowski [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 aweek updated to version 0.2.0 with previous version 0.1.0 dated 2019-03-06

Title: Convert Dates to Arbitrary Week Definitions
Description: Which day a week starts depends heavily on the either the local or professional context. This package is designed to be a lightweight solution to easily switching between week-based date definitions.
Author: Zhian N. Kamvar [aut, cre]
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>

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Package TestDataImputation updated to version 1.1 with previous version 1.0 dated 2016-08-11

Title: Missing Item Responses Imputation for Test and Assessment Data
Description: Functions for imputing missing item responses for dichotomous and polytomous test and assessment data. This package enables missing imputation methods that are suitable for test and assessment data, including: listwise (LW) deletion, treating as incorrect (IN), person mean imputation (PM), item mean imputation (IM), two-way imputation (TW), logistic regression imputation (LR), and EM imputation.
Author: Shenghai Dai [aut, cre], Xiaolin Wang [aut], Dubravka Svetina [aut]
Maintainer: Shenghai Dai <s.dai@wsu.edu>

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Package rpf updated to version 0.60 with previous version 0.59 dated 2018-05-07

Title: Response Probability Functions
Description: The purpose of this package is to factor out logic and math common to Item Factor Analysis fitting, diagnostics, and analysis. It is envisioned as core support code suitable for more specialized IRT packages to build upon. Complete access to optimized C functions are made available with R_RegisterCCallable().
Author: Joshua Pritikin [cre, aut], Jonathan Weeks [ctb], Li Cai [ctb], Carrie Houts [ctb], Phil Chalmers [ctb], Michael D. Hunter [ctb], Carl F. Falk [ctb]
Maintainer: Joshua Pritikin <jpritikin@pobox.com>

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Package ipumsr updated to version 0.4.0 with previous version 0.3.0 dated 2018-09-27

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

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Package chngpt updated to version 2019.3-8 with previous version 2019.3-6 dated 2019-03-07

Title: Estimation and Hypothesis Testing for Threshold Regression
Description: Threshold regression models are also called two-phase regression, broken-stick regression, split-point regression, structural change models, and regression kink models. Methods for both continuous and discontinuous threshold models are included, but the support for the former is much greater. This package is described in Fong, Huang, Gilbert and Permar (2017) chngpt: threshold regression model estimation and inference, BMC Bioinformatics, in press, <DOI:10.1186/s12859-017-1863-x>.
Author: Youyi Fong [cre], Tao Yang [aut], Zonglin He [aut], Adam Elder [aut]
Maintainer: Youyi Fong <youyifong@gmail.com>

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Package robustrank updated to version 2019.3-7 with previous version 2018.10-1 dated 2018-09-20

Title: Robust Rank-Based Tests
Description: Implements two-sample tests for paired data with missing values (Fong, Huang, Lemos and McElrath 2018, Biostatics, <doi:10.1093/biostatistics/kxx039>) and modified Wilcoxon-Mann-Whitney two sample location test, also known as the Fligner-Policello test.
Author: Youyi Fong <youyifong@gmail.com>
Maintainer: Youyi Fong <youyifong@gmail.com>

Diff between robustrank versions 2018.10-1 dated 2018-09-20 and 2019.3-7 dated 2019-03-08

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Package findpython updated to version 1.0.5 with previous version 1.0.4 dated 2018-11-29

Title: Functions to Find an Acceptable Python Binary
Description: Package designed to find an acceptable python binary.
Author: Trevor L Davis [aut, cre], Paul Gilbert [aut]
Maintainer: Trevor L Davis <trevor.l.davis@gmail.com>

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Package codyn updated to version 2.0.1 with previous version 2.0.0 dated 2018-06-12

Title: Community Dynamics Metrics
Description: Univariate and multivariate temporal and spatial diversity indices, rank abundance curves, and community stability measures. The functions implement measures that are either explicitly temporal and include the option to calculate them over multiple replicates, or spatial and include the option to calculate them over multiple time points. Functions fall into five categories: static diversity indices, temporal diversity indices, spatial diversity indices, rank abundance curves, and community stability measures. The diversity indices are temporal and spatial analogs to traditional diversity indices. Specifically, the package includes functions to calculate community richness, evenness and diversity at a given point in space and time. In addition, it contains functions to calculate species turnover, mean rank shifts, and lags in community similarity between two time points.
Author: Lauren Hallett [aut], Meghan L. Avolio [aut], Ian T. Carroll [aut], Sydney K. Jones [aut], A. Andrew M. MacDonald [aut], Dan F. B. Flynn [aut], Peter Slaughter [aut], Julie Ripplinger [aut], Scott L. Collins [aut], Corinna Gries [aut], Matthew B. Jones [aut, cre]
Maintainer: Matthew B. Jones <jones@nceas.ucsb.edu>

Diff between codyn versions 2.0.0 dated 2018-06-12 and 2.0.1 dated 2019-03-08

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Package argparse updated to version 2.0.1 with previous version 2.0.0 dated 2018-11-30

Title: Command Line Optional and Positional Argument Parser
Description: A command line parser to be used with Rscript to write "#!" shebang scripts that gracefully accept positional and optional arguments and automatically generate usage.
Author: Trevor L Davis [aut, cre], Allen Day [ctb] (Some documentation and examples ported from the getopt package.), Python Software Foundation [ctb] (Some documentation from the optparse Python module.), Paul Newell [ctb]
Maintainer: Trevor L Davis <trevor.l.davis@gmail.com>

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Package yardstick updated to version 0.0.3 with previous version 0.0.2 dated 2018-11-05

Title: Tidy Characterizations of Model Performance
Description: Tidy tools for quantifying how well model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).
Author: Max Kuhn [aut, cre], Davis Vaughan [aut], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

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Package revdbayes updated to version 1.3.3 with previous version 1.3.2 dated 2018-02-12

Title: Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis
Description: Provides functions for the Bayesian analysis of extreme value models. The 'rust' package <https://cran.r-project.org/package=rust> is used to simulate a random sample from the required posterior distribution. The functionality of 'revdbayes' is similar to the 'evdbayes' package <https://cran.r-project.org/package=evdbayes>, which uses Markov Chain Monte Carlo ('MCMC') methods for posterior simulation. Also provided are functions for making inferences about the extremal index, using the K-gaps model of Suveges and Davison (2010) <doi:10.1214/09-AOAS292>. Also provided are d,p,q,r functions for the Generalised Extreme Value ('GEV') and Generalised Pareto ('GP') distributions that deal appropriately with cases where the shape parameter is very close to zero.
Author: Paul J. Northrop [aut, cre, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

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Package needmining updated to version 0.1.1 with previous version 0.1.0 dated 2019-02-27

Title: A Simple Needmining Implementation
Description: Showcasing needmining (the semi-automatic extraction of customer needs from social media data) with Twitter data. It uses the handling of the Twitter API provided by the package 'rtweet' and the textmining algorithms provided by the package 'tm'. Niklas Kuehl (2016) <doi:10.1007/978-3-319-32689-4_14> wrote an introduction to the topic of needmining.
Author: Dorian Proksch <dorian.proksch@hhl.de>, Timothy P. Jurka [ctb], Yoshimasa Tsuruoka [ctb], Loren Collingwood [ctb], Amber E. Boydstun [ctb], Emiliano Grossman [ctb], Wouter van Atteveldt [ctb]
Maintainer: Dorian Proksch <dorian.proksch@hhl.de>

Diff between needmining versions 0.1.0 dated 2019-02-27 and 0.1.1 dated 2019-03-08

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Package future updated to version 1.12.0 with previous version 1.11.1.1 dated 2019-01-26

Title: Unified Parallel and Distributed Processing in R for Everyone
Description: The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multiprocess)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers etc. Because of its unified API, there is no need to modify any code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

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Package RSSL updated to version 0.8 with previous version 0.7 dated 2018-07-12

Title: Implementations of Semi-Supervised Learning Approaches for Classification
Description: A collection of implementations of semi-supervised classifiers and methods to evaluate their performance. The package includes implementations of, among others, Implicitly Constrained Learning, Moment Constrained Learning, the Transductive SVM, Manifold regularization, Maximum Contrastive Pessimistic Likelihood estimation, S4VM and WellSVM.
Author: Jesse Krijthe [aut, cre]
Maintainer: Jesse Krijthe <jkrijthe@gmail.com>

Diff between RSSL versions 0.7 dated 2018-07-12 and 0.8 dated 2019-03-08

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Package RcppArmadillo updated to version 0.9.200.7.1 with previous version 0.9.200.7.0 dated 2019-01-17

Title: 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library
Description: 'Armadillo' is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the header files from the templated 'Armadillo' library. Thus users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed under Apache License 2; previous releases were under licensed as MPL 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. Note that Armadillo requires a fairly recent compiler; for the g++ family at least version 4.6.* is required.
Author: Dirk Eddelbuettel, Romain Francois, Doug Bates and Binxiang Ni
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package burnr updated to version 0.3.1 with previous version 0.3.0 dated 2019-01-07

Title: Fire-History Analysis in R
Description: Basic tools to analyze forest fire history data (e.g. FHX) in R.
Author: Steven Malevich [aut, cre], Christopher Guiterman [ctb], Ellis Margolis [ctb]
Maintainer: Steven Malevich <malevich@email.arizona.edu>

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New package seastests with initial version 0.14.2
Package: seastests
Title: Seasonality Tests
Version: 0.14.2
Authors@R: person('Daniel', 'Ollech', email = 'daniel.ollech@bundesbank.de', role = c('aut', 'cre'))
Description: An overall test for seasonality of a given time series in addition to a set of single seasonality tests as used in Ollech and Webel (forthcoming): An overall seasonality test. Bundesbank Discussion Paper.
Depends: R (>= 3.1.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Maintainer: Daniel Ollech <daniel.ollech@bundesbank.de>
Imports: xts, zoo, forecast, stats, graphics, utils
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-02-06 15:30:53 UTC; s3504do
Author: Daniel Ollech [aut, cre]
Repository: CRAN
Date/Publication: 2019-03-08 17:20:02 UTC

More information about seastests at CRAN
Permanent link

New package mcmcabn with initial version 0.1
Package: mcmcabn
Title: Flexible Implementation of a Structural MCMC Sampler for DAGs
Version: 0.1
Authors@R: c(person("Gilles", "Kratzer", role = c("aut", "cre"), email = "gilles.kratzer@math.uzh.ch", comment = c(ORCID = "0000-0002-5929-8935")), person("Reinhard", "Furrer", role = c("ctb"), email = "reinhard.furrer@math.uzh.ch", comment = c(ORCID = "0000-0002-6319-2332")))
Maintainer: Gilles Kratzer <gilles.kratzer@math.uzh.ch>
Description: Flexible implementation of a structural MCMC sampler for Directed Acyclic Graphs (DAGs). It supports the new edge reversal move from Grzegorczyk and Husmeier (2008) <doi:10.1007/s10994-008-5057-7> and the Markov blanket resampling from Su and Borsuk (2016) <http://jmlr.org/papers/v17/su16a.html>. It supports three priors: a prior controlling for structure complexity from Koivisto and Sood (2004) <http://dl.acm.org/citation.cfm?id=1005332.1005352>, an uninformative prior and a user defined prior. The three main problems that can be addressed by this R package are selecting the most probable structure based on a cache of pre-computed scores, controlling for overfitting and sampling the landscape of high scoring structures. It allows to quantify the marginal impact of relationships of interest by marginalising out over structures or nuisance dependencies. Structural MCMC seems a very elegant and natural way to estimate the true marginal impact, so one can determine if it's magnitude is big enough to consider as a worthwhile intervention.
Depends: R (>= 3.0.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: gRbase, abn, coda, ggplot2, cowplot, ggpubr
Suggests: bnlearn, knitr, rmarkdown, ggdag, testthat
VignetteBuilder: knitr
URL: https://www.math.uzh.ch/pages/mcmcabn/
BugReports: https://git.math.uzh.ch/gkratz/mcmcabn/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-08 08:42:10 UTC; Kratzer
Author: Gilles Kratzer [aut, cre] (<https://orcid.org/0000-0002-5929-8935>), Reinhard Furrer [ctb] (<https://orcid.org/0000-0002-6319-2332>)
Repository: CRAN
Date/Publication: 2019-03-08 17:10:03 UTC

More information about mcmcabn at CRAN
Permanent link

New package grainchanger with initial version 0.1.0
Package: grainchanger
Title: Moving-Window and Direct Data Aggregation
Version: 0.1.0
Authors@R: c(person("Laura", "Graham", email = "LauraJaneEGraham@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3611-7281")), person("Felix", "Eigenbrod", role = "ctb", email = "f.eigenbrod@soton.ac.uk", comment = "Input on initial conceptual development"), person("Marco", "Sciaini", role = "ctb", email = "sciaini.marco@gmail.com", comment = "Input on package development and structure"))
Description: Data aggregation via moving window or direct methods. Aggregate a fine-resolution raster to a grid. The moving window method smooths the surface using a specified function within a moving window of a specified size and shape prior to aggregation. The direct method simply aggregates to the grid using the specified function.
Depends: R (>= 3.3)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: raster, sf, furrr, checkmate, methods
Suggests: testthat, spelling, knitr, rmarkdown, covr, ggplot2, landscapetools
RoxygenNote: 6.1.0
Language: en-GB
VignetteBuilder: knitr
URL: https://github.com/laurajanegraham/grainchanger
BugReports: https://github.com/laurajanegraham/grainchanger/issues
NeedsCompilation: no
Packaged: 2019-03-08 16:39:37 UTC; lg1u16
Author: Laura Graham [aut, cre] (<https://orcid.org/0000-0002-3611-7281>), Felix Eigenbrod [ctb] (Input on initial conceptual development), Marco Sciaini [ctb] (Input on package development and structure)
Maintainer: Laura Graham <LauraJaneEGraham@gmail.com>
Repository: CRAN
Date/Publication: 2019-03-08 17:20:05 UTC

More information about grainchanger at CRAN
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New package EntropyMCMC with initial version 1.0.4
Package: EntropyMCMC
Type: Package
Title: MCMC Simulation and Convergence Evaluation using Entropy and Kullback-Leibler Divergence Estimation
Version: 1.0.4
Date: 2019-03-08
Authors@R: c(person("Didier", "Chauveau", role = c("aut", "cre"), email = "didier.chauveau@univ-orleans.fr"), person("Houssam", "Alrachid", role = "ctb"))
Description: Tools for Markov Chain Monte Carlo (MCMC) simulation and performance analysis. Simulate MCMC algorithms including adaptive MCMC, evaluate their convergence rate, and compare candidate MCMC algorithms for a same target density, based on entropy and Kullback-Leibler divergence criteria. MCMC algorithms can be simulated using provided functions, or imported from external codes. This package is based upon work starting with Chauveau, D. and Vandekerkhove, P. (2013) <doi:10.1051/ps/2012004> and next articles.
Depends: R (>= 3.0)
Imports: RANN, parallel, mixtools
Suggests: Rmpi, snow
License: GPL (>= 3)
LazyLoad: yes
Author: Didier Chauveau [aut, cre], Houssam Alrachid [ctb]
Maintainer: Didier Chauveau <didier.chauveau@univ-orleans.fr>
NeedsCompilation: yes
Packaged: 2019-03-08 16:27:10 UTC; didier
Repository: CRAN
Date/Publication: 2019-03-08 17:22:51 UTC

More information about EntropyMCMC at CRAN
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New package deepNN with initial version 0.3
Package: deepNN
Title: Deep Learning
Version: 0.3
Authors@R: c(person("Benjamin", "Taylor", , "b.taylor1@lancaster.ac.uk", role = c("aut","cre")))
Description: Implementation of some Deep Learning methods. Includes multilayer perceptron, different activation functions, regularisation strategies, stochastic gradient descent and dropout. Thanks go to the following references for helping to inspire and develop the package: Ian Goodfellow, Yoshua Bengio, Aaron Courville, Francis Bach (2016, ISBN:978-0262035613) Deep Learning. Terrence J. Sejnowski (2018, ISBN:978-0262038034) The Deep Learning Revolution. Grant Sanderson (3brown1blue) <https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi> Neural Networks YouTube playlist. Michael A. Nielsen <http://neuralnetworksanddeeplearning.com/> Neural Networks and Deep Learning.
Depends: R (>= 3.2.1)
Imports: stats, graphics, utils, Matrix, methods
License: GPL-3
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-03-07 15:24:43 UTC; taylorb1
Author: Benjamin Taylor [aut, cre]
Maintainer: Benjamin Taylor <b.taylor1@lancaster.ac.uk>
Repository: CRAN
Date/Publication: 2019-03-08 17:42:42 UTC

More information about deepNN at CRAN
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Package cholera updated to version 0.6.0 with previous version 0.5.1 dated 2018-08-15

Title: Amend, Augment and Aid Analysis of John Snow's Cholera Map
Description: Amends errors, augments data and aids analysis of John Snow's map of the 1854 London cholera outbreak.
Author: Peter Li [aut, cre]
Maintainer: Peter Li <lindbrook@gmail.com>

Diff between cholera versions 0.5.1 dated 2018-08-15 and 0.6.0 dated 2019-03-08

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 cholera-0.6.0/cholera/R/addVoronoi.R                                |   48 
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 cholera-0.6.0/cholera/R/addWhitehead.R                              |   22 
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 cholera-0.6.0/cholera/R/cholera.R                                   |    8 
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 183 files changed, 6034 insertions(+), 3373 deletions(-)

More information about cholera at CRAN
Permanent link

New package tablerDash with initial version 0.1.0
Package: tablerDash
Type: Package
Title: 'Tabler' API for 'Shiny'
Version: 0.1.0
Authors@R: c( person("David", "Granjon", email = "dgranjon@ymail.com", role = c("aut", "cre")), person(family = "RinteRface", role = "cph"), person(family = "codecalm", role = c("ctb", "cph"), comment = "tabler template for Bootstrap 4"), person("Winston", "Chang", role = c("ctb", "cph"), comment = "Utils functions from shinydashboard"))
Maintainer: David Granjon <dgranjon@ymail.com>
Description: 'R' interface to the 'Tabler' HTML template. See more here <https://tabler.io>. 'tablerDash' is a light 'Bootstrap 4' dashboard template. There are different layouts available such as a one page dashboard or a multi page template, where the navigation menu is contained in the navigation bar. A fancy example is available at <https://dgranjon.shinyapps.io/shinyMons/>.
URL: https://rinterface.github.io/tablerDash/, https://github.com/RinteRface/tablerDash/
BugReports: https://github.com/RinteRface/tablerDash/issues
Imports: shiny, htmltools, knitr
Suggests: shinyWidgets, shinyEffects, echarts4r
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-07 10:16:45 UTC; macdavidgranjon
Author: David Granjon [aut, cre], RinteRface [cph], codecalm [ctb, cph] (tabler template for Bootstrap 4), Winston Chang [ctb, cph] (Utils functions from shinydashboard)
Repository: CRAN
Date/Publication: 2019-03-08 16:00:03 UTC

More information about tablerDash at CRAN
Permanent link

Package spam64 updated to version 2.2-2 with previous version 2.2-1 dated 2018-12-20

Title: 64-Bit Extension of the SPArse Matrix R Package 'spam'
Description: Provides the Fortran code of the R package 'spam' with 64-bit integers. Loading this package together with the R package spam enables the sparse matrix class spam to handle huge sparse matrices with more than 2^31-1 non-zero elements.
Author: Reinhard Furrer [aut, cre], Florian Gerber [aut], Roman Flury [aut], Daniel Gerber [ctb], Kaspar Moesinger [ctb], Youcef Saad [prg] (SPARSEKIT http://www-users.cs.umn.edu/~saad/software/SPARSKIT/), Esmond G. Ng [prg] (Fortran Cholesky routines), Barry W. Peyton [prg] (Fortran Cholesky routines), Joseph W.H. Liu [prg] (Fortran Cholesky routines), Alan D. George [prg] (Fortran Cholesky routines), Lehoucq B. Rich [prg] (ARPACK), Maschhoff Kristi [prg] (ARPACK), Sorensen C. Danny [prg] (ARPACK), Yang Chao [prg] (ARPACK)
Maintainer: Reinhard Furrer <reinhard.furrer@math.uzh.ch>

Diff between spam64 versions 2.2-1 dated 2018-12-20 and 2.2-2 dated 2019-03-08

 DESCRIPTION |   54 +++++++++++++++++++++++++++---------------------------
 MD5         |    2 +-
 2 files changed, 28 insertions(+), 28 deletions(-)

More information about spam64 at CRAN
Permanent link

Package spam updated to version 2.2-2 with previous version 2.2-1 dated 2018-12-20

Title: SPArse Matrix
Description: Set of functions for sparse matrix algebra. Differences with other sparse matrix packages are: (1) we only support (essentially) one sparse matrix format, (2) based on transparent and simple structure(s), (3) tailored for MCMC calculations within G(M)RF. (4) and it is fast and scalable (with the extension package spam64).
Author: Reinhard Furrer [aut, cre], Florian Gerber [aut], Roman Flury [aut], Daniel Gerber [ctb], Kaspar Moesinger [ctb], Youcef Saad [prg] (SPARSEKIT http://www-users.cs.umn.edu/~saad/software/SPARSKIT/), Esmond G. Ng [prg] (Fortran Cholesky routines), Barry W. Peyton [prg] (Fortran Cholesky routines), Joseph W.H. Liu [prg] (Fortran Cholesky routines), Alan D. George [prg] (Fortran Cholesky routines), Lehoucq B. Rich [prg] (ARPACK), Maschhoff Kristi [prg] (ARPACK), Sorensen C. Danny [prg] (ARPACK), Yang Chao [prg] (ARPACK)
Maintainer: Reinhard Furrer <reinhard.furrer@math.uzh.ch>

Diff between spam versions 2.2-1 dated 2018-12-20 and 2.2-2 dated 2019-03-08

 spam-2.2-1/spam/vignettes/spam.html                       |only
 spam-2.2-2/spam/DESCRIPTION                               |   54 ++--
 spam-2.2-2/spam/MD5                                       |  153 ++++++--------
 spam-2.2-2/spam/NEWS.md                                   |    7 
 spam-2.2-2/spam/R/apply.R                                 |    4 
 spam-2.2-2/spam/R/constructors.R                          |    4 
 spam-2.2-2/spam/R/covmat.R                                |    4 
 spam-2.2-2/spam/R/definitions.R                           |    4 
 spam-2.2-2/spam/R/deprecated.R                            |    4 
 spam-2.2-2/spam/R/diff.R                                  |    4 
 spam-2.2-2/spam/R/dim.R                                   |    4 
 spam-2.2-2/spam/R/dist.R                                  |    4 
 spam-2.2-2/spam/R/eigen.R                                 |    4 
 spam-2.2-2/spam/R/foreign.R                               |    4 
 spam-2.2-2/spam/R/helper.R                                |    4 
 spam-2.2-2/spam/R/kronecker.R                             |    4 
 spam-2.2-2/spam/R/math.R                                  |    4 
 spam-2.2-2/spam/R/mle.R                                   |    4 
 spam-2.2-2/spam/R/norm.R                                  |    4 
 spam-2.2-2/spam/R/permutation.R                           |    4 
 spam-2.2-2/spam/R/plotting.R                              |    4 
 spam-2.2-2/spam/R/precmat.R                               |    4 
 spam-2.2-2/spam/R/profile.R                               |    4 
 spam-2.2-2/spam/R/rep_len64.R                             |    4 
 spam-2.2-2/spam/R/rmvnorm.R                               |    4 
 spam-2.2-2/spam/R/rowcolstats.R                           |    4 
 spam-2.2-2/spam/R/s3only.R                                |    4 
 spam-2.2-2/spam/R/s4coerce.R                              |    4 
 spam-2.2-2/spam/R/spam_solve.R                            |    4 
 spam-2.2-2/spam/R/spamlist.R                              |    4 
 spam-2.2-2/spam/R/subset.R                                |    4 
 spam-2.2-2/spam/R/summary.R                               |    4 
 spam-2.2-2/spam/R/tailhead.R                              |    4 
 spam-2.2-2/spam/R/tcrossprod.R                            |    4 
 spam-2.2-2/spam/R/toepliz.R                               |    4 
 spam-2.2-2/spam/R/xybind.R                                |    4 
 spam-2.2-2/spam/inst/doc/spam.pdf                         |binary
 spam-2.2-2/spam/tests/demo_article-jss-example1.R         |    4 
 spam-2.2-2/spam/tests/demo_article-jss-example1.Rout.save |   12 -
 spam-2.2-2/spam/tests/demo_article-jss-example2.R         |    4 
 spam-2.2-2/spam/tests/demo_article-jss-example2.Rout.save |   12 -
 spam-2.2-2/spam/tests/demo_article-jss.R                  |    4 
 spam-2.2-2/spam/tests/demo_article-jss.Rout.save          |   12 -
 spam-2.2-2/spam/tests/demo_cholesky.R                     |    4 
 spam-2.2-2/spam/tests/demo_cholesky.Rout.save             |   12 -
 spam-2.2-2/spam/tests/demo_jss15-BYM.R                    |    4 
 spam-2.2-2/spam/tests/demo_jss15-BYM.Rout.save            |   12 -
 spam-2.2-2/spam/tests/demo_jss15-Leroux.R                 |    4 
 spam-2.2-2/spam/tests/demo_jss15-Leroux.Rout.save         |   12 -
 spam-2.2-2/spam/tests/demo_spam.R                         |    4 
 spam-2.2-2/spam/tests/demo_spam.Rout.save                 |   12 -
 spam-2.2-2/spam/tests/demo_timing.R                       |    4 
 spam-2.2-2/spam/tests/demo_timing.Rout.save               |   12 -
 spam-2.2-2/spam/tests/jss_areal_counts.R                  |    4 
 spam-2.2-2/spam/tests/jss_areal_counts.Rout.save          |   12 -
 spam-2.2-2/spam/tests/testthat.R                          |    4 
 spam-2.2-2/spam/tests/testthat/helper.R                   |    4 
 spam-2.2-2/spam/tests/testthat/test-constructors.R        |   20 +
 spam-2.2-2/spam/tests/testthat/test-covmat.R              |    4 
 spam-2.2-2/spam/tests/testthat/test-crossprod.R           |    4 
 spam-2.2-2/spam/tests/testthat/test-diff.R                |    4 
 spam-2.2-2/spam/tests/testthat/test-dim.R                 |    4 
 spam-2.2-2/spam/tests/testthat/test-dist.R                |    4 
 spam-2.2-2/spam/tests/testthat/test-eigen.R               |    4 
 spam-2.2-2/spam/tests/testthat/test-helper.R              |    4 
 spam-2.2-2/spam/tests/testthat/test-kronecker.R           |    4 
 spam-2.2-2/spam/tests/testthat/test-math.R                |    4 
 spam-2.2-2/spam/tests/testthat/test-mle.R                 |    4 
 spam-2.2-2/spam/tests/testthat/test-ops.R                 |    4 
 spam-2.2-2/spam/tests/testthat/test-overall.R             |    4 
 spam-2.2-2/spam/tests/testthat/test-permutation.R         |    4 
 spam-2.2-2/spam/tests/testthat/test-profile.R             |    4 
 spam-2.2-2/spam/tests/testthat/test-rep_len64.R           |    4 
 spam-2.2-2/spam/tests/testthat/test-rowcolstats.R         |    4 
 spam-2.2-2/spam/tests/testthat/test-solve.R               |    4 
 spam-2.2-2/spam/tests/testthat/test-spamlist.R            |    4 
 spam-2.2-2/spam/tests/testthat/test-subset.R              |    4 
 spam-2.2-2/spam/tests/testthat/test-xybind.R              |    4 
 78 files changed, 301 insertions(+), 293 deletions(-)

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Package serieslcb updated to version 0.3.0 with previous version 0.2.0 dated 2018-07-19

Title: Lower Confidence Bounds for Binomial Series System
Description: Calculate lower confidence bounds for binomial series system reliability. The R 'shiny' application, launched by launch_app(), weaves together a workflow of customized simulations and delta coverage calculations to output a ranked list of lower confidence bound methods.
Author: Edward Schuberg
Maintainer: Edward Schuberg <eschu003@ucr.edu>

Diff between serieslcb versions 0.2.0 dated 2018-07-19 and 0.3.0 dated 2019-03-08

 DESCRIPTION     |    8 -
 MD5             |    8 +
 R/functions.R   |   14 +++
 inst/app.R      |  231 ++++++++++++++++++++++++++++++++++++++++----------------
 inst/www        |only
 man/rmse.LCB.Rd |only
 6 files changed, 189 insertions(+), 72 deletions(-)

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Package rgl updated to version 0.100.18 with previous version 0.99.16 dated 2018-03-28

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

Diff between rgl versions 0.99.16 dated 2018-03-28 and 0.100.18 dated 2019-03-08

 DESCRIPTION                                   |    9 
 MD5                                           |  170 ++--
 NAMESPACE                                     |   25 
 R/arc3d.R                                     |only
 R/ashape3d.R                                  |only
 R/callbacks.R                                 |   17 
 R/convertScene.R                              |    7 
 R/enum.R                                      |    2 
 R/getscene.R                                  |    2 
 R/grid3d.R                                    |    6 
 R/material.R                                  |   20 
 R/mesh3d.R                                    |  208 +++++
 R/par3d.R                                     |  118 +--
 R/pch3d.R                                     |   72 +-
 R/persp3d.R                                   |   17 
 R/plot3d.R                                    |   85 ++
 R/plotmath3d.R                                |   23 
 R/r3d.rgl.R                                   |   31 
 R/rglwidget.R                                 |   34 
 R/scene.R                                     |   72 +-
 R/shapelist3d.R                               |    6 
 R/subdivision.mesh3d.R                        |    3 
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 R/thigmophobe3d.R                             |only
 R/zzz.R                                       |    5 
 build/vignette.rds                            |binary
 demo/mouseCallbacks.R                         |   13 
 demo/rglExamples.R                            |   10 
 demo/shapes3d.R                               |    2 
 demo/subdivision.r                            |   10 
 inst/NEWS                                     |   61 +
 inst/doc/WebGL.html                           |   56 +
 inst/doc/legacyWebGL.html                     |  231 +++++-
 inst/doc/rgl.R                                |    4 
 inst/doc/rgl.Rmd                              |  136 ++-
 inst/doc/rgl.html                             |  665 +++++++++++-------
 inst/htmlwidgets/lib/rglClass/rglClass.src.js |  133 +++
 man/3dobjects.Rd                              |    3 
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 man/persp3d.Rd                                |   53 -
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 man/plot3d.lm.Rd                              |only
 man/plotmath3d.Rd                             |    2 
 man/postscript.Rd                             |    2 
 man/rgl-internal.Rd                           |    4 
 man/rgl.select.Rd                             |    6 
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 man/select3d.Rd                               |    4 
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 man/subscene3d.Rd                             |   37 -
 man/texts.Rd                                  |   14 
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 src/ABCLineSet.cpp                            |   45 -
 src/BBoxDeco.cpp                              |    3 
 src/Material.cpp                              |   10 
 src/Material.h                                |    3 
 src/SceneNode.h                               |    1 
 src/Shape.cpp                                 |   19 
 src/Shape.h                                   |    6 
 src/SpriteSet.cpp                             |   28 
 src/SpriteSet.h                               |   11 
 src/TextSet.cpp                               |   19 
 src/TextSet.h                                 |    7 
 src/Viewpoint.cpp                             |   26 
 src/Viewpoint.h                               |    5 
 src/api.cpp                                   |  175 ++--
 src/api.h                                     |   15 
 src/callbacks.cpp                             |   68 +
 src/fps.cpp                                   |    4 
 src/glgui.cpp                                 |   66 +
 src/glgui.h                                   |   30 
 src/init.cpp                                  |   20 
 src/par3d.cpp                                 |  914 +++++++++++++-------------
 src/rglview.cpp                               |  680 ++-----------------
 src/rglview.h                                 |  111 ---
 src/scene.cpp                                 |   47 +
 src/scene.h                                   |    3 
 src/subscene.cpp                              |  623 +++++++++++++++++
 src/subscene.h                                |  151 ++++
 src/x11gui.cpp                                |   10 
 vignettes/rgl.Rmd                             |  136 ++-
 91 files changed, 3588 insertions(+), 2216 deletions(-)

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Package rcartocolor updated to version 1.0.0 with previous version 0.0.22 dated 2018-02-08

Title: 'CARTOColors' Palettes
Description: Provides color schemes for maps and other graphics designed by 'CARTO' as described at <https://carto.com/carto-colors/>. It includes four types of palettes: aggregation, diverging, qualitative, and quantitative.
Author: Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>)
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

Diff between rcartocolor versions 0.0.22 dated 2018-02-08 and 1.0.0 dated 2019-03-08

 DESCRIPTION              |   10 +++++-----
 MD5                      |    8 ++++----
 data/cartocolors.rda     |binary
 data/metacartocolors.rda |binary
 man/carto_scale.Rd       |   14 ++++++--------
 5 files changed, 15 insertions(+), 17 deletions(-)

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New package mulset with initial version 1.0.0
Package: mulset
Version: 1.0.0
Title: Multiset Intersection Generator
Date: 2019-03-7
Authors@R: c(person("Ivan", "Tomic", role=c("aut","cre","cph"), email="info@ivantomic.com", comment = c(ORCID = "0000-0003-3596-681X")), person("Adriana", "Tomic", role=c("aut","ctb"), email="atomic@stanford.edu", comment = c(ORCID = "0000-0001-9885-3535")))
Author: Ivan Tomic [aut, cre, cph] (<https://orcid.org/0000-0003-3596-681X>), Adriana Tomic [aut, ctb] (<https://orcid.org/0000-0001-9885-3535>)
Description: Computes efficient data distributions from highly inconsistent datasets with many missing values using multi-set intersections. Based upon hash functions, 'mulset' can quickly identify intersections from very large matrices of input vectors across columns and rows and thus provides scalable solution for dealing with missing values. Tomic et al. (2019) <doi:10.1101/545186>.
Maintainer: Ivan Tomic <info@ivantomic.com>
Packaged: 2019-03-07 20:24:54 UTC; login
Imports: gtools, digest, stats
Depends: R (>= 3.4.0)
URL: https://github.com/LogIN-/mulset
BugReports: https://github.com/LogIN-/mulset/issues
License: EUPL (>= 1.2)
Encoding: UTF-8
LazyLoad: yes
LazyData: yes
RoxygenNote: 6.1.1.9000
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2019-03-08 16:50:03 UTC

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New package ELISAtools with initial version 0.1.0
Package: ELISAtools
Title: ELISA Data Analysis with Batch Correction
Version: 0.1.0
Authors@R: person("Feng", "Feng", email = "ffeng@BU.edu", role = c("aut", "cre"))
Description: To run data analysis for enzyme-link immunosorbent assays (ELISAs). Either the five- or four-parameter logistic model will be fitted for data of single ELISA. Moreover, the batch effect correction/normalization will be carried out, when there are more than one batches of ELISAs. Feng (2018) <doi:10.1101/483800>.
Depends: R (>= 3.4.0), R2HTML (>= 2.3.2), stringi (>= 1.1.7), minpack.lm (>= 1.2-1), methods
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
Collate: 'BatchCorrection.R' 'ELISAplate.R' 'ELISAtools_IO.R' 'ELISAtools.R' 'Regression.R'
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-03-07 15:47:08 UTC; ff23
Author: Feng Feng [aut, cre]
Maintainer: Feng Feng <ffeng@BU.edu>
Repository: CRAN
Date/Publication: 2019-03-08 16:12:53 UTC

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New package datapackage.r with initial version 0.1.0
Package: datapackage.r
Type: Package
Title: Data Package 'Frictionless Data'
Version: 0.1.0
Date: 2019-03-07
Authors@R: c(person("Kleanthis", "Koupidis", email = "koupidis@okfn.gr", role = c("aut", "cre")), person("Lazaros", "Ioannidis", email = "larjohn@gmail.com", role = "aut"), person("Charalampos", "Bratsas", email = "cbratsas@math.auth.gr", role = "aut"), person("Open Knowledge International", email = "info@okfn.org", role = "cph"))
Maintainer: Kleanthis Koupidis <koupidis@okfn.gr>
Description: Work with 'Frictionless Data Packages' (<https://frictionlessdata.io/specs/data-package/>). Allows to load and validate any descriptor for a data package profile, create and modify descriptors and provides expose methods for reading and streaming data in the package. When a descriptor is a 'Tabular Data Package', it uses the 'Table Schema' package (<https://CRAN.R-project.org/package=tableschema.r>) and exposes its functionality, for each resource object in the resources field.
URL: https://github.com/frictionlessdata/datapackage-r
License: MIT + file LICENSE
BugReports: https://github.com/frictionlessdata/datapackage-r/issues
Encoding: UTF-8
LazyData: true
Imports: config, future, httr, iterators, jsonlite, jsonvalidate, purrr, R6, R.utils, readr, rlist, stringr, tableschema.r, tools, urltools, utils, V8
Suggests: covr, curl, data.table, DBI, devtools, foreach, httptest, knitr, rmarkdown, RSQLite, testthat
Collate: 'DataPackageError.R' 'Package.R' 'helpers.R' 'profile.R' 'binary.readable.connection.r' 'binary.readable.r' 'datapackage.r.R' 'infer.R' 'is.valid.R' 'resource.R' 'validate.R'
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-03-07 19:12:01 UTC; akis
Author: Kleanthis Koupidis [aut, cre], Lazaros Ioannidis [aut], Charalampos Bratsas [aut], Open Knowledge International [cph]
Repository: CRAN
Date/Publication: 2019-03-08 16:32:49 UTC

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New package visualR with initial version 1.0.0
Package: visualR
Type: Package
Title: Generates a 3D Graphic, Plotting Stock Option Parameters Over Time
Version: 1.0.0
Author: John T. Buynak
Maintainer: John T. Buynak <jbuynak94@gmail.com>
Description: Generates a 3D graph which plots a selected stock option parameter over time. The default setting plots the net parameter position of a double vertical spread over time.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5), optionstrat, plotly
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-07 04:56:14 UTC; John Buynak
Repository: CRAN
Date/Publication: 2019-03-08 15:40:03 UTC

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New package tidylog with initial version 0.1.0
Package: tidylog
Type: Package
Title: Logging for 'dplyr' Functions
Version: 0.1.0
Authors@R: person("Benjamin", "Elbers", email = "elbersb@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5392-3448"))
Description: Provides feedback about basic 'dplyr' operations.
License: MIT + file LICENSE
Imports: dplyr, glue
Suggests: testthat, covr, lintr
Encoding: UTF-8
LazyData: true
URL: https://github.com/elbersb/tidylog/
BugReports: https://github.com/elbersb/tidylog/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-06 17:23:16 UTC; benjamin
Author: Benjamin Elbers [aut, cre] (<https://orcid.org/0000-0001-5392-3448>)
Maintainer: Benjamin Elbers <elbersb@gmail.com>
Repository: CRAN
Date/Publication: 2019-03-08 15:10:03 UTC

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New package tanaka with initial version 0.1.0
Package: tanaka
Type: Package
Title: Design Shaded Contour Lines (or Tanaka) Maps
Version: 0.1.0
Authors@R: person("Timothée", "Giraud", email = "timothee.giraud@cnrs.fr", role = c("cre","aut"))
Description: The Tanaka method enhances the representation of topography on a map using shaded contour lines. In this simplified implementation of the method, north-west white contours represent illuminated topography and south-east black contours represent shaded topography.
License: GPL-3
Imports: raster, sf, isoband, methods, lwgeom, grDevices, graphics
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, sp, covr
NeedsCompilation: no
Packaged: 2019-03-06 15:41:07 UTC; tim
Author: Timothée Giraud [cre, aut]
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>
Repository: CRAN
Date/Publication: 2019-03-08 15:10:07 UTC

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Package RGtk2 updated to version 2.20.36 with previous version 2.20.35 dated 2018-06-12

Title: R Bindings for Gtk 2.8.0 and Above
Description: Facilities in the R language for programming graphical interfaces using Gtk, the Gimp Tool Kit.
Author: Michael Lawrence <michafla@gene.com> and Duncan Temple Lang <duncan@wald.ucdavis.edu>
Maintainer: Michael Lawrence <michafla@gene.com>

Diff between RGtk2 versions 2.20.35 dated 2018-06-12 and 2.20.36 dated 2019-03-08

 DESCRIPTION            |    6 
 MD5                    |   34 +-
 R/gdkCoerce.R          |   11 
 inst/doc/overview2.pdf |binary
 src/atkClasses.c       |   96 ++++--
 src/atkManuals.c       |    3 
 src/classes.c          |   31 +-
 src/conversion.c       |    2 
 src/gdkClasses.c       |   68 +++-
 src/gdkManuals.c       |   27 +
 src/gioClasses.c       |  200 ++++++++++---
 src/gioManuals.c       |   70 ++--
 src/glib.c             |    6 
 src/gobject.c          |    7 
 src/gtkClasses.c       |  716 ++++++++++++++++++++++++++++++++++++-------------
 src/gtkManuals.c       |   38 +-
 src/pangoClasses.c     |   24 +
 src/pangoManuals.c     |   20 -
 18 files changed, 980 insertions(+), 379 deletions(-)

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Package Matrix updated to version 1.2-16 with previous version 1.2-15 dated 2018-11-01

Title: Sparse and Dense Matrix Classes and Methods
Description: A rich hierarchy of matrix classes, including triangular, symmetric, and diagonal matrices, both dense and sparse and with pattern, logical and numeric entries. Numerous methods for and operations on these matrices, using 'LAPACK' and 'SuiteSparse' libraries.
Author: Douglas Bates [aut], Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>), Timothy A. Davis [ctb] (SuiteSparse and 'cs' C libraries, notably CHOLMOD, AMD; collaborators listed in dir(pattern = '^[A-Z]+[.]txt$', full.names=TRUE, system.file('doc', 'SuiteSparse', package='Matrix'))), Jens Oehlschlägel [ctb] (initial nearPD()), Jason Riedy [ctb] (condest() and onenormest() for octave, Copyright: Regents of the University of California), R Core Team [ctb] (base R matrix implementation)
Maintainer: Martin Maechler <mmaechler+Matrix@gmail.com>

Diff between Matrix versions 1.2-15 dated 2018-11-01 and 1.2-16 dated 2019-03-08

 DESCRIPTION                |   13 ++++++---
 MD5                        |   60 ++++++++++++++++++++++-----------------------
 R/AllClass.R               |    2 -
 R/Auxiliaries.R            |    5 +++
 R/Ops.R                    |   52 ++++++++++++++++++++++-----------------
 R/diagMatrix.R             |   15 +++++++++++
 R/sparseMatrix.R           |   38 ++++++++++++++--------------
 TODO                       |    9 ++++--
 build/partial.rdb          |binary
 build/vignette.rds         |binary
 data/CAex.R                |    7 +++--
 data/KNex.R                |    6 +++-
 data/USCounties.R          |   12 ++++++---
 inst/NEWS.Rd               |   26 +++++++++++++++++++
 inst/doc/Comparisons.pdf   |binary
 inst/doc/Design-issues.pdf |binary
 inst/doc/Intro2Matrix.pdf  |binary
 inst/doc/Introduction.pdf  |binary
 inst/doc/sparseModels.pdf  |binary
 inst/test-tools-1.R        |    2 +
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 tests/dg_Matrix.R          |    1 
 tests/dpo-test.R           |    2 -
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 tests/factorizing.R        |    2 -
 tests/group-methods.R      |   38 ++++++++++++++++++++++------
 tests/indexing.R           |    3 +-
 tests/indexing.Rout.save   |   35 +++++++++++++-------------
 tests/matprod.R            |    2 -
 tests/validObj.R           |    3 +-
 31 files changed, 230 insertions(+), 124 deletions(-)

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New package loadr with initial version 0.1.2
Package: loadr
Version: 0.1.2
Date: 2019-03-06
Title: Cleaner Workspaces with Shared Variable Environments
Description: Provides intuitive functions for loading objects into environments, encouraging less cluttered workspaces and sharing variables with large or reusable data across users and sessions. The user provides named variables which are loaded into the variable environment for later retrieval.
Authors@R: person("Nathan", "Sheffield", email = "nathan@code.databio.org", role = c("aut", "cre"))
Suggests: knitr, testthat
VignetteBuilder: knitr
License: BSD_2_clause + file LICENSE
Encoding: UTF-8
URL: https://www.github.com/databio/loadr
BugReports: https://www.github.com/databio/loadr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-06 17:46:58 UTC; nsheff
Author: Nathan Sheffield [aut, cre]
Maintainer: Nathan Sheffield <nathan@code.databio.org>
Repository: CRAN
Date/Publication: 2019-03-08 15:20:03 UTC

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New package jsmodule with initial version 0.7.10
Package: jsmodule
Title: 'RStudio' Addins and 'Shiny' Modules for Medical Research
Version: 0.7.10
Date: 2019-03-07
Authors@R: c(person("Jinseob", "Kim", email = "jinseob2kim@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9403-605X")), person("Anpanman", role = c("cph", "fnd")) )
Description: 'RStudio' addins and 'Shiny' modules for descriptive statistics, regression and survival analysis.
Depends: R (>= 3.4.0)
License: Apache License 2.0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: stats, data.table, shiny, readxl, DT, jstable, labelled, methods, epiDisplay, GGally, ggplot2, haven, rstudioapi, shinycustomloader, MatchIt, survey, tableone, jskm, survival, purrr, geepack, maxstat
URL: https://github.com/jinseob2kim/jsmodule
BugReports: https://github.com/jinseob2kim/jsmodule/issues
Suggests: testthat, shinytest, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-03-07 06:59:01 UTC; js
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>), Anpanman [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>
Repository: CRAN
Date/Publication: 2019-03-08 15:50:03 UTC

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New package HMMmlselect with initial version 0.1.0
Package: HMMmlselect
Type: Package
Title: Determine the Number of States in Hidden Markov Models via Marginal Likelihood
Version: 0.1.0
Author: Yang Chen, Cheng-Der Fuh, Chu-Lan Kao, and S. C. Kou.
Maintainer: Chu-Lan Michael Kao <chulankao@gmail.com>
Description: Provide functions to make estimate the number of states for a hidden Markov model (HMM) using marginal likelihood method proposed by the authors. See the Manual.pdf file a detail description of all functions, and a detail tutorial.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: HiddenMarkov, mclust, mvtnorm, stats, DirichletReg, Rcpp (>= 0.12.10)
LinkingTo: Rcpp
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2019-03-06 04:20:44 UTC; USER
Repository: CRAN
Date/Publication: 2019-03-08 15:12:52 UTC

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Package glmlep updated to version 0.2 with previous version 0.1 dated 2013-06-18

Title: Fit GLM with LEP-Based Penalized Maximum Likelihood
Description: Efficient algorithms for fitting regularization paths for linear or logistic regression models penalized by LEP.
Author: Canhong Wen, Hao Lin, Xueqin Wang
Maintainer: Canhong Wen <wencanhong@gmail.com>

Diff between glmlep versions 0.1 dated 2013-06-18 and 0.2 dated 2019-03-08

 DESCRIPTION       |   12 ++++++------
 MD5               |   13 +++++++------
 NAMESPACE         |    4 ++--
 R/cv.glmlep.R     |    8 ++++----
 R/glmlep.R        |    4 ++--
 man/cv.glmlep.Rd  |    4 ----
 man/glmlep.Rd     |    6 ------
 src/glmlep_init.c |only
 8 files changed, 21 insertions(+), 30 deletions(-)

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New package fastglm with initial version 0.0.1
Package: fastglm
Type: Package
Title: Fast and Stable Fitting of Generalized Linear Models using 'RcppEigen'
Version: 0.0.1
Authors@R: c( person("Jared", "Huling", , "jaredhuling@gmail.com", c("aut", "cre")), person("Douglas", "Bates", , , c("cph")), person("Dirk", "Eddelbuettel", , , c("cph")), person("Romain", "Francois", , , c("cph")), person("Yixuan", "Qiu", , , c("cph")) )
Maintainer: Jared Huling <jaredhuling@gmail.com>
Description: Fits generalized linear models efficiently using 'RcppEigen'. The iteratively reweighted least squares implementation utilizes the step-halving approach of Marschner (2011) <doi:10.32614/RJ-2011-012> to help safeguard against convergence issues.
BugReports: https://github.com/jaredhuling/fastglm/issues
License: GPL (>= 2)
Encoding: UTF-8
Imports: Rcpp (>= 0.12.13)
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown, glm2
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-03-07 00:09:43 UTC; huling.7
Author: Jared Huling [aut, cre], Douglas Bates [cph], Dirk Eddelbuettel [cph], Romain Francois [cph], Yixuan Qiu [cph]
Repository: CRAN
Date/Publication: 2019-03-08 15:42:44 UTC

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New package discharge with initial version 1.0.0
Package: discharge
Type: Package
Title: Fourier Analysis of Discharge Data
Version: 1.0.0
Encoding: UTF-8
Date: 2019-03-06
Authors@R: c( person("Samarth", "Shah", email = "sbshah10@asu.edu", role = c("aut","cre")), person("Albert", "Ruhi", role = "aut"), person("Future H2O", role = "cph") )
Description: Computes discrete fast Fourier transform of river discharge data and the derived metrics. The methods are described in J. L. Sabo, D. M. Post (2008) <doi:10.1890/06-1340.1> and J. L. Sabo, A. Ruhi, G. W. Holtgrieve, V. Elliott, M. E. Arias, P. B. Ngor, T. A. Räsänsen, S. Nam (2017) <doi:10.1126/science.aao1053>.
Imports: lmom, ggplot2, CircStats, checkmate, boot
Depends: R (>= 3.0.2)
License: GPL-3
LazyData: TRUE
Packaged: 2019-03-07 00:35:30 UTC; Samarth
RoxygenNote: 6.1.1
NeedsCompilation: no
Author: Samarth Shah [aut, cre], Albert Ruhi [aut], Future H2O [cph]
Maintainer: Samarth Shah <sbshah10@asu.edu>
Repository: CRAN
Date/Publication: 2019-03-08 15:42:48 UTC

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New package comprehenr with initial version 0.5.4
Package: comprehenr
Type: Package
Title: List Comprehensions
Version: 0.5.4
Maintainer: Gregory Demin <gdemin@gmail.com>
Authors@R: person("Gregory", "Demin", email = "gdemin@gmail.com", role = c("aut", "cre"))
Description: Provides 'Python'-style list comprehensions. List comprehension expressions use usual loops (for(), while() and repeat()) and usual if() as list producers. In many cases it gives more concise notation than standard "*apply + filter" strategy.
URL: https://github.com/gdemin/comprehenr
BugReports: https://github.com/gdemin/comprehenr/issues
Depends: R (>= 3.3.0),
Suggests: knitr, testthat,
VignetteBuilder: knitr
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-06 14:53:55 UTC; gregory
Author: Gregory Demin [aut, cre]
Repository: CRAN
Date/Publication: 2019-03-08 15:02:42 UTC

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Package arrApply updated to version 2.1 with previous version 2.0.1 dated 2016-11-10

Title: Apply a Function to a Margin of an Array
Description: High performance variant of apply() for a fixed set of functions. Considerable speedup is a trade-off for universality, user defined functions cannot be used with this package. However, 21 most currently employed functions are available for usage. They can be divided in three types: reducing functions (like mean(), sum() etc., giving a scalar when applied to a vector), mapping function (like normalise(), cumsum() etc., giving a vector of the same length as the input vector) and finally, vector reducing function (like diff() which produces result vector of a length different from the length of input vector). Optional or mandatory additional arguments required by some functions (e.g. norm type for norm() or normalise() functions) can be passed as named arguments in '...'.
Author: Serguei Sokol
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

Diff between arrApply versions 2.0.1 dated 2016-11-10 and 2.1 dated 2019-03-08

 DESCRIPTION         |   14 +++++++-------
 MD5                 |   12 ++++++------
 NEWS                |    7 +++++++
 R/RcppExports.R     |    7 +++++--
 man/arrApply.Rd     |    6 ++++--
 src/RcppExports.cpp |   12 +++++++++++-
 src/arrApply.cpp    |   15 ++++++++++-----
 7 files changed, 50 insertions(+), 23 deletions(-)

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Package icesDatras (with last version 1.2-0) was removed from CRAN

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

2017-01-10 1.2-0
2016-08-04 1.0-0

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New package tenispolaR with initial version 0.1.4
Package: tenispolaR
Title: Provides ZENIT-POLAR Substitution Cipher Method of Encryption
Version: 0.1.4
Authors@R: person(given = "Adelmo", family = "Filho", role = c("aut", "cre"), email = "adelmo.aguiar.filho@gmail.com")
Description: Implementation of ZENIT-POLAR substitution cipher method of encryption using by default the TENIS-POLAR cipher. This last cipher of encryption became famous through the collection of Brazilian books "Os Karas" by the author Pedro Bandeira. For more details, see "A Cryptographic Dictionary" (GC&CS, 1944).
Encoding: UTF-8
LazyData: true
URL: https://github.com/adelmofilho/tenispolaR
BugReports: https://github.com/adelmofilho/tenispolaR/issues
Suggests: covr, testthat
Imports: stringr
RoxygenNote: 6.1.1
License: GPL-3
NeedsCompilation: no
Packaged: 2019-03-05 22:16:13 UTC; Adelmo Filho
Author: Adelmo Filho [aut, cre]
Maintainer: Adelmo Filho <adelmo.aguiar.filho@gmail.com>
Repository: CRAN
Date/Publication: 2019-03-08 14:10:03 UTC

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New package retrodesign with initial version 0.1.0
Package: retrodesign
Type: Package
Title: Tools for Type S (Sign) and Type M (Magnitude) Errors
Version: 0.1.0
Authors@R: c( person("Andrew", "Timm", email = "timmandrew1@gmail.com", role = c("cre","aut")), person("Andrew", "Gelman", role = c("ctb", "cph")), person("John", "Carlin", role = c("ctb", "cph")) )
Description: Provides tools for working with Type S (Sign) and Type M (Magnitude) errors, as proposed in Gelman and Tuerlinckx (2000) <doi.org/10.1007/s001800000040> and Gelman & Carlin (2014) <doi.org/10.1177/1745691614551642>. In addition to simply calculating the probability of Type S/M error, the package includes functions for calculating these errors across a variety of effect sizes for comparison, and recommended sample size given "tolerances" for Type S/M errors. To improve the speed of these calculations, closed forms solutions for the probability of a Type S/M error from Lu, Qiu, and Deng (2018) <doi.org/10.1111/bmsp.12132> are implemented. As of 1.0.0, this includes support only for simple research designs. See the package vignette for a fuller exposition on how Type S/M errors arise in research, and how to analyze them using the type of design analysis proposed in the above papers.
Depends: R (>= 3.1.0)
License: MIT + file LICENSE
URL: https://github.com/andytimm/retrodesign
BugReports: https://github.com/andytimm/retrodesign/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: graphics
Suggests: ggplot2, knitr, rmarkdown, gridExtra, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-03-05 20:16:18 UTC; Andy
Author: Andrew Timm [cre, aut], Andrew Gelman [ctb, cph], John Carlin [ctb, cph]
Maintainer: Andrew Timm <timmandrew1@gmail.com>
Repository: CRAN
Date/Publication: 2019-03-08 14:00:02 UTC

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New package conquestr with initial version 0.3.7
Package: conquestr
Type: Package
Title: An R Front End for 'ACER ConQuest'
Version: 0.3.7
Authors@R: c(person("Dan", "Cloney", email = "dan.cloney@acer.org", role = c("cre", "aut")), person("Ray", "Adams", email = "ray.adams@acer.org", role = "aut"))
URL: https://www.acer.org/au/conquest, https://conquest-forums.acer.edu.au, https://shop.acer.edu.au/acer-conquest-4
Description: Extends 'ACER ConQuest' by allowing R users to call 'ACER ConQuest' from within R. The user can also access 'ACER ConQuest' data objects by reading 'ACER ConQuest' System Files (generated by the 'ACER ConQuest' command 'put'). This is of particular use to those who are parsing text file output (e.g., 'show' files) as this is not consistent across releases of 'ACER ConQuest'. Requires 'ACER ConQuest' version 4.29.3 or later. A demonstration version can be downloaded from <https://shop.acer.edu.au/acer-conquest-4>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports:
SystemRequirements: ACER ConQuest (>=4.30.2)
Suggests: dplyr, knitr, rmarkdown
Collate: 'ReadConQuestLibrary.R' 'ReadConQuestState.R' 'conquestrFunc.R' 'conquestr.R'
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-02-22 06:49:37 UTC; acercloneyd
Author: Dan Cloney [cre, aut], Ray Adams [aut]
Maintainer: Dan Cloney <dan.cloney@acer.org>
Repository: CRAN
Date/Publication: 2019-03-08 14:22:41 UTC

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Package runner updated to version 0.2.0 with previous version 0.1.0 dated 2018-08-31

Title: Running Operations for Vectors
Description: Calculates running functions (a.k.a. windowed, rolling, cumulative) with varying window size and missing handling options. Package brings also running streak and running which, what extends beyond range of functions already implemented in R packages.
Author: Dawid Kałędkowski [aut, cre]
Maintainer: Dawid Kałędkowski <dawid.kaledkowski@gmail.com>

Diff between runner versions 0.1.0 dated 2018-08-31 and 0.2.0 dated 2019-03-08

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 runner-0.2.0/runner/tests/testthat/test_mean_run.R                   |   41 ++
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Package PowerUpR updated to version 1.0.3 with previous version 1.0.2 dated 2018-12-15

Title: Power Analysis Tools for Multilevel Randomized Experiments
Description: Includes tools to calculate statistical power, minimum detectable effect size (MDES), MDES difference (MDESD), and minimum required sample size for various multilevel randomized experiments with continuous outcomes. Some of the functions can assist with planning two- and three-level cluster-randomized trials (CRTs) sensitive to moderation effects, and with planning two-level CRTs sensitive to 2-2-1 and 2-1-1 mediation effects. See 'PowerUp!' Excel series at <https://www.causalevaluation.org/>.
Author: Metin Bulus [aut, cre], Nianbo Dong [aut], Benjamin Kelcey [aut], Jessaca Spybrook [aut]
Maintainer: Metin Bulus <bulusmetin@gmail.com>

Diff between PowerUpR versions 1.0.2 dated 2018-12-15 and 1.0.3 dated 2019-03-08

 DESCRIPTION                                        |   10 
 MD5                                                |   22 -
 NEWS.md                                            |    4 
 R/cra2r2.R                                         |   10 
 R/error.R                                          |    6 
 R/plot.R                                           |  355 +++++++++++++++------
 R/t1t2.R                                           |   48 ++
 R/utils.R                                          |   14 
 README.md                                          |    2 
 inst/CITATION                                      |    8 
 inst/doc/three_level_cluster_randomized_trial.html |    4 
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 12 files changed, 350 insertions(+), 143 deletions(-)

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Package phyclust updated to version 0.1-23 with previous version 0.1-22 dated 2017-12-02

Title: Phylogenetic Clustering (Phyloclustering)
Description: Phylogenetic clustering (phyloclustering) is an evolutionary Continuous Time Markov Chain model-based approach to identify population structure from molecular data without assuming linkage equilibrium. The package phyclust (Chen 2011) provides a convenient implementation of phyloclustering for DNA and SNP data, capable of clustering individuals into subpopulations and identifying molecular sequences representative of those subpopulations. It is designed in C for performance, interfaced with R for visualization, and incorporates other popular open source programs including ms (Hudson 2002) <doi:10.1093/bioinformatics/18.2.337>, seq-gen (Rambaut and Grassly 1997) <doi:10.1093/bioinformatics/13.3.235>, Hap-Clustering (Tzeng 2005) <doi:10.1002/gepi.20063> and PAML baseml (Yang 1997, 2007) <doi:10.1093/bioinformatics/13.5.555>, <doi:10.1093/molbev/msm088>, for simulating data, additional analyses, and searching the best tree. See the phyclust website for more information, documentations and examples.
Author: Wei-Chen Chen [aut, cre], Karin Dorman [aut]
Maintainer: Wei-Chen Chen <wccsnow@gmail.com>

Diff between phyclust versions 0.1-22 dated 2017-12-02 and 0.1-23 dated 2019-03-08

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More information about phyclust at CRAN
Permanent link

New package phmm with initial version 0.7-11
Package: phmm
Version: 0.7-11
Date: 2019-03-05
Title: Proportional Hazards Mixed-Effects Model
Authors@R: c(person(given="Michael", family="Donohue", role = c("aut", "cre"), email = "mdonohue@usc.edu"), person(given="Ronghui", family="Xu", role = "aut"))
Maintainer: Michael Donohue <mdonohue@usc.edu>
Depends: survival, lattice, Matrix
VignetteBuilder: knitr
URL: https://github.com/mcdonohue/phmm
Suggests: knitr, lme4 (>= 1.0)
Description: Fits proportional hazards model incorporating random effects using an EM algorithm using Markov Chain Monte Carlo at E-step. Vaida and Xu (2000) <DOI:10.1002/1097-0258(20001230)19:24%3C3309::AID-SIM825%3E3.0.CO;2-9>.
License: GPL-3
Collate: 'phmm-package.R' 'formula.R' 'linear.predictors.R' 'phmm.R' 'pseudoPoisPHMM.R' 'traceHat.R'
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2019-03-08 03:10:08 UTC; mdonohue
Author: Michael Donohue [aut, cre], Ronghui Xu [aut]
Repository: CRAN
Date/Publication: 2019-03-08 13:40:07 UTC

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New package MODIS with initial version 1.1.5
Package: MODIS
Type: Package
Title: Acquisition and Processing of MODIS Products
Version: 1.1.5
Date: 2019-03-08
URL: https://github.com/MatMatt/MODIS
BugReports: https://github.com/MatMatt/MODIS/issues
Authors@R: c( person("Matteo", "Mattiuzzi", role = "aut", email = "matteo@mattiuzzi.com"), person("Jan", "Verbesselt", role = "ctb"), person("Tomislav", "Hengl", role = "ctb"), person("Anja", "Klisch", role = "ctb"), person("Forrest", "Stevens", role = "ctb"), person("Steven", "Mosher", role = "ctb"), person("Bradley", "Evans", role = "ctb"), person("Agustin", "Lobo", role = "ctb"), person("Koen", "Hufkens", role = "ctb"), person("Florian", "Detsch", role = c("cre", "aut"), email = "fdetsch@web.de"))
Description: Download and processing functionalities for the Moderate Resolution Imaging Spectroradiometer (MODIS). The package provides automated access to the global online data archives LP DAAC (<https://lpdaac.usgs.gov/>), LAADS (<https://ladsweb.modaps.eosdis.nasa.gov/>) and NSIDC (<https://nsidc.org/>) as well as processing capabilities such as file conversion, mosaicking, subsetting and time series filtering.
License: MIT + file LICENSE
LazyData: TRUE
Depends: mapdata, R (>= 2.10), raster
Imports: bitops, curl, devtools, grDevices, graphics, mapedit, maps, maptools, methods, parallel, ptw, rgdal, rgeos, sf, sp, stats, utils
SystemRequirements: GDAL (>= 1.8.0)
ByteCompile: TRUE
Encoding: UTF-8
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-03-08 09:46:02 UTC; FlorianD
Author: Matteo Mattiuzzi [aut], Jan Verbesselt [ctb], Tomislav Hengl [ctb], Anja Klisch [ctb], Forrest Stevens [ctb], Steven Mosher [ctb], Bradley Evans [ctb], Agustin Lobo [ctb], Koen Hufkens [ctb], Florian Detsch [cre, aut]
Maintainer: Florian Detsch <fdetsch@web.de>
Repository: CRAN
Date/Publication: 2019-03-08 13:43:00 UTC

More information about MODIS at CRAN
Permanent link

Package liteq updated to version 1.1.0 with previous version 1.0.1 dated 2017-10-20

Title: Lightweight Portable Message Queue Using 'SQLite'
Description: Temporary and permanent message queues for R. Built on top of 'SQLite' databases. 'SQLite' provides locking, and makes it possible to detect crashed consumers. Crashed jobs can be automatically marked as "failed", or put in the queue again, potentially a limited number of times.
Author: Gábor Csárdi
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between liteq versions 1.0.1 dated 2017-10-20 and 1.1.0 dated 2019-03-08

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Package diceR updated to version 0.5.2 with previous version 0.5.1 dated 2018-06-11

Title: Diverse Cluster Ensemble in R
Description: Performs cluster analysis using an ensemble clustering framework, Chiu & Talhouk (2018) <doi:10.1186/s12859-017-1996-y>. Results from a diverse set of algorithms are pooled together using methods such as majority voting, K-Modes, LinkCluE, and CSPA. There are options to compare cluster assignments across algorithms using internal and external indices, visualizations such as heatmaps, and significance testing for the existence of clusters.
Author: Derek Chiu [aut, cre], Aline Talhouk [aut], Johnson Liu [ctb, com]
Maintainer: Derek Chiu <dchiu@bccrc.ca>

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Package AICcmodavg updated to version 2.2-1 with previous version 2.2-0 dated 2019-02-26

Title: Model Selection and Multimodel Inference Based on (Q)AIC(c)
Description: Functions to implement model selection and multimodel inference based on Akaike's information criterion (AIC) and the second-order AIC (AICc), as well as their quasi-likelihood counterparts (QAIC, QAICc) from various model object classes. The package implements classic model averaging for a given parameter of interest or predicted values, as well as a shrinkage version of model averaging parameter estimates or effect sizes. The package includes diagnostics and goodness-of-fit statistics for certain model types including those of 'unmarkedFit' classes estimating demographic parameters after accounting for imperfect detection probabilities. Some functions also allow the creation of model selection tables for Bayesian models of the 'bugs', 'rjags', and 'jagsUI' classes. Functions also implement model selection using BIC. Objects following model selection and multimodel inference can be formatted to LaTeX using 'xtable' methods included in the package.
Author: Marc J. Mazerolle <marc.mazerolle@sbf.ulaval.ca> and portions of code contributed by Dan Linden.
Maintainer: Marc J. Mazerolle <marc.mazerolle@sbf.ulaval.ca>

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Package rockchalk updated to version 1.8.144 with previous version 1.8.140 dated 2019-02-19

Title: Regression Estimation and Presentation
Description: A collection of functions for interpretation and presentation of regression analysis. These functions are used to produce the statistics lectures in <http://pj.freefaculty.org/guides>. Includes regression diagnostics, regression tables, and plots of interactions and "moderator" variables. The emphasis is on "mean-centered" and "residual-centered" predictors. The vignette 'rockchalk' offers a fairly comprehensive overview. The vignette 'Rstyle' has advice about coding in R. The package title 'rockchalk' refers to our school motto, 'Rock Chalk Jayhawk, Go K.U.'.
Author: Paul E. Johnson [aut, cre], Gabor Grothendieck [ctb]
Maintainer: Paul E. Johnson <pauljohn@ku.edu>

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Package rioja updated to version 0.9-15.2 with previous version 0.9-15.1 dated 2018-01-04

Title: Analysis of Quaternary Science Data
Description: Functions for the analysis of Quaternary science data, including constrained clustering, WA, WAPLS, IKFA, MLRC and MAT transfer functions, and stratigraphic diagrams.
Author: Steve Juggins
Maintainer: ORPHANED

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Package MODIStsp updated to version 1.3.8 with previous version 1.3.7 dated 2018-12-03

Title: A Tool for Automating Download and Preprocessing of MODIS Land Products Data
Description: Allows automating the creation of time series of rasters derived from MODIS Satellite Land Products data. It performs several typical preprocessing steps such as download, mosaicking, reprojection and resize of data acquired on a specified time period. All processing parameters can be set using a user-friendly GUI. Users can select which layers of the original MODIS HDF files they want to process, which additional Quality Indicators should be extracted from aggregated MODIS Quality Assurance layers and, in the case of Surface Reflectance products , which Spectral Indexes should be computed from the original reflectance bands. For each output layer, outputs are saved as single-band raster files corresponding to each available acquisition date. Virtual files allowing access to the entire time series as a single file are also created. Command-line execution exploiting a previously saved processing options file is also possible, allowing to automatically update time series related to a MODIS product whenever a new image is available.
Author: Lorenzo Busetto [aut, cre] (<https://orcid.org/0000-0001-9634-6038>), Luigi Ranghetti [aut] (<https://orcid.org/0000-0001-6207-5188>), Leah Wasser [rev] (Leah Wasser reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/184), Jeff Hanson [rev] (Jeff Hanson reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/184)
Maintainer: Lorenzo Busetto <lbusett@gmail.com>

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Package magicaxis updated to version 2.0.7 with previous version 2.0.4 dated 2018-11-29

Title: Pretty Scientific Plotting with Minor-Tick and Log Minor-Tick Support
Description: Functions to make useful (and pretty) plots for scientific plotting. Additional plotting features are added for base plotting, with particular emphasis on making attractive log axis plots.
Author: Aaron Robotham
Maintainer: Aaron Robotham <aaron.robotham@uwa.edu.au>

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Package DataVisualizations updated to version 1.1.6 with previous version 1.1.5 dated 2019-02-02

Title: Visualizations of High-Dimensional Data
Description: The flagship idea of 'DataVisualizations' is the mirrored density plot (MD-plot) which is a PDE-optimized violin plot for either classified or non-classified multivariate data. The MD-plot is an alternative to the box-and-whisker diagram (box plot) and bean plot. Furthermore, a collection of various visualization methods for univariate data is provided. In the case of exploratory data analysis, 'DataVisualizations' makes it possible to inspect the distribution of each feature of a dataset visually through a combination of four methods. One of these methods is the Pareto density estimation (PDE) of the probability density function (pdf). Additionally, visualizations of the distribution of distances using PDE, the scatter-density plot using PDE for two variables as well as the Shepard density plot and the Bland-Altman plot are presented here. Pertaining to classified high-dimensional data, a number of visualizations are described, such as f.ex. the heat map and silhouette plot. A political map of the world or Germany can be visualized with the additional information defined by a classification of countries or regions. By extending the political map further, an uncomplicated function for a Choropleth map can be used which is useful for measurements across a geographic area. For categorical features, the Pie charts, slope charts and fan plots, improved by the ABC analysis, become usable. More detailed explanations are found in the book by Thrun, M.C.: "Projection-Based Clustering through Self-Organization and Swarm Intelligence" (2018) <doi:10.1007/978-3-658-20540-9>.
Author: Michael Thrun [aut, cre, cph] (<https://orcid.org/0000-0001-9542-5543>), Felix Pape [aut, rev], Onno Hansen-Goos [ctr, ctb], Alfred Ultsch [dtc, ctb]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package validatetools updated to version 0.4.6 with previous version 0.4.3 dated 2018-03-27

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 petrinetR updated to version 0.2.1 with previous version 0.2.0 dated 2018-07-03

Title: Building, Visualizing, Exporting and Replaying Petri Nets
Description: Functions for the construction of Petri Nets. Petri Nets can be replayed by firing enabled transitions. Silent transitions will be hidden by the execution handler. Also includes functionalities for the visualization of Petri Nets and export of Petri Nets to PNML (Petri Net Markup Language) files.
Author: Gert Janssenswillen [aut, cre]
Maintainer: Gert Janssenswillen <gert.janssenswillen@uhasselt.be>

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Package glmmfields updated to version 0.1.2 with previous version 0.1.1 dated 2018-11-09

Title: Generalized Linear Mixed Models with Robust Random Fields for Spatiotemporal Modeling
Description: Implements Bayesian spatial and spatiotemporal models that optionally allow for extreme spatial deviations through time. 'glmmfields' uses a predictive process approach with random fields implemented through a multivariate-t distribution instead of the usual multivariate normal. Sampling is conducted with 'Stan'. References: Anderson and Ward (2019) <doi:10.1002/ecy.2403>.
Author: Sean C. Anderson [aut, cre], Eric J. Ward [aut], Trustees of Columbia University [cph]
Maintainer: Sean C. Anderson <sean@seananderson.ca>

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Package GenEst updated to version 1.2.3 with previous version 1.2.2 dated 2019-02-06

Title: Generalized Mortality Estimator
Description: Command-line and 'shiny' GUI implementation of the GenEst models for estimating bird and bat mortality at wind and solar power facilities, following Dalthorp, et al. (2018) <doi:10.3133/tm7A2>.
Author: Daniel Dalthorp [aut, cre], Juniper Simonis [aut], Lisa Madsen [aut], Manuela Huso [aut], Paul Rabie [aut], Jeffrey Mintz [aut], Robert Wolpert [aut], Jared Studyvin [aut], Franzi Korner-Nievergelt [aut]
Maintainer: Daniel Dalthorp <ddalthorp@usgs.gov>

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Package fastNaiveBayes updated to version 1.0.1 with previous version 1.0.0 dated 2019-02-28

Title: Extremely Fast Implementation of a Naive Bayes Classifier
Description: This is an extremely fast implementation of a Naive Bayes classifier. This package is currently the only package that supports a Bernoulli distribution, a Multinomial distribution, and a Gaussian distribution, making it suitable for both binary features, frequency counts, and numerical features. Another unique feature is the support of a mix of different event models. Only numerical variables are allowed, however, categorical variables can be transformed into dummies and used with the Bernoulli distribution. This implementation offers a huge performance gain compared to the 'e1071' implementation in R. The execution times were compared on a data set of tweets and was found to be around 330 times faster. See the vignette for more details. This performance gain is only realized using a Bernoulli event model. Furthermore, the Multinomial event model implementation is even slightly faster, but incomparable since it was not implemented in 'e1071' The implementation is largely based on the paper "A comparison of event models for Naive Bayes anti-spam e-mail filtering" written by K.M. Schneider (2003) <doi:10.3115/1067807>. Any issues can be submitted to: <https://github.com/mskogholt/fastNaiveBayes/issues>.
Author: Martin Skogholt
Maintainer: Martin Skogholt <m.skogholt@gmail.com>

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Package palasso updated to version 0.0.4 with previous version 0.0.3 dated 2019-02-19

Title: Paired Lasso Regression
Description: Implements sparse regression with paired covariates (Rauschenberger et al. 2019). For the optional shrinkage, install ashr (<https://github.com/stephens999/ashr>) and CorShrink (<https://github.com/kkdey/CorShrink>) from GitHub (see README).
Author: Armin Rauschenberger [aut, cre]
Maintainer: Armin Rauschenberger <a.rauschenberger@vumc.nl>

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Package JointAI updated to version 0.5.0 with previous version 0.4.0 dated 2018-12-04

Title: Joint Analysis and Imputation of Incomplete Data
Description: Provides joint analysis and imputation of (generalized) linear and cumulative logit regression models, (generalized) linear and cumulative logit mixed models and parametric (Weibull) as well as Cox proportional hazards survival models with incomplete (covariate) data in the Bayesian framework. The package performs some preprocessing of the data and creates a 'JAGS' model, which will then automatically be passed to 'JAGS' <http://mcmc-jags.sourceforge.net> with the help of the package 'rjags'. It also provides summary and plotting functions for the output and allows to export imputed values.
Author: Nicole S. Erler [aut, cre] (<https://orcid.org/0000-0002-9370-6832>)
Maintainer: Nicole S. Erler <n.erler@erasmusmc.nl>

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Package coin updated to version 1.3-0 with previous version 1.2-2 dated 2017-11-28

Title: Conditional Inference Procedures in a Permutation Test Framework
Description: Conditional inference procedures for the general independence problem including two-sample, K-sample (non-parametric ANOVA), correlation, censored, ordered and multivariate problems.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>), Henric Winell [aut] (<https://orcid.org/0000-0001-7995-3047>), Kurt Hornik [aut] (<https://orcid.org/0000-0003-4198-9911>), Mark A. van de Wiel [aut] (<https://orcid.org/0000-0003-4780-8472>), Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package agop updated to version 0.2-2 with previous version 0.1-4 dated 2014-09-14

Title: Aggregation Operators and Preordered Sets
Description: Tools supporting multi-criteria and group decision making, including variable number of criteria, by means of aggregation operators, spread measures, fuzzy logic connectives, fusion functions, and preordered sets. Possible applications include, but are not limited to, quality management, scientometrics, software engineering, etc.
Author: Marek Gagolewski [aut, cre], Anna Cena [ctb]
Maintainer: Marek Gagolewski <marek@gagolewski.com>

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Package cgraph updated to version 4.0.0 with previous version 3.0.1 dated 2018-11-05

Title: Computational Graphs
Description: Allows to create, evaluate, and differentiate computational graphs in R. A computational graph is a graph representation of a multivariate function decomposed by its (elementary) operations. Nodes in the graph represent arrays while edges represent dependencies among the arrays. An advantage of expressing a function as a computational graph is that this enables to differentiate the function by automatic differentiation. The 'cgraph' package supports various operations including basic arithmetic, trigonometry operations, and linear algebra operations. It differentiates computational graphs by reverse automatic differentiation. The flexible architecture of the package makes it applicable to solve a variety of problems including local sensitivity analysis, gradient-based optimization, and machine learning.
Author: Ron Triepels
Maintainer: Ron Triepels <dev@cgraph.org>

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Package biomod2 updated to version 3.3-7.1 with previous version 3.3-7 dated 2016-03-01

Title: Ensemble Platform for Species Distribution Modeling
Description: Functions for species distribution modeling, calibration and evaluation, ensemble of models.
Author: Wilfried Thuiller [aut, cre], Damien Georges [aut, cre], Robin Engler [aut], Frank Breiner [aut]
Maintainer: Damien Georges <damien.georges2@gmail.com>

Diff between biomod2 versions 3.3-7 dated 2016-03-01 and 3.3-7.1 dated 2019-03-08

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 R/Biomod.Models_RE.R          |    4 ++--
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Package rivernet updated to version 1.2 with previous version 1.1 dated 2017-05-12

Title: Read, Analyze and Plot River Networks
Description: Functions for reading, analysing and plotting river networks. For this package, river networks consist of sections and nodes with associated attributes, e.g. to characterise their morphological, chemical and biological state. The package provides functions to read this data from text files, to analyse the network structure and network paths and regions consisting of sections and nodes that fulfill prescribed criteria, and to plot the river network and associated properties.
Author: Peter Reichert
Maintainer: Peter Reichert <peter.reichert@eawag.ch>

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Package bnspatial updated to version 1.0.4 with previous version 1.0.3 dated 2017-11-17

Title: Spatial Implementation of Bayesian Networks and Mapping
Description: Allows spatial implementation of Bayesian networks and mapping in geographical space. It makes maps of expected value (or most likely state) given known and unknown conditions, maps of uncertainty measured as coefficient of variation or Shannon index (entropy), maps of probability associated to any states of any node of the network. Some additional features are provided as well: parallel processing options, data discretization routines and function wrappers designed for users with minimal knowledge of the R language. Outputs can be exported to any common GIS format. Development was funded by the European Union FP7 (2007-2013), under project ROBIN (<http://robinproject.info>).
Author: Dario Masante [aut, cre]
Maintainer: Dario Masante <dario.masante@gmail.com>

Diff between bnspatial versions 1.0.3 dated 2017-11-17 and 1.0.4 dated 2019-03-08

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Package benchmarkmeData updated to version 1.0.1 with previous version 1.0.0 dated 2019-01-27

Title: Data Set for the 'benchmarkme' Package
Description: Crowd sourced benchmarks from running the 'benchmarkme' package.
Author: Colin Gillespie [aut, cre]
Maintainer: Colin Gillespie <csgillespie@gmail.com>

Diff between benchmarkmeData versions 1.0.0 dated 2019-01-27 and 1.0.1 dated 2019-03-08

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Package spew (with last version 1.3.0) was removed from CRAN

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

2017-11-03 1.3.0

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Package egonet (with last version 1.2) was removed from CRAN

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

2012-11-10 1.2
2011-11-20 1.1
2010-04-07 1.0

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