Fri, 11 Jan 2019

Package mudata2 updated to version 1.0.5 with previous version 1.0.4 dated 2018-12-08

Title: Interchange Tools for Multi-Parameter Spatiotemporal Data
Description: Formatting and structuring multi-parameter spatiotemporal data is often a time-consuming task. This package offers functions and data structures designed to easily organize and visualize these data for applications in geology, paleolimnology, dendrochronology, and paleoclimate. See Dunnington and Spooner (2018) <doi:10.1139/facets-2017-0026>.
Author: Dewey Dunnington [aut, cre] (<https://orcid.org/0000-0002-9415-4582>)
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

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Package ipc updated to version 0.1.2 with previous version 0.1.1 dated 2018-11-05

Title: Tools for Message Passing Between Processes
Description: Provides tools for passing messages between R processes. Shiny Examples are provided showing how to perform useful tasks such as: updating reactive values from within a future, progress bars for long running async tasks, and interrupting async tasks based on user input.
Author: Ian E. Fellows
Maintainer: Ian E. Fellows <ian@fellstat.com>

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Package bibliometrix updated to version 2.1.0 with previous version 2.0.2 dated 2018-11-16

Title: An R-Tool for Comprehensive Science Mapping Analysis
Description: Tool for quantitative research in scientometrics and bibliometrics. It provides various routines for importing bibliographic data from SCOPUS (<http://scopus.com>), Clarivate Analytics Web of Science (<http://www.webofknowledge.com/>), Cochrane Library (<http://www.cochranelibrary.com/>) and PubMed (<https://www.ncbi.nlm.nih.gov/pubmed/>) databases, performing bibliometric analysis and building networks for co-citation, coupling, scientific collaboration and co-word analysis.
Author: Massimo Aria [cre, aut], Corrado Cuccurullo [aut]
Maintainer: Massimo Aria <aria@unina.it>

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Package beginr updated to version 0.1.4 with previous version 0.1.3 dated 2018-06-12

Title: Functions for R Beginners
Description: Useful functions for R beginners, including hints for the arguments of the 'plot()' function, self-defined functions for error bars, user-customized pair plots and hist plots, enhanced linear regression figures, etc.. This package could be helpful to R experts as well.
Author: Peng Zhao
Maintainer: Peng Zhao <pzhao@pzhao.net>

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Package steemr updated to version 0.1.2 with previous version 0.0.5 dated 2018-09-11

Title: A Tool for Processing Steem Data
Description: Steem is a blockchain-based social media platform (see <https://en.wikipedia.org/wiki/Steemit>). The Steem social activity data are saved in the Steem blockchain, the SteemDB database, the SteemSQL database, and so on. 'steemr' is an R package that downloads the Steem data from the SteemDB and SteemSQL servers, re-organizes the data in a user-friendly way, and visualizes the data for further analysis.
Author: Peng Zhao <pzhao@pzhao.net>
Maintainer: Peng Zhao <pzhao@pzhao.net>

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New package forestSAS with initial version 1.0.1
Package: forestSAS
Version: 1.0.1
Date: 2019-01-02
Type: Package
Title: Forest Spatial Structure Analysis Systems
Authors@R: c(person(given="Zongzheng",family="Chai", email="chaizz@126.com",role=c("aut", "cre")))
Author: Zongzheng Chai [aut, cre]
Maintainer: Zongzheng Chai <chaizz@126.com>
Depends: R (>= 3.4.0)
Imports: spatstat
Description: In recent years, there has been considerable interest in a group of neighborhood-based structural parameters that properly express the spatial structure characteristics of tree populations and forest communities and have strong operability for guiding forestry practices.the 'forestSAS' package provide more important information and allow us to better understand and analyze the fine-scale spatial structure of tree populations and stand structure.
License: GPL (>= 2)
LazyData: TRUE
NeedsCompilation: no
Repository: CRAN
Packaged: 2019-01-02 13:28:52 UTC; Administrator
Date/Publication: 2019-01-11 18:10:02 UTC

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New package wdpar with initial version 0.0.1
Package: wdpar
Type: Package
Version: 0.0.1
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, methods, sp, assertthat (>= 0.2.0), progress (>= 1.2.0), curl (>= 3.2), rappdirs (>= 0.3.1), httr (>= 1.3.1), pingr (>= 1.1.2), countrycode (>= 1.1.0), wdman (>= 0.2.4), RSelenium (>= 1.7.4), xml2 (>= 1.2.0), cli (>= 1.0.1), stringi (>= 1.2.4), 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)
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: 2019-01-07 07:25:46 UTC; jeff
Author: Jeffrey O Hanson [aut, cre]
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>
Repository: CRAN
Date/Publication: 2019-01-11 17:10:03 UTC

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New package tsutils with initial version 0.9.0
Package: tsutils
Type: Package
Title: Time Series Exploration, Modelling and Forecasting
Version: 0.9.0
Authors@R: c( person("Nikolaos", "Kourentzes",, "nikolaos@kourentzes.com", c("aut", "cre")), person("Ivan", "Svetunkov",, "ivan@svetunkov.ru", c("ctb")), person("Oliver", "Schaer",, "info@oliverschaer.ch", c("ctb")))
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.
Imports: RColorBrewer, forecast, MAPA
Suggests: thief
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/trnnick/tsutils/
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-01-08 17:29:56 UTC; Nikos
Author: Nikolaos Kourentzes [aut, cre], Ivan Svetunkov [ctb], Oliver Schaer [ctb]
Maintainer: Nikolaos Kourentzes <nikolaos@kourentzes.com>
Repository: CRAN
Date/Publication: 2019-01-11 17:10:07 UTC

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New package TPES with initial version 1.0.0
Package: TPES
Type: Package
Title: Tumor Purity Estimation using SNVs
Version: 1.0.0
Date: 2019-01-09
Author: Alessio Locallo <alessio.locallo@gmail.com>, Davide Prandi <davide.prandi@unitn.it>, Francesca Demichelis <f.demichelis@unitn.it>
Maintainer: Alessio Locallo <alessio.locallo@gmail.com>
Description: A bioinformatics tool for the estimation of the tumor purity from sequencing data. It uses the set of putative clonal somatic single nucleotide variants within copy number neutral segments to call tumor cellularity.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Imports: grDevices, graphics, stats
NeedsCompilation: no
Packaged: 2019-01-09 17:03:16 UTC; l0ka
Repository: CRAN
Date/Publication: 2019-01-11 17:40:12 UTC

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New package tor with initial version 1.0.1
Package: tor
Title: Import Multiple Files From a Single Directory at Once
Version: 1.0.1
Authors@R: person(given = "Mauro", family = "Lepore", role = c("aut", "cre"), email = "maurolepore@gmail.com")
Description: The goal of tor (to-R) is to help you to import multiple files from a single directory at once, and to do so as quickly, flexibly, and simply as possible. It makes a frequent, task less painful.
License: GPL-3
URL: https://github.com/maurolepore/tor
BugReports: https://github.com/maurolepore/tor/issues
Imports: fs, readr, rlang, tibble
Suggests: covr, knitr, rmarkdown, spelling, testthat
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-01-09 22:14:53 UTC; LeporeM
Author: Mauro Lepore [aut, cre]
Maintainer: Mauro Lepore <maurolepore@gmail.com>
Repository: CRAN
Date/Publication: 2019-01-11 17:40:03 UTC

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Package rtrek updated to version 0.2.0 with previous version 0.1.0 dated 2018-06-06

Title: Datasets and Functions Relating to Star Trek
Description: Provides datasets related to the Star Trek fictional universe and functions for working with the data. The package also provides access to real world datasets based on the televised series and other related licensed media productions. It interfaces with the Star Trek API (STAPI) (<http://stapi.co/>), Memory Alpha (<http://memory-alpha.wikia.com/>), and Memory Beta (<http://memory-beta.wikia.com/>) to retrieve data, metadata and other information relating to Star Trek. It also contains several local datasets covering a variety of topics. The package also provides functions for working with data from other Star Trek-related R data packages containing larger datasets not stored in 'rtrek'.
Author: Matthew Leonawicz [aut, cre] (<https://orcid.org/0000-0001-9452-2771>)
Maintainer: Matthew Leonawicz <matt_leonawicz@esource.com>

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New package prithulib with initial version 1.0.2
Package: prithulib
Type: Package
Title: Perform Random Experiments
Version: 1.0.2
Author: Prithul Chaturvedi <prithulc@gmail.com>
Maintainer: Prithul Chaturvedi <prithulc@gmail.com>
Description: Enables user to perform the following: 1. Roll 'n' number of die/dice (roll()). 2. Toss 'n' number of coin(s) (toss()). 3. Play the game of Rock, Paper, Scissors. 4. Choose 'n' number of card(s) from a pack of 52 playing cards (Joker optional).
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-01-09 12:29:08 UTC; Prithul
Repository: CRAN
Date/Publication: 2019-01-11 17:30:03 UTC

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Package GPM updated to version 3.0.0 with previous version 2.0.0 dated 2018-11-14

Title: Gaussian Process Modeling of Multi-Response and Possibly Noisy Datasets
Description: Provides a general and efficient tool for fitting a response surface to a dataset via Gaussian processes. The dataset can have multiple responses and be noisy (with stationary variance). The fitted GP model can predict the gradient as well. The package is based on the work of Bostanabad, R., Kearney, T., Tao, S. Y., Apley, D. W. & Chen, W. (2018) Leveraging the nugget parameter for efficient Gaussian process modeling. International Journal for Numerical Methods in Engineering, 114, 501-516.
Author: Ramin Bostanabad, Tucker Kearney, Siyo Tao, Daniel Apley, and Wei Chen (IDEAL)
Maintainer: Ramin Bostanabad <bostanabad@u.northwestern.edu>

Diff between GPM versions 2.0.0 dated 2018-11-14 and 3.0.0 dated 2019-01-11

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New package ggdark with initial version 0.2.1
Package: ggdark
Type: Package
Title: Dark Mode for 'ggplot2' Themes
Version: 0.2.1
Author: Neal Grantham
Maintainer: Neal Grantham <neal@nsgrantham.com>
Description: Activate dark mode on your favorite 'ggplot2' theme with dark_mode() or use the dark versions of 'ggplot2' themes, including dark_theme_gray(), dark_theme_minimal(), and others. When a dark theme is applied, all geom color and geom fill defaults are changed to make them visible against a dark background. To restore the defaults to their original values, use invert_geom_defaults().
License: MIT + file LICENSE
Depends: R (>= 3.1)
Imports: ggplot2 (>= 3.0)
Suggests: testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-01-09 08:17:48 UTC; neal
Repository: CRAN
Date/Publication: 2019-01-11 17:30:06 UTC

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Package FedData updated to version 2.5.6 with previous version 2.5.5 dated 2018-08-09

Title: Functions to Automate Downloading Geospatial Data Available from Several Federated Data Sources
Description: Functions to automate downloading geospatial data available from several federated data sources (mainly sources maintained by the US Federal government). Currently, the package enables extraction from seven datasets: The National Elevation Dataset digital elevation models (1 and 1/3 arc-second; USGS); The National Hydrography Dataset (USGS); The Soil Survey Geographic (SSURGO) database from the National Cooperative Soil Survey (NCSS), which is led by the Natural Resources Conservation Service (NRCS) under the USDA; the Global Historical Climatology Network (GHCN), coordinated by National Climatic Data Center at NOAA; the Daymet gridded estimates of daily weather parameters for North America, version 3, available from the Oak Ridge National Laboratory's Distributed Active Archive Center (DAAC); the International Tree Ring Data Bank; and the National Land Cover Database (NLCD).
Author: R. Kyle Bocinsky [aut, cre], Dylan Beaudette [ctb], Scott Chamberlain [ctb]
Maintainer: R. Kyle Bocinsky <bocinsky@gmail.com>

Diff between FedData versions 2.5.5 dated 2018-08-09 and 2.5.6 dated 2019-01-11

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New package estmeansd with initial version 0.1.0
Package: estmeansd
Type: Package
Title: Estimating the Sample Mean and Standard Deviation from Commonly Reported Quantiles in Meta-Analysis
Version: 0.1.0
Authors@R: c(person("Sean", "McGrath", role = c("aut", "cre"), email = "sean.mcgrath@mail.mcgill.ca"), person("XiaoFei", "Zhao", role = c("aut"), email = "xiaofei.zhao@mail.mcgill.ca"), person("Russell", "Steele", role = c("aut"), email = "russell.steele@mcgill.ca"), person("Andrea", "Benedetti", role = c("aut"), email = "andrea.benedetti@mcgill.ca"))
Author: Sean McGrath [aut, cre], XiaoFei Zhao [aut], Russell Steele [aut], Andrea Benedetti [aut]
Maintainer: Sean McGrath <sean.mcgrath@mail.mcgill.ca>
Description: Implements the methods of McGrath et al. (in preparation) for estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. These methods can be applied to studies that report the sample median, sample size, and one or both of (i) the sample minimum and maximum values and (ii) the first and third quartiles.
Imports: metaBLUE, metamedian, stats
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-01-09 21:01:55 UTC; Sean
Repository: CRAN
Date/Publication: 2019-01-11 17:40:06 UTC

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New package econetwork with initial version 0.1
Package: econetwork
Type: Package
Title: Analyzing Ecological Networks
Version: 0.1
Date: 2019-01-09
Author: Stephane Dray, Catherine Matias, Vincent Miele, Marc Ohlmann, Wilfried Thuiller
Maintainer: Vincent Miele <vincent.miele@univ-lyon1.fr>
Description: A collection of advanced tools, methods and models specifically designed for analyzing different types of ecological networks - especially antagonistic (food webs, host-parasite), mutualistic (plant-pollinator, plant-fungus, etc) and competitive networks, as well as their variability in time and space. Statistical models are developed to describe and understand the mechanisms that determine species interactions, and to decipher the organization of these (multi-layer) ecological networks.
Imports: stats, igraph, rdiversity, Matrix.utils
LinkingTo:
License: GPL-3
URL: https://plmlab.math.cnrs.fr/econetproject/econetwork
NeedsCompilation: no
Packaged: 2019-01-09 10:58:04 UTC; vmiele
Repository: CRAN
Date/Publication: 2019-01-11 17:40:09 UTC

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New package BMTME with initial version 1.0.4
Package: BMTME
Title: Bayesian Multi-Trait Multi-Environment for Genomic Selection Analysis
Version: 1.0.4
Date: 2018-12-25
Language: en-US
Authors@R: c(person("Francisco Javier", "Luna-Vazquez", email = "frahik@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5370-7152")), person("Fernando H.", "Toledo", role = "aut"), person("Osval Antonio", "Montesinos-Lopez", email= "oamontes1@ucol.mx", role = "aut", comment = c(ORCID = "0000-0002-3973-6547")), person("Abelardo", "Montesinos-Lopez", role = "aut"), person("Jose", "Crossa", role = "aut", comment = c(ORCID = "0000-0001-9429-5855")))
Maintainer: Francisco Javier Luna-Vazquez <frahik@gmail.com>
Description: Genomic selection and prediction models with the capacity to use multiple traits and environments, through ready-to-use Bayesian models. It consists a group of functions that help to create regression models for some genomic models proposed by Montesinos-López, et al. (2016) <doi:10.1534/g3.116.032359> also in Montesinos-López et al. (2018) <doi:10.1534/g3.118.200728> and Montesinos-López et al. (2018) <doi:10.2134/agronj2018.06.0362>.
Depends: R (>= 3.0.0)
License: LGPL-3
Encoding: UTF-8
LazyData: true
Type: Package
RoxygenNote: 6.1.1
URL: https://github.com/frahik/BMTME
BugReports: https://github.com/frahik/BMTME/issues/new
NeedsCompilation: yes
Collate: BME.R BMTME.R BMTME_Package.R BMORS.R BMORSEnv.R cholesky.R datasets.R detectCore.R RandomPartition.R RcppExports.R utils.R
Imports: BGLR, doSNOW, dplyr, foreach, matrixcalc, mvtnorm, progress, snow, tidyr
LinkingTo: Rcpp, RcppArmadillo
SystemRequirements: C++11
Suggests: covr, knitr, rmarkdown, testthat,
VignetteBuilder: knitr
Packaged: 2019-01-06 17:58:50 UTC; frahik
Author: Francisco Javier Luna-Vazquez [aut, cre] (<https://orcid.org/0000-0002-5370-7152>), Fernando H. Toledo [aut], Osval Antonio Montesinos-Lopez [aut] (<https://orcid.org/0000-0002-3973-6547>), Abelardo Montesinos-Lopez [aut], Jose Crossa [aut] (<https://orcid.org/0000-0001-9429-5855>)
Repository: CRAN
Date/Publication: 2019-01-11 17:20:10 UTC

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New package voronoiTreemap with initial version 0.2.0
Package: voronoiTreemap
Type: Package
Title: Voronoi Treemaps with Added Interactivity by Shiny
Version: 0.2.0
Date: 2019-01-08
Authors@R: c( person("Alexander", "Kowarik", email = "alexander.kowarik@statistik.gv.at", role = c("aut","cre"), comment=c(ORCID="0000-0001-8598-4130")), person("Bernhard", "Meindl", email = "bernhard.meindl@statistik.gv.at", role = c("aut")), person("Malaver", "Vojvodic", email = "mmala027@uottawa.ca", role = c("aut")), person("Mike", "Bostock", role = c("aut", "cph"), comment = "d3.js library, http://d3js.org"), person("Franck", "Lebeau", role = c("aut", "cph"), comment = "d3-voronoi-treemap library, https://github.com/Kcnarf/d3-voronoi-treemap"))
Description: The d3.js framework with the plugins d3-voronoi-map, d3-voronoi-treemap and d3-weighted-voronoi are used to generate Voronoi treemaps in R and in a shiny application. The computation of the Voronoi treemaps are based on Nocaj and Brandes (2012) <doi:10.1111/j.1467-8659.2012.03078.x>.
URL: https://github.com/uRosConf/voronoiTreemap
License: GPL-3
Imports: data.tree,rlang,htmlwidgets,shiny,shinyjs,DT
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: rmarkdown, scales, testthat
NeedsCompilation: no
Packaged: 2019-01-08 13:14:29 UTC; kowarik
Author: Alexander Kowarik [aut, cre] (<https://orcid.org/0000-0001-8598-4130>), Bernhard Meindl [aut], Malaver Vojvodic [aut], Mike Bostock [aut, cph] (d3.js library, http://d3js.org), Franck Lebeau [aut, cph] (d3-voronoi-treemap library, https://github.com/Kcnarf/d3-voronoi-treemap)
Maintainer: Alexander Kowarik <alexander.kowarik@statistik.gv.at>
Repository: CRAN
Date/Publication: 2019-01-11 17:00:03 UTC

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Package pixiedust updated to version 0.8.6 with previous version 0.8.5 dated 2018-07-16

Title: Tables so Beautifully Fine-Tuned You Will Believe It's Magic
Description: The introduction of the 'broom' package has made converting model objects into data frames as simple as a single function. While the 'broom' package focuses on providing tidy data frames that can be used in advanced analysis, it deliberately stops short of providing functionality for reporting models in publication-ready tables. 'pixiedust' provides this functionality with a programming interface intended to be similar to 'ggplot2's system of layers with fine tuned control over each cell of the table. Options for output include printing to the console and to the common markdown formats (markdown, HTML, and LaTeX). With a little 'pixiedust' (and happy thoughts) tables can really fly.
Author: Benjamin Nutter [aut, cre], David Kretch [ctb]
Maintainer: Benjamin Nutter <benjamin.nutter@gmail.com>

Diff between pixiedust versions 0.8.5 dated 2018-07-16 and 0.8.6 dated 2019-01-11

 DESCRIPTION                           |    8 +--
 MD5                                   |   82 +++++++++++++++++-----------------
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 42 files changed, 285 insertions(+), 220 deletions(-)

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New package pcLasso with initial version 1.0
Package: pcLasso
Type: Package
Title: Principal Components Lasso
Version: 1.0
Imports: svd
Author: Jerome Friedman, Kenneth Tay, Robert Tibshirani
Maintainer: Rob Tibshirani <tibs@stanford.edu>
Description: A method for fitting the entire regularization path of the principal components lasso for linear and logistic regression models. The algorithm uses cyclic coordinate descent in a path-wise fashion. See URL below for more information on the algorithm. See Tay, K., Friedman, J. ,Tibshirani, R., (2014) 'Principal component-guided sparse regression' <arXiv:1810.04651>.
License: GPL-3
URL: https://arxiv.org/abs/1810.04651
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-01-08 15:18:48 UTC; tibs
Repository: CRAN
Date/Publication: 2019-01-11 17:00:06 UTC

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New package MeTo with initial version 0.1.0
Package: MeTo
Type: Package
Title: Meteorological Tools
Version: 0.1.0
Maintainer: Ullrich Dettmann <ullrich.dettmann@thuenen.de>
Authors@R: c(person('Ullrich', 'Dettmann', email = 'ullrich.dettmann@thuenen.de', role = c('aut', 'cre')), person('R.', 'Grimma', role = 'aut'))
Description: Meteorological Tools following the FAO56 irrigation paper of Allen et al. (1998) [1]. Functions for calculating: reference evapotranspiration (ETref), extraterrestrial radiation (Ra), net radiation (Rn), saturation vapor pressure (satVP), global radiation (Rs), soil heat flux (G), daylight hours, and more. [1] Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, 300(9).
BugReports: https://bitbucket.org/UlliD/meto/issues
Imports: lubridate
License: GPL (>= 2)
Depends: R (>= 3.3.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-01-08 16:42:05 UTC; ulli
Author: Ullrich Dettmann [aut, cre], R. Grimma [aut]
Repository: CRAN
Date/Publication: 2019-01-11 17:00:16 UTC

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Package HydeNet updated to version 0.10.9 with previous version 0.10.8 dated 2018-07-19

Title: Hybrid Bayesian Networks Using R and JAGS
Description: Facilities for easy implementation of hybrid Bayesian networks using R. Bayesian networks are directed acyclic graphs representing joint probability distributions, where each node represents a random variable and each edge represents conditionality. The full joint distribution is therefore factorized as a product of conditional densities, where each node is assumed to be independent of its non-descendents given information on its parent nodes. Since exact, closed-form algorithms are computationally burdensome for inference within hybrid networks that contain a combination of continuous and discrete nodes, particle-based approximation techniques like Markov Chain Monte Carlo are popular. We provide a user-friendly interface to constructing these networks and running inference using the 'rjags' package. Econometric analyses (maximum expected utility under competing policies, value of information) involving decision and utility nodes are also supported.
Author: Jarrod E. Dalton <daltonj@ccf.org> and Benjamin Nutter <benjamin.nutter@gmail.com>
Maintainer: Benjamin Nutter <benjamin.nutter@gmail.com>

Diff between HydeNet versions 0.10.8 dated 2018-07-19 and 0.10.9 dated 2019-01-11

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 21 files changed, 231 insertions(+), 143 deletions(-)

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New package GMSimpute with initial version 0.0.1.0
Package: GMSimpute
Title: Generalized Mass Spectrum Missing Peaks Abundance Imputation
Version: 0.0.1.0
Authors@R: person("Qian", "Li", email = "qian.li10000@gmail.com", role = c("aut", "cre"))
Description: Two-Step Lasso (TS-Lasso) and compound minimum methods to recover the abundance of missing peaks in mass spectrum analysis. TS-Lasso is an imputation method that handles various types of missing peaks simultaneously. This package provides the procedure to generate missing peaks (or data) for simulation study, as well as a tool to estimate and visualize the proportion of missing at random.
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: utils, glmnet, ggplot2, reshape2
NeedsCompilation: no
Packaged: 2019-01-06 14:16:04 UTC; liq
Author: Qian Li [aut, cre]
Maintainer: Qian Li <qian.li10000@gmail.com>
Repository: CRAN
Date/Publication: 2019-01-11 17:00:25 UTC

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Package glmmTMB updated to version 0.2.3 with previous version 0.2.2.0 dated 2018-07-03

Title: Generalized Linear Mixed Models using Template Model Builder
Description: Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.
Author: Arni Magnusson [aut] (<https://orcid.org/0000-0003-2769-6741>), Hans Skaug [aut], Anders Nielsen [aut] (<https://orcid.org/0000-0001-9683-9262>), Casper Berg [aut] (<https://orcid.org/0000-0002-3812-5269>), Kasper Kristensen [aut], Martin Maechler [aut] (<https://orcid.org/0000-0002-8685-9910>), Koen van Bentham [aut], Nafis Sadat [ctb] (<https://orcid.org/0000-0001-5715-616X>), Ben Bolker [aut] (<https://orcid.org/0000-0002-2127-0443>), Mollie Brooks [aut, cre] (<https://orcid.org/0000-0001-6963-8326>)
Maintainer: Mollie Brooks <mollieebrooks@gmail.com>

Diff between glmmTMB versions 0.2.2.0 dated 2018-07-03 and 0.2.3 dated 2019-01-11

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New package FMAdist with initial version 0.1.0
Package: FMAdist
Type: Package
Title: Frequentist Model Averaging Distribution
Version: 0.1.0
Authors@R: c(person("Barry L.", "Nelson", role = c("aut"), email = "nelsonb@northwestern.edu"), person("Xi", "Jiang", role = c("aut","cre"), email = "xijiang2020@u.northwestern.edu"))
Author: Barry L. Nelson [aut], Xi Jiang [aut, cre]
Maintainer: Xi Jiang <xijiang2020@u.northwestern.edu>
Description: Creation of an input model (fitted distribution) via the frequentist model averaging (FMA) approach and generate random-variates from the distribution specified by "myfit" which is the fitted input model via the FMA approach. See W. X. Jiang and B. L. Nelson (2018), "Better Input Modeling via Model Averaging," Proceedings of the 2018 Winter Simulation Conference, IEEE Press, 1575-1586.
Depends: R (>= 3.1.0), stats, utils
Imports: fitdistrplus, STAR, EnvStats, extraDistr, MASS, quadprog
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2018-12-21 21:32:35 UTC; Wendy
Repository: CRAN
Date/Publication: 2019-01-11 16:30:07 UTC

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Package enrichwith updated to version 0.2 with previous version 0.1.1 dated 2018-05-06

Title: Methods to Enrich R Objects with Extra Components
Description: Provides the "enrich" method to enrich list-like R objects with new, relevant components. The current version has methods for enriching objects of class 'family', 'link-glm', 'lm', 'glm' and 'betareg'. The resulting objects preserve their class, so all methods associated with them still apply. The package also provides the 'enriched_glm' function that has the same interface as 'glm' but results in objects of class 'enriched_glm'. In addition to the usual components in a `glm` object, 'enriched_glm' objects carry an object-specific simulate method and functions to compute the scores, the observed and expected information matrix, the first-order bias, as well as model densities, probabilities, and quantiles at arbitrary parameter values. The package can also be used to produce customizable source code templates for the structured implementation of methods to compute new components and enrich arbitrary objects.
Author: Ioannis Kosmidis [aut, cre]
Maintainer: Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>

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New package cPCG with initial version 1.0
Package: cPCG
Type: Package
Title: Efficient and Customized Preconditioned Conjugate Gradient Method for Solving System of Linear Equations
Version: 1.0
Date: 2018-12-30
Author: Yongwen Zhuang
Maintainer: Yongwen Zhuang <zyongwen@umich.edu>
Description: Solves system of linear equations using (preconditioned) conjugate gradient algorithm, with improved efficiency using Armadillo templated 'C++' linear algebra library, and flexibility for user-specified preconditioning method. Please check <https://github.com/styvon/cPCG> for latest updates.
Depends: R (>= 3.0.0)
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.19)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
Encoding: UTF-8
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-12-30 19:47:42 UTC; zyongwen
Repository: CRAN
Date/Publication: 2019-01-11 17:00:10 UTC

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New package CluMP with initial version 0.7
Package: CluMP
Title: Clustering of Micro Panel Data
Version: 0.7
Authors@R: c( person("Jan", "Fojtik", email = "9afojtik@gmail.com", role = c("aut", "cre")), person("Anna", "Grishko", email = "anja.grishko@gmail.com", role = "aut"), person("Lukas", "Sobisek", email = "Lukas.Sobisek@yahoo.com", role = c("aut", "cph", "rev")))
Description: Two-step feature-based clustering method designed for micro panel (longitudinal) data with the artificial panel data generator. See Sobisek, Fojtik, Stachova (2018) <arXiv:1807.05926>.
URL: https://arxiv.org/ftp/arxiv/papers/1807/1807.05926.pdf
Depends: R (>= 3.4.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: MASS, ggplot2 (>= 3.0.0), dplyr (>= 0.7.6), NbClust (>= 3.0), amap (>= 0.8-16), tableone, rlang, stats
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2019-01-08 20:08:44 UTC; 9afoj
Author: Jan Fojtik [aut, cre], Anna Grishko [aut], Lukas Sobisek [aut, cph, rev]
Maintainer: Jan Fojtik <9afojtik@gmail.com>
Repository: CRAN
Date/Publication: 2019-01-11 17:00:28 UTC

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Package clr updated to version 0.1.1 with previous version 0.1.0 dated 2018-12-03

Title: Curve Linear Regression via Dimension Reduction
Description: A new methodology for linear regression with both curve response and curve regressors, which is described in Cho, Goude, Brossat and Yao (2013) <doi:10.1080/01621459.2012.722900> and (2015) <doi:10.1007/978-3-319-18732-7_3>. The key idea behind this methodology is dimension reduction based on a singular value decomposition in a Hilbert space, which reduces the curve regression problem to several scalar linear regression problems.
Author: Amandine Pierrot with contributions and/or help from Qiwei Yao, Haeran Cho, Yannig Goude and Tony Aldon.
Maintainer: Amandine Pierrot <amandine.m.pierrot@gmail.com>

Diff between clr versions 0.1.0 dated 2018-12-03 and 0.1.1 dated 2019-01-11

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Package blocksdesign updated to version 3.3 with previous version 3.2 dated 2018-12-18

Title: Nested and Crossed Block Designs for Factorial, Fractional Factorial and Unstructured Treatment Sets
Description: Constructs D-optimal or near D-optimal nested and crossed block designs for unstructured or general factorial treatment designs. The treatment design, if required, is found from a defined model design formula. The block design is found from a defined set of block factors and is conditional on the defined treatment design. The block factors are added in sequence and each added block factor is optimized conditional on all previously added block factors. The block design can have repeated nesting down to any required depth of nesting with either simple nested blocks or a crossed blocks design at each level of nesting. Outputs include a table showing the allocation of treatments to blocks and tables showing the achieved D-efficiency factors for each block and treatment design.
Author: R. N. Edmondson.
Maintainer: Rodney Edmondson <rodney.edmondson@gmail.com>

Diff between blocksdesign versions 3.2 dated 2018-12-18 and 3.3 dated 2019-01-11

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New package apcf with initial version 0.1.1
Package: apcf
Title: Adapted Pair Correlation Function
Version: 0.1.1
Authors@R: person(given="Robert", family="Nuske", role=c("aut", "cre"), email="robert.nuske@mailbox.org", comment=c(ORCID="0000-0001-9773-2061"))
Description: The adapted pair correlation function transfers the concept of the pair correlation function from point patterns to patterns of objects of finite size and irregular shape (e.g. lakes within a country). This is a reimplementation of the method suggested by Nuske et al. (2009) <doi:10.1016/j.foreco.2009.09.050> using the libraries 'GEOS' and 'GDAL' directly instead of through 'PostGIS'.
License: GPL (>= 3)
URL: https://github.com/rnuske/apcf
BugReports: https://github.com/rnuske/apcf/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3.0)
Imports: Rcpp (>= 0.12), graphics
Suggests: knitr, rmarkdown
LinkingTo: Rcpp
SystemRequirements: C++11, GDAL (>= 2.0.0), GEOS (>= 3.4.0)
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-01-08 16:29:13 UTC; rnuske
Author: Robert Nuske [aut, cre] (<https://orcid.org/0000-0001-9773-2061>)
Maintainer: Robert Nuske <robert.nuske@mailbox.org>
Repository: CRAN
Date/Publication: 2019-01-11 16:50:02 UTC

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Package pmhtutorial updated to version 1.4 with previous version 1.3 dated 2018-10-18

Title: Minimal Working Examples for Particle Metropolis-Hastings
Description: Routines for state estimate in a linear Gaussian state space model and a simple stochastic volatility model using particle filtering. Parameter inference is also carried out in these models using the particle Metropolis-Hastings algorithm that includes the particle filter to provided an unbiased estimator of the likelihood. This package is a collection of minimal working examples of these algorithms and is only meant for educational use and as a start for learning to them on your own.
Author: Johan Dahlin
Maintainer: Johan Dahlin <uni@johandahlin.com>

Diff between pmhtutorial versions 1.3 dated 2018-10-18 and 1.4 dated 2019-01-11

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New package mimi with initial version 0.1.0
Package: mimi
Type: Package
Title: Main Effects and Interactions in Mixed and Incomplete Data
Version: 0.1.0
Author: Geneviève Robin
Maintainer: Genevieve Robin <genevieve.robin@polytechnique.edu>
Description: Estimation of main effects and interactions in mixed data sets with missing values. Numeric, binary and count variables are supported. Main effects and interactions are modelled using an exponential family parametric model. Particular examples include the log-linear model for count data and the linear model for numeric data. Estimation is done through a convex program where main effects are assumed sparse and the interactions low-rank. Geneviève Robin, Olga Klopp, Julie Josse, Éric Moulines, Robert Tibshirani (2018) <arXiv:1806.09734>.
Depends: R (>= 2.10)
License: GPL-3
Imports: glmnet, softImpute, stats, ade4, FactoMineR, parallel, doParallel, foreach, data.table
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2019-01-07 09:25:21 UTC; genevieverobin
Repository: CRAN
Date/Publication: 2019-01-11 15:50:02 UTC

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New package KDViz with initial version 1.3
Package: KDViz
Type: Package
Title: Knowledge Domain Visualization
Version: 1.3
Date: 2018-12-27
Author: Andres Palacios
Maintainer: Andres Palacios <anfpalacioscl@unal.edu.co>
Description: Knowledge domain visualization using 'mpa' co-words method as the word clustering method and network graphs with 'D3.js' library as visualization tool.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 2.10)
Imports: htmlwidgets, igraph, mpa, networkD3, rvest, stringr, tm, xml2
LazyData: true
NeedsCompilation: no
Packaged: 2019-01-06 07:58:36 UTC; andre
Repository: CRAN
Date/Publication: 2019-01-11 15:30:02 UTC

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Package VizOR (with last version 0.8-5) was removed from CRAN

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

2016-12-13 0.8-5
2013-11-14 0.7-9

Permanent link
Package states updated to version 0.2.2 with previous version 0.2.1 dated 2018-05-06

Title: Create Panels of Independent States
Description: Create panel data consisting of independent states from 1816 to the present. The package includes the Gleditsch & Ward (G&W) and Correlates of War (COW) lists of independent states, as well as helper functions for working with state panel data and standardizing other data sources to create country-year/month/etc. data.
Author: Andreas Beger [cre, aut] (<https://orcid.org/0000-0003-1883-3169>)
Maintainer: Andreas Beger <adbeger@gmail.com>

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Package RVAideMemoire updated to version 0.9-71 with previous version 0.9-70 dated 2018-11-06

Title: Testing and Plotting Procedures for Biostatistics
Description: Contains miscellaneous functions useful in biostatistics, mostly univariate and multivariate testing procedures with a special emphasis on permutation tests. Many functions intend to simplify user's life by shortening existing procedures or by implementing plotting functions that can be used with as many methods from different packages as possible.
Author: Maxime Herv
Maintainer: Maxime Herv <maxime.herve@univ-rennes1.fr>

Diff between RVAideMemoire versions 0.9-70 dated 2018-11-06 and 0.9-71 dated 2019-01-11

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Package clipr updated to version 0.5.0 with previous version 0.4.1 dated 2018-06-23

Title: Read and Write from the System Clipboard
Description: Simple utility functions to read from and write to the Windows, OS X, and X11 clipboards.
Author: Matthew Lincoln [aut, cre] (<https://orcid.org/0000-0002-4387-3384>), Louis Maddox [ctb], Steve Simpson [ctb], Jennifer Bryan [ctb]
Maintainer: Matthew Lincoln <matthew.d.lincoln@gmail.com>

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Package GGIR updated to version 1.8-1 with previous version 1.7-1 dated 2018-11-25

Title: Raw Accelerometer Data Analysis
Description: A tool to process and analyse data collected with wearable raw acceleration sensors as described in van Hees and colleagues (2014) <doi: 10.1152/japplphysiol.00421.2014> and (2015) <doi: 10.1371/journal.pone.0142533>. The package has been developed and tested for binary data from 'GENEActiv' <https://www.activinsights.com/> and GENEA devices (not for sale), .csv-export data from 'Actigraph' <http://actigraphcorp.com> devices, and .cwa and .wav-format data from 'Axivity' <https://axivity.com/product/ax3>. These devices are currently widely used in research on human daily physical activity.
Author: Vincent T van Hees [aut, cre], Zhou Fang [ctb], Jing Hua Zhao [ctb], Joe Heywood [ctb], Evgeny Mirkes [ctb], Severine Sabia [ctb], Joan Capdevila Pujol [ctb], Jairo H Migueles [ctb]
Maintainer: Vincent T van Hees <vincentvanhees@gmail.com>

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Package dynamichazard updated to version 0.6.3 with previous version 0.6.2 dated 2019-01-10

Title: Dynamic Hazard Models using State Space Models
Description: Contains functions that lets you fit dynamic hazard models using state space models. The first implemented model is described in Fahrmeir (1992) <doi:10.1080/01621459.1992.10475232> and Fahrmeir (1994) <doi:10.1093/biomet/81.2.317>. Extensions hereof are available where the Extended Kalman filter is replaced by an unscented Kalman filter and other options including particle filters. The implemented particle filters support more general state space models.
Author: Benjamin Christoffersen [cre, aut], Alan Miller [cph], Anthony Williams [cph], Boost developers [cph], R-core [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>

Diff between dynamichazard versions 0.6.2 dated 2019-01-10 and 0.6.3 dated 2019-01-11

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Package suropt updated to version 0.1.1 with previous version 0.1.0 dated 2018-11-26

Title: Surrogate-Based Optimization
Description: Multi-Objective optimization based on surrogate models. Important functions: build_surmodel, train_hego, train_mego, train_sme.
Author: Adriano Passos [aut, cre], Marco Luersen [ctb]
Maintainer: Adriano Passos <adriano.utfpr@gmail.com>

Diff between suropt versions 0.1.0 dated 2018-11-26 and 0.1.1 dated 2019-01-11

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Package RDFTensor updated to version 1.1 with previous version 1.0 dated 2018-11-27

Title: Different Tensor Factorization (Decomposition) Techniques for RDF Tensors (Three-Mode-Tensors)
Description: Different Tensor Factorization techniques suitable for RDF Tensors. RDF Tensors are three-mode-tensors, binary tensors and usually very sparse. Currently implemented methods are 'RESCAL' Maximilian Nickel, Volker Tresp, and Hans-Peter Kriegel (2012) <doi:10.1145/2187836.2187874>, 'NMU' Daniel D. Lee and H. Sebastian Seung (1999) <doi:10.1038/44565>, 'ALS', Alternating Least Squares 'parCube' Papalexakis, Evangelos, C. Faloutsos, and N. Sidiropoulos (2012) <doi:10.1007/978-3-642-33460-3_39>, 'CP_APR' C. Chi and T. G. Kolda (2012) <doi:10.1137/110859063>. The code is mostly converted from MATLAB and Python implementations of these methods. The package also contains functions to get Boolean (Binary) transformation of the real-number-decompositions. These methods also are for general tensors, so with few modifications they can be applied for other types of tensor.
Author: Abdelmoneim Amer Desouki
Maintainer: Abdelmoneim Amer Desouki <desouki@mail.upb.de>

Diff between RDFTensor versions 1.0 dated 2018-11-27 and 1.1 dated 2019-01-11

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Package mdmb updated to version 1.2-4 with previous version 1.1-51 dated 2019-01-07

Title: Model Based Treatment of Missing Data
Description: Contains model-based treatment of missing data for regression models with missing values in covariates or the dependent variable using maximum likelihood or Bayesian estimation (Ibrahim et al., 2005; <doi:10.1198/016214504000001844>). The regression model can be nonlinear (e.g., interaction effects, quadratic effects or B-spline functions). Multilevel models with missing data in predictors are available for Bayesian estimation. Substantive-model compatible multiple imputation can be also conducted.
Author: Alexander Robitzsch [aut, cre], Oliver Luedtke [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between mdmb versions 1.1-51 dated 2019-01-07 and 1.2-4 dated 2019-01-11

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Package jointseg updated to version 1.0.2 with previous version 1.0.1 dated 2017-11-28

Title: Joint Segmentation of Multivariate (Copy Number) Signals
Description: Methods for fast segmentation of multivariate signals into piecewise constant profiles and for generating realistic copy-number profiles. A typical application is the joint segmentation of total DNA copy numbers and allelic ratios obtained from Single Nucleotide Polymorphism (SNP) microarrays in cancer studies. The methods are described in Pierre-Jean, Rigaill and Neuvial (2015) <doi:10.1093/bib/bbu026>.
Author: Morgane Pierre-Jean [aut, cre], Pierre Neuvial [aut], Guillem Rigaill [aut]
Maintainer: Morgane Pierre-Jean <mpierrejean.pro@gmail.com>

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Package FLSSS updated to version 8.5.2 with previous version 8.3 dated 2019-01-08

Title: Mining Rigs for Specialized Subset Sum, Multi-Subset Sum, Multidimensional Subset Sum, Multidimensional Knapsack, Generalized Assignment Problems
Description: Specialized solvers for combinatorial optimization problems in the Subset Sum family. These solvers differ from the mainstream in the options of (i) restricting subset size, (ii) bounding subset elements, (iii) mining real-value sets with predefined subset sum errors, and (iv) finding one or more subsets in limited time. A novel algorithm for mining the one-dimensional Subset Sum induced algorithms for the multi-Subset Sum and the multidimensional Subset Sum. The latter decomposes the problem in a novel approach, and the multi-threaded framework offers exact algorithms to the multidimensional Knapsack and the Generalized Assignment problems. Package updates include (a) renewed implementation of the multi-Subset Sum, multidimensional Knapsack and Generalized Assignment solvers; (b) availability of bounding solution space in the multidimensional Subset Sum; (c) fundamental data structure and architectural changes for enhanced cache locality and better chance of SIMD vectorization; (d) an option of mapping real-domain problems to the integer domain with user-controlled precision loss, and those integers are further zipped non-uniformly in 64-bit buffers. Arithmetic on compressed integers is done by bit-manipulation and the design has virtually zero speed lag relative to normal integers arithmetic. The consequent reduction in dimensionality may yield substantial acceleration. Compilation with g++ '-Ofast' is recommended. See package vignette (<arXiv:1612.04484v3>) for details. Functions prefixed with 'aux' (auxiliary) are or will be implementations of existing foundational or cutting-edge algorithms for solving optimization problems of interest.
Author: Charlie Wusuo Liu
Maintainer: Charlie Wusuo Liu <liuwusuo@gmail.com>

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Package epubr updated to version 0.6.0 with previous version 0.5.0 dated 2018-10-22

Title: Read EPUB File Metadata and Text
Description: Provides functions supporting the reading and parsing of internal e-book content from EPUB files. The 'epubr' package provides functions supporting the reading and parsing of internal e-book content from EPUB files. E-book metadata and text content are parsed separately and joined together in a tidy, nested tibble data frame. E-book formatting is not completely standardized across all literature. It can be challenging to curate parsed e-book content across an arbitrary collection of e-books perfectly and in completely general form, to yield a singular, consistently formatted output. Many EPUB files do not even contain all the same pieces of information in their respective metadata. EPUB file parsing functionality in this package is intended for relatively general application to arbitrary EPUB e-books. However, poorly formatted e-books or e-books with highly uncommon formatting may not work with this package. There may even be cases where an EPUB file has DRM or some other property that makes it impossible to read with 'epubr'. Text is read 'as is' for the most part. The only nominal changes are minor substitutions, for example curly quotes changed to straight quotes. Substantive changes are expected to be performed subsequently by the user as part of their text analysis. Additional text cleaning can be performed at the user's discretion, such as with functions from packages like 'tm' or 'qdap'.
Author: Matthew Leonawicz [aut, cre] (<https://orcid.org/0000-0001-9452-2771>)
Maintainer: Matthew Leonawicz <matt_leonawicz@esource.com>

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Package ClusterR updated to version 1.1.8 with previous version 1.1.7 dated 2018-12-09

Title: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering
Description: Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and affinity propagation clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of 'RcppArmadillo' to speed up the computationally intensive parts of the functions. For more information, see (i) "Clustering in an Object-Oriented Environment" by Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software, <doi:10.18637/jss.v001.i04>; (ii) "Web-scale k-means clustering" by D. Sculley (2010), ACM Digital Library, <doi:10.1145/1772690.1772862>; (iii) "Armadillo: a template-based C++ library for linear algebra" by Sanderson et al (2016), The Journal of Open Source Software, <doi:10.21105/joss.00026>; (iv) "Clustering by Passing Messages Between Data Points" by Brendan J. Frey and Delbert Dueck, Science 16 Feb 2007: Vol. 315, Issue 5814, pp. 972-976, <doi:10.1126/science.1136800>.
Author: Lampros Mouselimis [aut, cre], Conrad Sanderson [cph] (Author of the C++ Armadillo library), Ryan Curtin [cph] (Author of the C++ Armadillo library), Siddharth Agrawal [cph] (Author of the C code of the Mini-Batch-Kmeans algorithm (https://github.com/siddharth-agrawal/Mini-Batch-K-Means)), Brendan Frey [cph] (Author of the matlab code of the Affinity propagation algorithm (for commercial use please contact the author)), Delbert Dueck [cph] (Author of the matlab code of the Affinity propagation algorithm)
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>

Diff between ClusterR versions 1.1.7 dated 2018-12-09 and 1.1.8 dated 2019-01-11

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Package RLumShiny updated to version 0.2.2 with previous version 0.2.1 dated 2018-06-18

Title: 'Shiny' Applications for the R Package 'Luminescence'
Description: A collection of 'shiny' applications for the R package 'Luminescence'. These mainly, but not exclusively, include applications for plotting chronometric data from e.g. luminescence or radiocarbon dating. It further provides access to bootstraps tooltip and popover functionality and contains the 'jscolor.js' library with a custom 'shiny' output binding.
Author: Christoph Burow [aut, cre] (<https://orcid.org/0000-0002-5023-4046>), Urs Tilmann Wolpert [aut], Sebastian Kreutzer [aut] (<https://orcid.org/0000-0002-0734-2199>), R Luminescence Package Team [ctb], Jan Odvarko [cph] (jscolor.js in www/jscolor), AnalytixWare [cph] (ShinySky package), RStudio [cph] (chooser_inputBinding.js in www/ and chooser.R in R/)
Maintainer: Christoph Burow <christoph.burow@uni-koeln.de>

Diff between RLumShiny versions 0.2.1 dated 2018-06-18 and 0.2.2 dated 2019-01-11

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Package pinp updated to version 0.0.7 with previous version 0.0.6 dated 2018-07-17

Title: 'pinp' is not 'PNAS'
Description: A 'PNAS'-alike style for 'rmarkdown', derived from the 'Proceedings of the National Academy of Sciences of the United States of America' ('PNAS', see <https://www.pnas.org>) 'LaTeX' style, and adapted for use with 'markdown' and 'pandoc'.
Author: Dirk Eddelbuettel and James Balamuta
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between pinp versions 0.0.6 dated 2018-07-17 and 0.0.7 dated 2019-01-11

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Package pkgcache updated to version 1.0.3 with previous version 1.0.2 dated 2018-12-31

Title: Cache 'CRAN'-Like Metadata and R Packages
Description: Metadata and package cache for CRAN-like repositories. This is a utility package to be used by package management tools that want to take advantage of caching.
Author: Gábor Csárdi [aut, cre]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

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Package imagerExtra updated to version 1.3.1 with previous version 1.3.0 dated 2018-11-28

Title: Extra Image Processing Library Based on 'imager'
Description: Providing advanced functions for image processing based on the package 'imager'.
Author: Shota Ochi [aut, cre], Guoshen Yu [ctb, cph], Guillermo Sapiro [ctb, cph], Catalina Sbert [ctb, cph], Image Processing On Line [cph], Pascal Getreuer [ctb, cph]
Maintainer: Shota Ochi <shotaochi1990@gmail.com>

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Package HiClimR updated to version 2.1.3 with previous version 2.1.1 dated 2019-01-03

Title: Hierarchical Climate Regionalization
Description: A tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering. It adds several features and a new clustering method (called, 'regional' linkage) to hierarchical clustering in R ('hclust' function in 'stats' library): data regridding, coarsening spatial resolution, geographic masking, contiguity-constrained clustering, data filtering by mean and/or variance thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function with preliminary big data support, different clustering methods, hybrid hierarchical clustering, multivariate clustering (MVC), cluster validation, visualization of regionalization results, and exporting region map and mean timeseries into NetCDF-4 file.
Author: Hamada S. Badr [aut, cre], Benjamin F. Zaitchik [aut], Amin K. Dezfuli [aut]
Maintainer: Hamada S. Badr <badr@jhu.edu>

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Package blavaan updated to version 0.3-4 with previous version 0.3-3 dated 2018-10-31

Title: Bayesian Latent Variable Analysis
Description: Fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models.
Author: Edgar Merkle [aut, cre] (<https://orcid.org/0000-0001-7158-0653>), Yves Rosseel [aut], Mauricio Garnier-Villarreal [ctb], Terrence D. Jorgensen [ctb], Huub Hoofs [ctb], Rens van de Schoot [ctb]
Maintainer: Edgar Merkle <merklee@missouri.edu>

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Package rsoi updated to version 0.5.0 with previous version 0.4.0 dated 2018-12-02

Title: Import Various Northern and Southern Hemisphere Climate Indices
Description: Downloads Southern Oscillation Index, Oceanic Nino Index, North Pacific Gyre Oscillation data, North Atlantic Oscillation and Arctic Oscillation. Data sources are described in the README file.
Author: Sam Albers [aut, cre] (<https://orcid.org/0000-0002-9270-7884>)
Maintainer: Sam Albers <sam.albers@gmail.com>

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Package dartR (with last version 1.1.6) was removed from CRAN

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2018-11-26 1.1.6
2018-05-11 1.0.5

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Package LVGP updated to version 2.1.5 with previous version 2.1.4 dated 2018-11-14

Title: Latent Variable Gaussian Process Modeling with Qualitative and Quantitative Input Variables
Description: Fit response surfaces for datasets with latent-variable Gaussian process modeling, predict responses for new inputs, and plot latent variables locations in the latent space (only 1D or 2D). The input variables of the datasets can be quantitative, qualitative/categorical or mixed. The output variable of the datasets is a scalar (quantitative). The optimization of the likelihood function is done using a successive approximation/relaxation algorithm similar to another GP modeling package "GPM". The modeling method is published in "A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors" by Yichi Zhang, Siyu Tao, Wei Chen, and Daniel W. Apley (2018) <arXiv:1806.07504>. The package is developed in IDEAL of Northwestern University.
Author: Siyu Tao, Yichi Zhang, Daniel W. Apley, Wei Chen
Maintainer: Siyu Tao <siyutao2020@u.northwestern.edu>

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Package PopGenReport (with last version 3.0.0) was removed from CRAN

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2017-02-01 3.0.0
2016-05-11 2.2.2
2015-07-08 2.2
2014-10-27 2.1
2014-07-04 2.0
2014-03-03 1.8
2013-12-12 1.6.6
2013-09-03 1.6
2013-05-22 1.01
2012-11-28 0.96

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Package DirichletReg updated to version 0.6-3.1 with previous version 0.6-3 dated 2015-11-12

Title: Dirichlet Regression in R
Description: Implements Dirichlet regression models in R.
Author: Marco Johannes Maier [cre, aut]
Maintainer: ORPHANED

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Package zstdr (with last version 0.1.1) was removed from CRAN

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2017-06-06 0.1.1
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Package mlmm.gwas (with last version 1.0.4) was removed from CRAN

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2018-07-19 1.0.4
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Package RcppHoney (with last version 0.1.7) was removed from CRAN

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2017-11-18 0.1.7
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2016-11-30 0.1.4
2016-11-26 0.1.2
2016-07-31 0.1.1
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Package similr (with last version 1.0.0) was removed from CRAN

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2018-11-19 1.0.0

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

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2018-07-12 1.2
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Package memor (with last version 0.1.1) was removed from CRAN

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2018-07-10 0.1.1

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Package mRMRe (with last version 2.0.7) was removed from CRAN

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2017-11-03 2.0.7
2014-08-19 2.0.5
2013-12-10 2.0.3
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2013-05-23 2.0.2
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Package MMPPsampler (with last version 1.0) was removed from CRAN

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2018-05-24 1.0

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Package DEVis (with last version 1.0.0) was removed from CRAN

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2018-10-16 1.0.0

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Package mnlogit (with last version 1.2.5) was removed from CRAN

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2016-11-08 1.2.5
2015-10-16 1.2.4
2015-09-12 1.2.3
2015-06-05 1.2.2
2015-05-13 1.2.1
2014-09-09 1.2.0
2014-04-10 1.1.1
2014-03-21 1.1.0
2013-12-08 1.0.1
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Package germinationmetrics (with last version 0.1.2) was removed from CRAN

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2018-10-31 0.1.2
2018-10-16 0.1.1.1
2018-07-26 0.1.1
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Package pgdraw (with last version 1.0) was removed from CRAN

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2018-07-13 1.0

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2018-12-16 0.2.0

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