Sun, 06 May 2018

Package tuber updated to version 0.9.7 with previous version 0.9.5 dated 2018-03-01

Title: Client for the YouTube API
Description: Get comments posted on YouTube videos, information on how many times a video has been liked, search for videos with particular content, and much more. You can also scrape captions from a few videos. To learn more about the YouTube API, see <https://developers.google.com/youtube/v3/>.
Author: Gaurav Sood [aut, cre], Kate Lyons [ctb], John Muschelli [ctb]
Maintainer: Gaurav Sood <gsood07@gmail.com>

Diff between tuber versions 0.9.5 dated 2018-03-01 and 0.9.7 dated 2018-05-06

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Package SemiCompRisks updated to version 3.1 with previous version 3.0 dated 2018-03-30

Title: Hierarchical Models for Parametric and Semi-Parametric Analyses of Semi-Competing Risks Data
Description: Hierarchical multistate models are considered to perform the analysis of independent/clustered semi-competing risks data. The package allows to choose the specification for model components from a range of options giving users substantial flexibility, including: accelerated failure time or proportional hazards regression models; parametric or non-parametric specifications for baseline survival functions and cluster-specific random effects distribution; a Markov or semi-Markov specification for terminal event following non-terminal event. While estimation is mainly performed within the Bayesian paradigm, the package also provides the maximum likelihood estimation approach for several parametric models. The package also includes functions for univariate survival analysis as complementary analysis tools.
Author: Kyu Ha Lee, Catherine Lee, Danilo Alvares, and Sebastien Haneuse
Maintainer: Kyu Ha Lee <klee@hsph.harvard.edu>

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Package mbir updated to version 1.3.1 with previous version 1.3 dated 2018-04-28

Title: Magnitude-Based Inferences
Description: Allows practitioners and researchers a wholesale approach for deriving magnitude-based inferences from raw data. A major goal of 'mbir' is to programmatically detect appropriate statistical tests to run in lieu of relying on practitioners to determine correct stepwise procedures independently.
Author: Kyle Peterson [aut, cre], Aaron Caldwell [aut]
Maintainer: Kyle Peterson <petersonkdon@gmail.com>

Diff between mbir versions 1.3 dated 2018-04-28 and 1.3.1 dated 2018-05-06

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Package gdistance updated to version 1.2-2 with previous version 1.2-1 dated 2017-02-26

Title: Distances and Routes on Geographical Grids
Description: Calculate distances and routes on geographic grids.
Author: Jacob van Etten
Maintainer: Jacob van Etten <jacobvanetten@yahoo.com>

Diff between gdistance versions 1.2-1 dated 2017-02-26 and 1.2-2 dated 2018-05-06

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Package imagine updated to version 1.4.0 with previous version 1.3.1 dated 2017-07-08

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

Diff between imagine versions 1.3.1 dated 2017-07-08 and 1.4.0 dated 2018-05-06

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Package CytobankAPI updated to version 1.1.2 with previous version 1.1.0 dated 2017-08-10

Title: Cytobank API Wrapper for R
Description: Tools to interface with Cytobank's API via R, organized by various endpoints that represent various areas of Cytobank functionality. Learn more about Cytobank at <https://www.cytobank.org>.
Author: Preston Ng [aut, cre], Chris Ciccolella [aut], Katherine Drake [aut]
Maintainer: Preston Ng <preston@cytobank.org>

Diff between CytobankAPI versions 1.1.0 dated 2017-08-10 and 1.1.2 dated 2018-05-06

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Package sm updated to version 2.2-5.5 with previous version 2.2-5.4 dated 2014-01-16

Title: Smoothing Methods for Nonparametric Regression and Density Estimation
Description: This is software linked to the book 'Applied Smoothing Techniques for Data Analysis - The Kernel Approach with S-Plus Illustrations' Oxford University Press.
Author: Adrian Bowman and Adelchi Azzalini. Ported to R by B. D. Ripley <ripley@stats.ox.ac.uk> up to version 2.0, version 2.1 by Adrian Bowman and Adelchi Azzalini, version 2.2 by Adrian Bowman.
Maintainer: Adrian Bowman <adrian.bowman@glasgow.ac.uk>

Diff between sm versions 2.2-5.4 dated 2014-01-16 and 2.2-5.5 dated 2018-05-06

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New package lmeVarComp with initial version 1.1
Package: lmeVarComp
Type: Package
Title: Testing for a Subset of Variance Components in Linear Mixed Models
Version: 1.1
Date: 2018-04-13
Authors@R: c(person("Yichi", "Zhang", role = c("aut", "cre"), email = "yzhang52@ncsu.edu"))
Author: Yichi Zhang [aut, cre]
Maintainer: Yichi Zhang <yzhang52@ncsu.edu>
Imports: stats
Depends: R (>= 3.0.0)
Description: Test zero variance components in linear mixed models and test additivity in nonparametric regression using the restricted likelihood ratio test and the generalized F-test. Details can be found at Zhang et al (2016) <doi:10.1002/cjs.11295>.
License: GPL (>= 2)
ByteCompile: yes
NeedsCompilation: yes
Packaged: 2018-05-06 18:50:44 UTC; Yichi
Repository: CRAN
Date/Publication: 2018-05-06 21:58:13 UTC

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Package cplm updated to version 0.7-6 with previous version 0.7-5 dated 2016-12-05

Title: Compound Poisson Linear Models
Description: Likelihood-based and Bayesian methods for various compound Poisson linear models.
Author: Yanwei (Wayne) Zhang
Maintainer: Yanwei (Wayne) Zhang <actuary_zhang@hotmail.com>

Diff between cplm versions 0.7-5 dated 2016-12-05 and 0.7-6 dated 2018-05-06

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New package uncertainty with initial version 0.2.0
Package: uncertainty
Type: Package
Title: Uncertainty Estimation and Contribution Analysis
Version: 0.2.0
Date: 2018-05-04
Author: Hugo Gasca-Aragon
Maintainer: Hugo Gasca-Aragon <hugo_gasca_aragon@hotmail.com>
Description: Implements the Gaussian method of first and second order, the Kragten numerical method and the Monte Carlo simulation method for uncertainty estimation and analysis.
Depends: graphics (>= 3.4.0), stats (>= 3.4.0), mvtnorm (>= 0.9), triangle (>= 0.7), R (>= 3.4.0)
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-05-06 13:45:18 UTC; Hugo Gasca
Repository: CRAN
Date/Publication: 2018-05-06 20:15:11 UTC

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Package RPostgres updated to version 1.1.1 with previous version 1.1.0 dated 2018-04-06

Title: 'Rcpp' Interface to 'PostgreSQL'
Description: Fully 'DBI'-compliant 'Rcpp'-backed interface to 'PostgreSQL' <https://www.postgresql.org/>, an open-source relational database.
Author: Hadley Wickham [aut], Jeroen Ooms [aut], Kirill Müller [aut, cre] (<https://orcid.org/0000-0002-1416-3412>), RStudio [cph], R Consortium [fnd], Tomoaki Nishiyama [ctb] (Code for encoding vectors into strings derived from RPostgreSQL)
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

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Package RMariaDB updated to version 1.0.6 with previous version 1.0.5 dated 2018-04-03

Title: Database Interface and 'MariaDB' Driver
Description: Implements a 'DBI'-compliant interface to 'MariaDB' (<https://mariadb.org/>) and 'MySQL' (<https://www.mysql.com/>) databases.
Author: Kirill Müller [aut, cre] (<https://orcid.org/0000-0002-1416-3412>), Jeroen Ooms [aut] (<https://orcid.org/0000-0002-4035-0289>), David James [aut], Saikat DebRoy [aut], Hadley Wickham [aut], Jeffrey Horner [aut], R Consortium [fnd], RStudio [cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

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Package RcppMsgPack updated to version 0.2.2 with previous version 0.2.1 dated 2018-01-16

Title: 'MsgPack' C++ Header Files and Interface Functions for R
Description: 'MsgPack' header files are provided for use by R packages, along with the ability to access, create and alter 'MsgPack' objects directly from R. 'MsgPack' is an efficient binary serialization format. It lets you exchange data among multiple languages like 'JSON' but it is faster and smaller. Small integers are encoded into a single byte, and typical short strings require only one extra byte in addition to the strings themselves. This package provides headers from the 'msgpack-c' implementation for C and C++(11) for use by R, particularly 'Rcpp'. The included 'msgpack-c' headers are licensed under the Boost Software License (Version 1.0); the code added by this package as well the R integration are licensed under the GPL (>= 2). See the files 'COPYRIGHTS' and 'AUTHORS' for a full list of copyright holders and contributors to 'msgpack-c'.
Author: Travers Ching and Dirk Eddelbuettel; the authors and contributors of MsgPack
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package psych updated to version 1.8.4 with previous version 1.8.3.3 dated 2018-03-30

Title: Procedures for Psychological, Psychometric, and Personality Research
Description: A general purpose toolbox for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Functions for simulating and testing particular item and test structures are included. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometric theory as well as publications in personality research. For more information, see the <https://personality-project.org/r> web page.
Author: William Revelle [aut, cre] (<https://orcid.org/0000-0003-4880-9610>)
Maintainer: William Revelle <revelle@northwestern.edu>

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Package miceFast updated to version 0.2.3 with previous version 0.1.0 dated 2018-04-16

Title: Fast Imputations Using 'Rcpp' and 'Armadillo'
Description: Fast imputations under the object-oriented programming paradigm. There was used quantitative models with a closed-form solution. Thus package is based on linear algebra operations. The biggest improvement in time performance could be achieve for a calculation where a grouping variable have to be used. A single evaluation of a quantitative model for the multiple imputations is another major enhancement. Moreover there are offered a few functions built to work with popular R packages such as 'data.table'.
Author: Maciej Nasinski [aut, cre]
Maintainer: Maciej Nasinski <nasinski.maciej@gmail.com>

Diff between miceFast versions 0.1.0 dated 2018-04-16 and 0.2.3 dated 2018-05-06

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New package BlockFeST with initial version 1.6
Package: BlockFeST
Type: Package
Title: Bayesian Calculation of Region-Specific Fixation Index to Detect Local Adaptation
Version: 1.6
Date: 2018-05-6
Author: Bastian Pfeifer
Maintainer: Bastian Pfeifer <bastianxpfeifer@gmail.com>
Depends: R (>= 2.14.2), BASIX
Imports: methods
Suggests: PopGenome
Description: An R implementation of an extension of the 'BayeScan' software (Foll, 2008) <DOI:10.1534/genetics.108.092221> for codominant markers, adding the option to group individual SNPs into pre-defined blocks. A typical application of this new approach is the identification of genomic regions, genes, or gene sets containing one or more SNPs that evolved under directional selection.
License: GPL-2
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2018-05-06 15:30:35 UTC; user
X-CRAN-Comment: Archived on 2018-05-03 as check problems were not corrected despite reminders.
Repository: CRAN
Date/Publication: 2018-05-06 20:40:35 UTC

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Package dbplot updated to version 0.3.0 with previous version 0.2.1 dated 2018-03-11

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

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Package RSQLite updated to version 2.1.1 with previous version 2.1.0 dated 2018-03-29

Title: 'SQLite' Interface for R
Description: Embeds the 'SQLite' database engine in R and provides an interface compliant with the 'DBI' package. The source for the 'SQLite' engine is included.
Author: Kirill Müller [aut, cre] (<https://orcid.org/0000-0002-1416-3412>), Hadley Wickham [aut], David A. James [aut], Seth Falcon [aut], SQLite Authors [ctb] (for the included SQLite sources), Liam Healy [ctb] (for the included SQLite sources), R Consortium [fnd], RStudio [cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

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Package propagate updated to version 1.0-6 with previous version 1.0-5 dated 2017-12-21

Title: Propagation of Uncertainty
Description: Propagation of uncertainty using higher-order Taylor expansion and Monte Carlo simulation.
Author: Andrej-Nikolai Spiess <a.spiess@uke.uni-hamburg.de>
Maintainer: Andrej-Nikolai Spiess <a.spiess@uke.uni-hamburg.de>

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Package fansi updated to version 0.2.3 with previous version 0.2.2 dated 2018-03-31

Title: ANSI Control Sequence Aware String Functions
Description: Counterparts to R string manipulation functions that account for the effects of ANSI text formatting control sequences.
Author: Brodie Gaslam [aut, cre], R Core Team [cph] (UTF8 byte length calcs from src/util.c)
Maintainer: Brodie Gaslam <brodie.gaslam@yahoo.com>

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Package WRSS updated to version 1.3 with previous version 1.2 dated 2018-04-18

Title: Water Resources System Simulator
Description: Water resources system simulator is a tool for simulation and analysis of large-scale water resources systems. 'WRSS' proposes functions and methods for construction, simulation and analysis of primary water resources features (e.g. reservoirs, aquifers, and etc.) based on Standard Operating Policy (SOP).
Author: Rezgar Arabzadeh; Parisa Aberi; Kaveh Panaghi; Shahab Araghinejad; Majid Montaseri
Maintainer: Rezgar Arabzadeh <rezgararabzadeh@ut.ac.ir>

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Package weco updated to version 1.2 with previous version 1.1 dated 2018-01-27

Title: Western Electric Company Rules (WECO) for Shewhart Control Chart
Description: Western Electric Company Rules (WECO) have been widely used for Shewhart control charts in order to increase the sensitivity of detecting assignable causes of process change. This package implements eight commonly used WECO rules and allow to apply the combination of these individual rules for detecting the deviation from a stable process. The package also provides a web-based graphical user interface to help users conduct the analysis.
Author: Chenguang Wang [aut, cre], Lingmin Zeng [aut], Zheyu Wang [aut], Wei Zhao1 [aut], Harry Yang [aut]
Maintainer: Chenguang Wang <cwang68@jhmi.edu>

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Package vtreat updated to version 1.0.4 with previous version 1.0.3 dated 2018-03-10

Title: A Statistically Sound 'data.frame' Processor/Conditioner
Description: A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. 'vtreat' prepares variables so that data has fewer exceptional cases, making it easier to safely use models in production. Common problems 'vtreat' defends against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new categorical levels (levels seen during application, but not during training). Reference: "'vtreat': a data.frame Processor for Predictive Modeling", 'Zumel', 'Mount', 2016, DOI:10.5281/zenodo.1173314.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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Package venn updated to version 1.6 with previous version 1.5 dated 2017-11-24

Title: Draw Venn Diagrams
Description: Draws and displays Venn diagrams up to 7 sets, and any Boolean union of set intersections.
Author: Adrian Dusa [aut, cre, cph]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

Diff between venn versions 1.5 dated 2017-11-24 and 1.6 dated 2018-05-06

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Package turboEM updated to version 2018.1 with previous version 2014.8-1 dated 2014-08-29

Title: A Suite of Convergence Acceleration Schemes for EM, MM and Other Fixed-Point Algorithms
Description: Algorithms for accelerating the convergence of slow, monotone sequences from smooth, contraction mapping such as the EM and MM algorithms. It can be used to accelerate any smooth, linearly convergent acceleration scheme. A tutorial style introduction to this package is available in a vignette on the CRAN download page or, when the package is loaded in an R session, with vignette("turboEM").
Author: Jennifer F. Bobb [aut], Ravi Varadhan [aut, cre], Hui Zhao [ctb]
Maintainer: Ravi Varadhan <ravi.varadhan@jhu.edu>

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Package tsBSS updated to version 0.4.1 with previous version 0.4 dated 2017-11-17

Title: Blind Source Separation and Supervised Dimension Reduction for Time Series
Description: Different estimates are provided to solve the blind source separation problem for multivariate time series with stochastic volatility (Matilainen, Nordhausen and Oja (2015) <doi:10.1016/j.spl.2015.04.033>); Matilainen, Miettinen, Nordhausen, Oja and Taskinen (2017) <doi:10.17713/ajs.v46i3-4.671>) and supervised dimension reduction problem for multivariate time series (Matilainen, Croux, Nordhausen and Oja (2017) <doi:10.1016/j.ecosta.2017.04.002>).
Author: Markus Matilainen, Christophe Croux, Jari Miettinen, Klaus Nordhausen, Hannu Oja, Sara Taskinen
Maintainer: Markus Matilainen <markus.matilainen@outlook.com>

Diff between tsBSS versions 0.4 dated 2017-11-17 and 0.4.1 dated 2018-05-06

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New package treedater with initial version 0.2.0
Package: treedater
Type: Package
Title: Fast Molecular Clock Dating of Phylogenetic Trees with Rate Variation
Version: 0.2.0
Date: 2018-04-23
Authors@R: c(person("Erik", "Volz", role = c("aut", "cre"), email = "erik.volz@gmail.com") )
Author: Erik Volz [aut, cre]
Maintainer: Erik Volz <erik.volz@gmail.com>
Description: Functions for estimating times of common ancestry and molecular clock rates of evolution using a variety of evolutionary models, parametric and nonparametric bootstrap confidence intervals, methods for detecting outlier lineages, and a statistical test for selecting molecular clock models. The methods are described in Volz, E.M. and S.D.W. Frost (2017) <doi:10.1093/ve/vex025>.
License: GPL-2
Imports: ape (>= 5.0)
Depends: limSolve (>= 1.5.5.0)
Suggests: lubridate,ggplot2,foreach,iterators,mgcv,knitr,rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-03 13:02:15 UTC; erikvolz
Repository: CRAN
Date/Publication: 2018-05-04 10:42:51 UTC

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Package tidystats updated to version 0.2 with previous version 0.1 dated 2017-10-29

Title: Create a Tidy Statistics Output File
Description: Produce a data file containing the output of statistical models and assist with a workflow aimed at writing scientific papers using 'R Markdown'. Supported statistical functions include: t.test(), cor.test(), lm(), aov(), anova(). The package is based on tidy data principles and the 'tidyverse' (Wickham, 2017).
Author: Willem Sleegers [aut, cre]
Maintainer: Willem Sleegers <w.sleegers@me.com>

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New package TDMR with initial version 2.0
Package: TDMR
Type: Package
Title: Tuned Data Mining in R
Version: 2.0
Date: 2018-05-04
Author: Wolfgang Konen <wolfgang.konen@fh-koeln.de>, Patrick Koch <patrick.koch@fh-koeln.de>
Maintainer: Wolfgang Konen <wolfgang.konen@fh-koeln.de>
Description: Tuned Data Mining in R ('TDMR') performs the complete tuning of a data mining task (predictive analytics, that is classification and regression). Preprocessing parameters and modeling parameters can be tuned simultaneously. It incorporates a variety of tuners (among them 'SPOT' and 'CMA' with package 'rCMA') and allows integration of additional tuners. Noise handling in the data mining optimization process is supported, see Koch et al. (2015) <doi:10.1016/j.asoc.2015.01.005>.
License: GPL (>= 2)
Depends: R (>= 2.14.0), SPOT (>= 2.0), twiddler
Suggests: cmaes, parallel, e1071, powell, ROCR, randomForest, rCMA, rSFA
Imports: testit, methods, adabag
Collate: 'defaultSC.R' 'defaultOpts.R' 'makeTdmRandomSeed.r' 'printTDMclassifier.r' 'printTDMregressor.r' 'tdmBigLoop.r' 'tdmClassify.r' 'tdmClassifyLoop.r' 'tdmDefaultsFill.r' 'tdmDispatchTuner.r' 'tdmEnvTMakeNew.r' 'tdmGeneralUtils.r' 'tdmGraphicUtils.r' 'tdmMapDesign.r' 'tdmMetacostRf.r' 'tdmModelingUtils.r' 'tdmOptsDefaults.r' 'tdmParaBootstrap.r' 'tdmPreprocUtils.r' 'tdmReadAndSplit.r' 'tdmReadDataset.r' 'tdmRegress.r' 'tdmRegressLoop.r' 'tdmROCR.r' 'tdmStartSpot2.r' 'tdmStartOther.r' 'tdmTuneIt.r' 'unbiasedRun.r'
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-04 14:12:08 UTC; wolfgang
Repository: CRAN
Date/Publication: 2018-05-04 20:21:14 UTC

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Package SurvDisc updated to version 0.1.1 with previous version 0.1.0 dated 2016-10-05

Title: Discrete Time Survival and Longitudinal Data Analysis
Description: Various functions for discrete time survival analysis and longitudinal analysis. SIMEX method for correcting for bias for errors-in-variables in a mixed effects model. Asymptotic mean and variance of different proportional hazards test statistics using different ties methods given two survival curves and censoring distributions. Score test and Wald test for regression analysis of grouped survival data. Calculation of survival curves for events defined by the response variable in a mixed effects model crossing a threshold with or without confirmation.
Author: John Lawrence [aut, cre], Jianjin Xu [ctb], Sue Jane Wang [ctb], Jim Hung [ctb]
Maintainer: John Lawrence <john.lawrence@fda.hhs.gov>

Diff between SurvDisc versions 0.1.0 dated 2016-10-05 and 0.1.1 dated 2018-05-06

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Package states updated to version 0.2.1 with previous version 0.2.0 dated 2018-02-23

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>

Diff between states versions 0.2.0 dated 2018-02-23 and 0.2.1 dated 2018-05-06

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Package statcheck updated to version 1.3.0 with previous version 1.2.2 dated 2016-08-18

Title: Extract Statistics from Articles and Recompute p Values
Description: Extract statistics from articles and recompute p values.
Author: Sacha Epskamp <mail@sachaepskamp.com> & Michele B. Nuijten <m.b.nuijten@uvt.nl>
Maintainer: Michele B. Nuijten <m.b.nuijten@uvt.nl>

Diff between statcheck versions 1.2.2 dated 2016-08-18 and 1.3.0 dated 2018-05-06

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New package sstModel with initial version 1.0.0
Package: sstModel
Title: Swiss Solvency Test (SST) Standard Models
Authors@R: c( person("Loris", "Michel", role = "aut"), person("Melvin", "Kianmanesh Rad", role = "aut"), person("Adrien", "Lamit", role = "aut"), person("Michael", "Schmutz", role = "cre", email = "michael.schmutz@finma.ch"), person(family = "Swiss Financial Market Supervisory Authority FINMA", role = "cph") )
License: GPL-3 + file LICENSE
Version: 1.0.0
Description: Framework for the implementation of solvency related computations based on standard models for the Swiss Solvency Test (SST), a risk-based capital standard for Swiss insurance companies. Allows Monte Carlo simulation of market risk, some insurance risks and their aggregation. Additional toolbox for preprocessing computations. Convenient 'shiny' GUI combined with a parser for an input 'excel' (.xlsx) template to simplify model configuration, data fill-in and results visualization.
Depends: R (>= 3.3.0)
Imports: data.table (>= 1.10.4-3), stats, utils, tools, readxl (>= 1.0.0), openxlsx (>= 4.0.17), MASS, shiny (>= 1.0.5), shinydashboard (>= 0.6.1)
Encoding: UTF-8
LazyData: true
Suggests: testthat, knitr, covr
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-05-03 15:56:54 UTC; michello
Author: Loris Michel [aut], Melvin Kianmanesh Rad [aut], Adrien Lamit [aut], Michael Schmutz [cre], Swiss Financial Market Supervisory Authority FINMA [cph]
Maintainer: Michael Schmutz <michael.schmutz@finma.ch>
Repository: CRAN
Date/Publication: 2018-05-03 22:21:08 UTC

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Package srvyr updated to version 0.3.2 with previous version 0.3.1 dated 2018-03-10

Title: 'dplyr'-Like Syntax for Summary Statistics of Survey Data
Description: Use piping, verbs like 'group_by' and 'summarize', and other 'dplyr' inspired syntactic style when calculating summary statistics on survey data using functions from the 'survey' package.
Author: Greg Freedman Ellis [aut, cre], Thomas Lumley [ctb]
Maintainer: Greg Freedman Ellis <greg.freedman@gmail.com>

Diff between srvyr versions 0.3.1 dated 2018-03-10 and 0.3.2 dated 2018-05-06

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Package spduration updated to version 0.17.1 with previous version 0.17.0 dated 2017-10-04

Title: Split-Population Duration (Cure) Regression
Description: An implementation of split-population duration regression models. Unlike regular duration models, split-population duration models are mixture models that accommodate the presence of a sub-population that is not at risk for failure, e.g. cancer patients who have been cured by treatment. This package implements Weibull and Loglogistic forms for the duration component, and focuses on data with time-varying covariates. These models were originally formulated in Boag (1949) <http://www.jstor.org/stable/2983694> and Berkson and Gage (1952) <http://www.jstor.org/stable/2281318>, and extended in Schmidt and Witte (1989) <doi:10.1016/0304-4076(89)90034-1>.
Author: Andreas Beger [aut, cre] (<https://orcid.org/0000-0003-1883-3169>), Daina Chiba [aut], Daniel W. Hill, Jr. [aut], Nils W. Metternich [aut], Shahryar Minhas [aut], Michael D. Ward [aut, cph]
Maintainer: Andreas Beger <adbeger@gmail.com>

Diff between spduration versions 0.17.0 dated 2017-10-04 and 0.17.1 dated 2018-05-06

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Package sparklyr updated to version 0.8.2 with previous version 0.8.1 dated 2018-05-02

Title: R Interface to Apache Spark
Description: R interface to Apache Spark, a fast and general engine for big data processing, see <http://spark.apache.org>. This package supports connecting to local and remote Apache Spark clusters, provides a 'dplyr' compatible back-end, and provides an interface to Spark's built-in machine learning algorithms.
Author: Javier Luraschi [aut, cre], Kevin Kuo [aut] (<https://orcid.org/0000-0001-7803-7901>), Kevin Ushey [aut], JJ Allaire [aut], RStudio [cph], The Apache Software Foundation [aut, cph]
Maintainer: Javier Luraschi <javier@rstudio.com>

Diff between sparklyr versions 0.8.1 dated 2018-05-02 and 0.8.2 dated 2018-05-06

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Package smooth updated to version 2.4.3 with previous version 2.4.1 dated 2018-03-06

Title: Forecasting Using Smoothing Functions
Description: Functions implementing Single Source of Error state-space models for purposes of time series analysis and forecasting. The package includes exponential smoothing, SARIMA in state-space forms and several simulation functions.
Author: Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK)
Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>

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Package sjmisc updated to version 2.7.2 with previous version 2.7.1 dated 2018-03-25

Title: Data and Variable Transformation Functions
Description: Collection of miscellaneous utility functions, supporting data transformation tasks like recoding, dichotomizing or grouping variables, setting and replacing missing values. The data transformation functions also support labelled data, and all integrate seamlessly into a 'tidyverse'-workflow.
Author: Daniel Lüdecke <d.luedecke@uke.de>
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package ShinyItemAnalysis updated to version 1.2.7 with previous version 1.2.6 dated 2018-03-02

Title: Test and Item Analysis via Shiny
Description: Interactive shiny application for analysis of educational tests and their items.
Author: Patricia Martinkova [aut, cre], Adela Drabinova [aut], Ondrej Leder [aut], Jakub Houdek [aut], Lubomir Stepanek [ctb]
Maintainer: Patricia Martinkova <martinkova@cs.cas.cz>

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Permanent link

New package shinyanimate with initial version 0.1.0
Package: shinyanimate
Type: Package
Title: Animation for 'shiny' Elements
Version: 0.1.0
Author: Swechhya Bista
Maintainer: Swechhya Bista <swechhyabista@gmail.com>
Description: An extension of 'animate.css' that allows user to easily add animations to any UI element in 'shiny' app using the elements id.
Imports: shiny
License: MIT + file LICENSE
URL: https://github.com/Swechhya/shinyanimate
BugReports: https://github.com/Swechhya/shinyanimate/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-03 12:09:13 UTC; leapfrog
Repository: CRAN
Date/Publication: 2018-05-03 12:35:26 UTC

More information about shinyanimate at CRAN
Permanent link

Package Seurat updated to version 2.3.1 with previous version 2.3.0 dated 2018-03-23

Title: Tools for Single Cell Genomics
Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Butler A and Satija R (2017) <doi:10.1101/164889> for more details.
Author: Rahul Satija [aut], Andrew Butler [aut] (<https://orcid.org/0000-0003-3608-0463>), Paul Hoffman [aut, cre] (<https://orcid.org/0000-0002-7693-8957>), Jeff Farrell [ctb], Shiwei Zheng [ctb] (<https://orcid.org/0000-0001-6682-6743>), Christoph Hafemeister [ctb] (0000-0001-6365-8254), Patrick Roelli [ctb]
Maintainer: Paul Hoffman <seuratpackage@gmail.com>

Diff between Seurat versions 2.3.0 dated 2018-03-23 and 2.3.1 dated 2018-05-06

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New package SBSDiff with initial version 0.1.0
Package: SBSDiff
Type: Package
Title: Satorra-Bentler Scaled Chi-Squared Difference Test
Version: 0.1.0
Author: Frank D. Mann <frankdmann@gmail.com>
Maintainer: Frank D. Mann <frankdmann@gmail.com>
Description: Calculates a Satorra-Bentler scaled chi-squared difference test between nested models that were estimated using maximum likelihood (ML) with robust standard errors, which cannot be calculated the traditional way. For details see Satorra & Bentler (2001) <doi:10.1007/bf02296192> and Satorra & Bentler (2010) <doi:10.1007/s11336-009-9135-y>. This package may be particularly helpful when used in conjunction with 'Mplus' software, specifically when implementing the complex survey option. In such cases, the model estimator in 'Mplus' defaults to ML with robust standard errors.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: stats
NeedsCompilation: no
Packaged: 2018-05-02 20:53:22 UTC; frankdmann
Repository: CRAN
Date/Publication: 2018-05-03 10:58:05 UTC

More information about SBSDiff at CRAN
Permanent link

Package sbpiper updated to version 1.8.0 with previous version 1.7.0 dated 2018-04-20

Title: Data Analysis Functions for 'SBpipe' Package
Description: Provides an API for analysing repetitive parameter estimations and simulations of mathematical models. Examples of mathematical models are Ordinary Differential equations (ODEs) or Stochastic Differential Equations (SDEs) models. Among the analyses for parameter estimation 'sbpiper' calculates statistics and generates plots for parameter density, PCA of the best fits, parameter profile likelihood estimations (PLEs), and 2D parameter PLEs. These results can be generated using all or a subset of the best computed parameter sets. Among the analyses for model simulation 'sbpiper' calculates statistics and generates plots for deterministic and stochastic time courses via cartesian and heatmap plots. Plots for the scan of one or two model parameters can also be generated. This package is primarily used by the software 'SBpipe'. Citation: Dalle Pezze P, Le Novère N. SBpipe: a collection of pipelines for automating repetitive simulation and analysis tasks. BMC Systems Biology. 2017;11:46. <doi:10.1186/s12918-017-0423-3>.
Author: Piero Dalle Pezze [aut, cre, cph] (<https://orcid.org/0000-0003-1695-6763>)
Maintainer: Piero Dalle Pezze <piero.dallepezze@gmail.com>

Diff between sbpiper versions 1.7.0 dated 2018-04-20 and 1.8.0 dated 2018-05-06

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New package SanzCircos with initial version 0.1.0
Package: SanzCircos
Type: Package
Title: Functions for Creating 'Circos' Files
Version: 0.1.0
Author: Matthew Woodruff, PhD
Maintainer: "Matthew Woodruff" <mcwoodr@emory.edu>
Description: A series of functions designed to aid in the creation of input files for the 'Circos' visualization platform <http://circos.ca/>. Included are two main function types - make_circos_x() and write_circos_x(). The "make" functions are designed to process an input data set, and return a data frame that can be manipulated and filtered to eliminate the need to write Perl scripts within the 'Circos' software platform for data filtering. The "write" functions take processed data frames from the "make" functions, and write .txt files compatible with the 'Circos' platform. In addition to these function types, there are other accessory functions that aid in the manipulation of the make_circos_x() returned data frames to enhance final visual appeal (such as color_circos_links()).
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dplyr, tidyr, purrr, readr, tibble, pbapply, randomcoloR, parallel, grDevices
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-05-03 17:43:19 UTC; Woodruff
Repository: CRAN
Date/Publication: 2018-05-04 10:52:54 UTC

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Package rpms updated to version 0.3.0 with previous version 0.2.1 dated 2017-06-02

Title: Recursive Partitioning for Modeling Survey Data
Description: Fits a linear model to survey data in each node obtained by recursively partitioning the data. The splitting variables and splits selected are obtained using a procedure which adjusts for complex sample design features used to obtain the data. Likewise the model fitting algorithm produces design-consistent coefficients to the least squares linear model between the dependent and independent variables. The first stage of the design is accounted for in the provided variance estimates. The main function returns the resulting binary tree with the linear model fit at every end-node. The package provides a number of functions and methods for these trees.
Author: Daniell Toth [aut, cre]
Maintainer: Daniell Toth <danielltoth@yahoo.com>

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Package rpf updated to version 0.56.2 with previous version 0.56.1 dated 2018-04-03

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: ORPHANED

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Package RNeXML updated to version 2.1.0 with previous version 2.0.8 dated 2017-11-17

Title: Semantically Rich I/O for the 'NeXML' Format
Description: Provides access to phyloinformatic data in 'NeXML' format. The package should add new functionality to R such as the possibility to manipulate 'NeXML' objects in more various and refined way and compatibility with 'ape' objects.
Author: Carl Boettiger [cre, aut] (<https://orcid.org/0000-0002-1642-628X>), Scott Chamberlain [aut] (<https://orcid.org/0000-0003-1444-9135>), Hilmar Lapp [aut] (<https://orcid.org/0000-0001-9107-0714>), Kseniia Shumelchyk [aut], Rutger Vos [aut] (<https://orcid.org/0000-0001-9254-7318>)
Maintainer: Carl Boettiger <cboettig@gmail.com>

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Package rjson updated to version 0.2.18 with previous version 0.2.15 dated 2014-11-02

Title: JSON for R
Description: Converts R object into JSON objects and vice-versa.
Author: Alex Couture-Beil <rjson_pkg@mofo.ca>
Maintainer: Alex Couture-Beil <rjson_pkg@mofo.ca>

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Package rgenoud updated to version 5.8-2.0 with previous version 5.8-1.0 dated 2017-10-23

Title: R Version of GENetic Optimization Using Derivatives
Description: A genetic algorithm plus derivative optimizer.
Author: Walter R. Mebane, Jr. <wmebane@umich.edu>, Jasjeet Singh Sekhon <sekhon@berkeley.edu>
Maintainer: Jasjeet Singh Sekhon <sekhon@berkeley.edu>

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Package Rfast updated to version 1.8.9 with previous version 1.8.8 dated 2018-03-10

Title: A Collection of Efficient and Extremely Fast R Functions
Description: A collection of fast (utility) functions for data analysis. Column- and row- wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), are some of the many fast functions.
Author: Manos Papadakis, Michail Tsagris, Marios Dimitriadis, Stefanos Fafalios, Ioannis Tsamardinos, Matteo Fasiolo, Giorgos Borboudakis, John Burkardt, Changliang Zou and Kleanthi Lakiotaki
Maintainer: Manos Papadakis <papadakm95@gmail.com>

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More information about Rfast at CRAN
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Package rexpokit updated to version 0.26.3 with previous version 0.26.2 dated 2018-01-31

Title: R Wrappers for EXPOKIT; Other Matrix Functions
Description: Wraps some of the matrix exponentiation utilities from EXPOKIT (<http://www.maths.uq.edu.au/expokit/>), a FORTRAN library that is widely recommended for matrix exponentiation (Sidje RB, 1998. "Expokit: A Software Package for Computing Matrix Exponentials." ACM Trans. Math. Softw. 24(1): 130-156). EXPOKIT includes functions for exponentiating both small, dense matrices, and large, sparse matrices (in sparse matrices, most of the cells have value 0). Rapid matrix exponentiation is useful in phylogenetics when we have a large number of states (as we do when we are inferring the history of transitions between the possible geographic ranges of a species), but is probably useful in other ways as well.
Author: Nicholas J. Matzke [aut, cre, cph], Roger B. Sidje [aut, cph], Drew Schmidt [aut]
Maintainer: ORPHANED

Diff between rexpokit versions 0.26.2 dated 2018-01-31 and 0.26.3 dated 2018-05-06

 DESCRIPTION      |   11 ++++++-----
 MD5              |    4 ++--
 src/my_expokit.f |    2 +-
 3 files changed, 9 insertions(+), 8 deletions(-)

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Package refinr updated to version 0.3.0 with previous version 0.2.0 dated 2018-01-05

Title: Cluster and Merge Similar Values Within a Character Vector
Description: These functions take a character vector as input, identify and cluster similar values, and then merge clusters together so their values become identical. The functions are an implementation of the key collision and ngram fingerprint algorithms from the open source tool Open Refine <http://openrefine.org/>. More info on key collision and ngram fingerprint can be found here <https://github.com/OpenRefine/OpenRefine/wiki/Clustering-In-Depth>.
Author: Chris Muir [aut, cre]
Maintainer: Chris Muir <chrismuirRVA@gmail.com>

Diff between refinr versions 0.2.0 dated 2018-01-05 and 0.3.0 dated 2018-05-06

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Package REddyProc updated to version 1.1.4 with previous version 1.1.3 dated 2018-01-19

Title: Post Processing of (Half-)Hourly Eddy-Covariance Measurements
Description: Standard and extensible Eddy-Covariance data post-processing includes uStar-filtering, gap-filling, and flux-partitioning. The Eddy-Covariance (EC) micrometeorological technique quantifies continuous exchange fluxes of gases, energy, and momentum between an ecosystem and the atmosphere. It is important for understanding ecosystem dynamics and upscaling exchange fluxes. (Aubinet et al. (2012) <doi:10.1007/978-94-007-2351-1>). This package inputs pre-processed (half-)hourly data and supports further processing. First, a quality-check and filtering is performed based on the relationship between measured flux and friction velocity (uStar) to discard biased data (Papale et al. (2006) <doi:10.5194/bg-3-571-2006>). Second, gaps in the data are filled based on information from environmental conditions (Reichstein et al. (2005) <doi:10.1111/j.1365-2486.2005.001002.x>). Third, the net flux of carbon dioxide is partitioned into its gross fluxes in and out of the ecosystem by night-time based and day-time based approaches (Lasslop et al. (2010) <doi:10.1111/j.1365-2486.2009.02041.x>).
Author: Department for Biogeochemical Integration at MPI-BGC, Jena, Germany [cph], Thomas Wutzler [aut, cre], Markus Reichstein [aut], Antje Maria Moffat [aut, trl], Olaf Menzer [ctb], Mirco Migliavacca [aut], Kerstin Sickel [ctb, trl], Ladislav Šigut [ctb]
Maintainer: Thomas Wutzler <twutz@bgc-jena.mpg.de>

Diff between REddyProc versions 1.1.3 dated 2018-01-19 and 1.1.4 dated 2018-05-06

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Package RcmdrPlugin.orloca updated to version 4.5 with previous version 4.1 dated 2013-01-21

Title: A GUI for Planar Location Problems
Description: A GUI for the orloca package is provided as a Rcmdr plug-in. The package deals with location problems on the plane.
Author: Manuel Munoz-Marquez <manuel.munoz@uca.es>
Maintainer: Manuel Munoz-Marquez <manuel.munoz@uca.es>

Diff between RcmdrPlugin.orloca versions 4.1 dated 2013-01-21 and 4.5 dated 2018-05-06

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 17 files changed, 133 insertions(+), 180 deletions(-)

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New package psyosphere with initial version 0.1.4
Package: psyosphere
Type: Package
Title: Analyse GPS Data
Version: 0.1.4
Date: 2018-05-03
Authors@R: c( person("Benjamin", "Ziepert", email = "feedback-psyosphere@analyse-gps.com", role = c("cre", "aut")), person("Elze G", "Ufkes", role = "ctb"), person("Peter W", "de Vries", role = "ctb"))
Maintainer: Benjamin Ziepert <feedback-psyosphere@analyse-gps.com>
Description: Analyse location data such as latitude, longitude, and elevation. Based on spherical trigonometry, variables such as speed, bearing, and distances can be calculated from moment to moment, depending on the sampling frequency of the equipment used, and independent of scale. Additionally, the package can plot tracks, coordinates, and shapes on maps, and sub-tracks can be selected with point-in-polygon or other techniques. The package is optimized to support behavioural science experiments with multiple tracks. It can detect and clean up errors in the data, and resulting data can be exported to be analysed in statistical software or geographic information systems (GIS).
Depends: R (>= 2.10)
License: MIT + file LICENSE
Imports: ggmap, rgdal, plyr, geosphere, ggplot2, sp, lubridate, RgoogleMaps, SDMTools, stats
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-03 10:48:33 UTC; micro
Author: Benjamin Ziepert [cre, aut], Elze G Ufkes [ctb], Peter W de Vries [ctb]
Repository: CRAN
Date/Publication: 2018-05-03 11:38:56 UTC

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Package ProjectionBasedClustering updated to version 1.0.7 with previous version 1.0.6 dated 2018-01-31

Title: Projection Based Clustering
Description: A clustering approach applicable to every projection method is proposed here [Thrun/Ultsch,2017] <DOI:10.13140/RG.2.2.13124.53124>. The two-dimensional scatter plot of any projection method can construct a topographic map which displays unapparent data structures by using distance and density information of the data. The generalized U*-matrix renders this visualization in the form of a topographic map, which can be used to automatically define the clusters of high-dimensional data. The whole system is based on the book "Projection-Based Clustering through Self-Organization and Swarm Intelligence" <DOI:10.1007/978-3-658-20540-9>. Selecting the correct projection method will result in a visualization in which mountains surround each cluster. The number of clusters can be determined by counting valleys on the topographic map. Most projection methods are wrappers for already available methods in R. By contrast, the neighbor retrieval visualizer (NeRV) is based on C++ source code of the 'dredviz' software package, and the Curvilinear Component Analysis (CCA) is translated from 'MATLAB' ('SOM Toolbox' 2.0) to R.
Author: Michael Thrun [aut, cre, cph], Florian Lerch [aut], Felix Pape [aut], Kristian Nybo [cph], Jarkko Venna [cph]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package pROC updated to version 1.12.1 with previous version 1.11.0 dated 2018-03-25

Title: Display and Analyze ROC Curves
Description: Tools for visualizing, smoothing and comparing receiver operating characteristic (ROC curves). (Partial) area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.
Author: Xavier Robin [cre, aut] (<https://orcid.org/0000-0002-6813-3200>), Natacha Turck [aut], Alexandre Hainard [aut], Natalia Tiberti [aut], Frédérique Lisacek [aut], Jean-Charles Sanchez [aut], Markus Müller [aut], Stefan Siegert [ctb] (Fast DeLong code)
Maintainer: Xavier Robin <pROC-cran@xavier.robin.name>

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Package popbio updated to version 2.4.4 with previous version 2.4.3 dated 2016-04-01

Title: Construction and Analysis of Matrix Population Models
Description: Construct and analyze projection matrix models from a demography study of marked individuals classified by age or stage. The package covers methods described in Matrix Population Models by Caswell (2001) and Quantitative Conservation Biology by Morris and Doak (2002).
Author: Chris Stubben, Brook Milligan, Patrick Nantel
Maintainer: Chris Stubben <chris.stubben@hci.utah.edu>

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New package PMmisc with initial version 0.1.0
Package: PMmisc
Type: Package
Title: P&M Miscellaneous R Functions
Version: 0.1.0
Author: Manuel Russon <manuekrusson@gmail.com>, Xuanhua "Peter" Yin <peteryin.sju@hotmail.com>
Maintainer: Xuanhua "Peter" Yin <peteryin.sju@hotmail.com>
Imports: robust
Description: Miscellaneous functions for data analysis, graphics, data manipulation, statistical investigation, including descriptive statistics, creating leading and lagging variables, portfolio return analysis, time series difference and percentage change calculation, stacking data for higher efficient analysis.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-03 14:15:55 UTC; Peter Yin
Repository: CRAN
Date/Publication: 2018-05-04 10:50:21 UTC

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New package pkgdown with initial version 1.0.0
Package: pkgdown
Title: Make Static HTML Documentation for a Package
Version: 1.0.0
Authors@R: c( person("Hadley", "Wickham", , "hadley@rstudio.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4757-117X") ), person("Jay", "Hesselberth", role = "ctb", comment = c(ORCID = "0000-0002-6299-179X") ), person("RStudio", role = c("cph", "fnd")) )
Description: Generate an attractive and useful website from a source package. 'pkgdown' convert your documentation, vignettes, 'README' and more to 'HTML' making it easy to share information about your package online.
License: MIT + file LICENSE
URL: http://pkgdown.r-lib.org, https://github.com/r-lib/pkgdown
BugReports: https://github.com/r-lib/pkgdown/issues
Depends: R (>= 3.1.0)
Imports: callr (>= 2.0.2), cli, crayon, desc, devtools, digest, evaluate, fs (>= 1.2.0), highlight, httr, magrittr, MASS, memoise, purrr, R6, rematch, rlang (>= 0.2.0), rmarkdown (>= 1.1.9007), roxygen2, rsconnect, rstudioapi, tibble, tools, whisker, xml2 (>= 1.1.1), yaml
Suggests: BiocInstaller, covr, jsonlite, knitr, magick, testthat
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-04-24 22:20:31 UTC; hadley
Author: Hadley Wickham [aut, cre] (<https://orcid.org/0000-0003-4757-117X>), Jay Hesselberth [ctb] (<https://orcid.org/0000-0002-6299-179X>), RStudio [cph, fnd]
Maintainer: Hadley Wickham <hadley@rstudio.com>
Repository: CRAN
Date/Publication: 2018-05-03 08:55:54 UTC

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Package PINSPlus updated to version 1.0.1 with previous version 1.0.0 dated 2018-03-16

Title: Clustering Algorithm for Data Integration and Disease Subtyping
Description: Provides a robust approach for omics data integration and disease subtyping. It is an improved implementation of PINS - Perturbation clustering for data INtegration and disease Subtyping (Nguyen T, Tagett R, Diaz D, Draghici S, Genome Research, 2017, <doi:10.1101/gr.215129.116>). 'PINSPlus' supports both single and multiple data types. The software automatically determines the optimal number of clusters and then partitions the samples in a way such that the results are robust to noise and data perturbation. 'PINSPlus' is fast and it supports parallel computing on Windows, Linux, and Mac OS.
Author: Hung Nguyen, Sangam Shrestha and Tin Nguyen
Maintainer: Hung Nguyen <hungnp@nevada.unr.edu>

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Package pbdZMQ updated to version 0.3-3 with previous version 0.3-2 dated 2018-01-31

Title: Programming with Big Data -- Interface to 'ZeroMQ'
Description: 'ZeroMQ' is a well-known library for high-performance asynchronous messaging in scalable, distributed applications. This package provides high level R wrapper functions to easily utilize 'ZeroMQ'. We mainly focus on interactive client/server programming frameworks. For convenience, a minimal 'ZeroMQ' library (4.2.2) is shipped with 'pbdZMQ', which can be used if no system installation of 'ZeroMQ' is available. A few wrapper functions compatible with 'rzmq' are also provided.
Author: Wei-Chen Chen [aut, cre], Drew Schmidt [aut], Christian Heckendorf [aut] (file transfer), George Ostrouchov [aut] (Mac OSX), Whit Armstrong [ctb] (some functions are modified from the rzmq package for backwards compatibility), Brian Ripley [ctb] (C code of shellexec, and Solaris), R Core team [ctb] (some functions are modified from the R source code), Philipp A. [ctb] (Fedora), Elliott Sales de Andrade [ctb] (sprintf), Spencer Aiello [ctb] (windows conf)
Maintainer: Wei-Chen Chen <wccsnow@gmail.com>

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Package pbdRPC updated to version 0.2-1 with previous version 0.2-0 dated 2018-02-01

Title: Programming with Big Data -- Remote Procedure Call
Description: A very light implementation yet secure for remote procedure calls with unified interface via ssh (OpenSSH) or plink/plink.exe (PuTTY).
Author: Wei-Chen Chen [aut, cre], Drew Schmidt [aut]
Maintainer: Wei-Chen Chen <wccsnow@gmail.com>

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Package optional updated to version 1.1 with previous version 1.0 dated 2017-07-31

Title: Optional Types and Pattern Matching
Description: Introduces some() and none, as well as match_with() from functional languages.
Author: Antoine Champion
Maintainer: Antoine Champion <antoine.champion@outlook.com>

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Package olsrr updated to version 0.5.1 with previous version 0.5.0 dated 2018-03-26

Title: Tools for Building OLS Regression Models
Description: Tools for building OLS regression models . Includes comprehensive regression output, heteroskedasticity tests, collinearity diagnostics, residual diagnostics, measures of influence, model fit assessment and variable selection procedures.
Author: Aravind Hebbali [aut, cre]
Maintainer: Aravind Hebbali <hebbali.aravind@gmail.com>

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Package oglmx updated to version 3.0.0.0 with previous version 2.0.0.3 dated 2017-03-12

Title: Estimation of Ordered Generalized Linear Models
Description: Ordered models such as ordered probit and ordered logit presume that the error variance is constant across observations. In the case that this assumption does not hold estimates of marginal effects are typically biased (Weiss (1997)). This package allows for generalization of ordered probit and ordered logit models by allowing the user to specify a model for the variance. Furthermore, the package includes functions to calculate the marginal effects. Wrapper functions to estimate the standard limited dependent variable models are also included.
Author: Nathan Carroll
Maintainer: Nathan Carroll <nathan.carroll@ur.de>

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Package nlcv updated to version 0.3.3 with previous version 0.3.2 dated 2017-10-19

Title: Nested Loop Cross Validation
Description: Nested loop cross validation for classification purposes for misclassification error rate estimation. The package supports several methodologies for feature selection: random forest, Student t-test, limma, and provides an interface to the following classification methods in the 'MLInterfaces' package: linear, quadratic discriminant analyses, random forest, bagging, prediction analysis for microarray, generalized linear model, support vector machine (svm and ksvm). Visualizations to assess the quality of the classifier are included: plot of the ranks of the features, scores plot for a specific classification algorithm and number of features, misclassification rate for the different number of features and classification algorithms tested and ROC plot. For further details about the methodology, please check: Markus Ruschhaupt, Wolfgang Huber, Annemarie Poustka, and Ulrich Mansmann (2004) <doi:10.2202/1544-6115.1078>.
Author: Willem Talloen, Tobias Verbeke
Maintainer: Laure Cougnaud <laure.cougnaud@openanalytics.eu>

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Package Nippon updated to version 0.7 with previous version 0.6.5 dated 2017-11-28

Title: Japanese Utility Functions and Data
Description: Japan-specific data is sometimes too unhandy for R users to manage. The utility functions and data in this package disencumber us from such an unnecessary burden.
Author: Susumu Tanimura <aruminat@gmail.com> [aut, cre], Hironobu Takahashi [cph], Hajime Baba [cph], Takatsugu Nokubi [cph]
Maintainer: Susumu Tanimura <aruminat@gmail.com>

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Package netregR updated to version 0.3.1 with previous version 0.3.0 dated 2018-04-10

Title: Regression of Network Responses
Description: Regress network responses (both directed and undirected) onto covariates of interest that may be actor-, relation-, or network-valued. In addition, compute principled variance estimates of the coefficients assuming that the errors are jointly exchangeable. Missing data is accommodated. Additionally implements building and inversion of covariance matrices under joint exchangeability, and generates random covariance matrices of this class. For more detail on methods, see Marrs, Fosdick, and McCormick (2017) <arXiv:1701.05530>.
Author: Frank W. Marrs [aut, cre], Bailey K. Fosdick [aut], Tyler H. McCormick [aut]
Maintainer: Frank W. Marrs <frank.marrs@colostate.edu>

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Package ncf updated to version 1.2-4 with previous version 1.2-3 dated 2018-04-19

Title: Spatial Covariance Functions
Description: R functions for analyzing spatial (cross-)covariance: the nonparametric (cross-)covariance function, the spline correlogram, the nonparametric phase coherence function, local indicators of spatial association (LISA), (Mantel) correlogram, (Partial) Mantel test.
Author: Ottar N. Bjornstad [aut, cre], Jun Cai [ctb]
Maintainer: Ottar N. Bjornstad <onb1@psu.edu>

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Package mvord updated to version 0.3.0 with previous version 0.2.1 dated 2017-11-29

Title: Multivariate Ordinal Regression Models
Description: A flexible framework for fitting multivariate ordinal regression models with composite likelihood methods.
Author: Rainer Hirk [aut, cre], Kurt Hornik [aut], Laura Vana [aut], Alan Genz [ctb] (Fortran Code)
Maintainer: Rainer Hirk <rhirk@wu.ac.at>

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Package msma updated to version 1.1 with previous version 1.0 dated 2018-03-01

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

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Package MSCMT updated to version 1.3.3 with previous version 1.3.2 dated 2018-02-19

Title: Multivariate Synthetic Control Method Using Time Series
Description: Three generalizations of the synthetic control method (which has already an implementation in package 'Synth') are implemented: first, 'MSCMT' allows for using multiple outcome variables, second, time series can be supplied as economic predictors, and third, a well-defined cross-validation approach can be used. Much effort has been taken to make the implementation as stable as possible (including edge cases) without losing computational efficiency. A detailed description of the main algorithms is given in Becker and Klößner (2018) <doi:10.1016/j.ecosta.2017.08.002>.
Author: Martin Becker [aut, cre] (<https://orcid.org/0000-0003-2336-9751>), Stefan Klößner [aut], Karline Soetaert [com], LAPACK authors [cph]
Maintainer: Martin Becker <martin.becker@mx.uni-saarland.de>

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New package mrMLM.GUI with initial version 3.1
Package: mrMLM.GUI
Type: Package
Title: Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for Genome-Wide Association Study
Version: 3.1
Date: 2018-4-25
Author: Zhang Ya-Wen, Li Pei, Ren Wen-Long, Ni Yuan-Li, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>
Description: Conduct multi-locus genome-wide association study under the framework of random-SNP-effect mixed linear model (mrMLM). First, each marker on the genome is scanned. Bonferroni correction is replaced by a less stringent selection criterion for significant test. Then, all the markers that are potentially associated with the trait are included in a multi-locus model, their effects are estimated by empirical Bayes and true Quantitative Trait Nucleotides (QTN) are identified by likelihood ratio test. Wen YJ, Zhang H, Ni YL, Huang B, Zhang J, Feng JY, Wang SB, Dunwell JM, Zhang YM, Wu R (2017) <doi:10.1093/bib/bbw145>.
Depends: shiny,MASS,data.table,doParallel,foreach
Imports: methods,openxlsx,stringr,qqman,ggplot2,lars,ncvreg,coin,shinyjs,sampling,mrMLM
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-05-03 15:22:31 UTC; abc
Repository: CRAN
Date/Publication: 2018-05-04 12:39:30 UTC

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Package MOLHD updated to version 0.2 with previous version 0.1 dated 2017-11-08

Title: Multiple Objective Latin Hypercube Design
Description: Generate the optimal maximin distance, minimax distance (only for low dimensions), and maximum projection designs within the class of Latin hypercube designs efficiently for computer experiments. Generate Pareto front optimal designs for each two of the three criteria and all the three criteria within the class of Latin hypercube designs efficiently. Provide criterion computing functions. References of this package can be found in Morris, M. D. and Mitchell, T. J. (1995) <doi:10.1016/0378-3758(94)00035-T>, Lu Lu and Christine M. Anderson-CookTimothy J. Robinson (2011) <doi:10.1198/Tech.2011.10087>, Joseph, V. R., Gul, E., and Ba, S. (2015) <doi:10.1093/biomet/asv002>.
Author: Ruizhe Hou , Lu Lu
Maintainer: Ruizhe Hou <houruizhe1210@gmail.com>

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Package mlmm.gwas updated to version 1.0.3 with previous version 1.0.2 dated 2018-04-03

Title: Pipeline for GWAS Using MLMM
Description: Pipeline for Genome-Wide Association Study using Multi-Locus Mixed Model from Segura V, Vilhjálmsson BJ et al. (2012) <doi:10.1038/ng.2314>. The pipeline include detection of associated SNPs with MLMM, model selection by lowest eBIC, estimation of the effects of the SNPs in the selected model and graphical functions.
Author: Fanny Bonnafous [aut], Olivier Guillaume[aut, cre], Brigitte Mangin [aut], Prune Pegot-Espagnet [aut], Vincent Segura [aut], Bjarni J. Vilhjalmsson [aut]
Maintainer: Olivier Guillaume <olivier.guillaume@inra.fr>

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Package missMDA updated to version 1.12 with previous version 1.11 dated 2017-03-16

Title: Handling Missing Values with Multivariate Data Analysis
Description: Imputation of incomplete continuous or categorical datasets; Missing values are imputed with a principal component analysis (PCA), a multiple correspondence analysis (MCA) model or a multiple factor analysis (MFA) model; Perform multiple imputation with and in PCA or MCA.
Author: Francois Husson, Julie Josse
Maintainer: Francois Husson <husson@agrocampus-ouest.fr>

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Package MEclustnet updated to version 1.2 with previous version 1.1 dated 2017-01-26

Title: Fitting the Mixture of Experts Latent Position Cluster Model to Network Data
Description: Fits the mixture of experts latent position cluster model to network data to cluster nodes into subgroups, while incorporating covariate information, in a mixture of experts model setting.
Author: Isobel Claire Gormley and Thomas Brendan Murphy
Maintainer: Isobel Claire Gormley <claire.gormley@ucd.ie>

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New package matR with initial version 0.9.1
Package: matR
Type: Package
Title: Metagenomics Analysis Tools
Authors@R: c( person (c("Daniel", "T."), "Braithwaite", role = c("aut"), email = "contact.dtb@gmail.com"), person (c("Kevin", "P."), "Keegan", role = "aut", email = "keegan@mcs.anl.gov"), person (c("William", "L."), "Trimble", role = c("cre", "ctb"), email = "trimble@anl.gov"), person (c("University", "of"), "Chicago", role = "cph"))
Version: 0.9.1
Depends: R (>= 2.10), MGRASTer, BIOM.utils, graphics, stats, utils
Imports:
Suggests: RJSONIO, qvalue, ecodist, gplots, scatterplot3d
URL: https://github.com/MG-RAST/matR/
Date: 2018-05-04
Description: An analysis platform for metagenomics combining specialized tools and workflows, easy handling of the BIOM format, and transparent access to MG-RAST resources. Integrates easily with other R packages and non-R software.
License: BSD_2_clause + file LICENSE
Copyright: University of Chicago
LazyData: yes
Collate: utils.R biom-ext.R client.R graphics.R analysis-support.R analysis-misc.R distx.R rowstats.R transform.R boxplot.R princomp.R image.R init.R
NeedsCompilation: no
Packaged: 2018-05-04 15:15:43 UTC; wltrimbl
Author: Daniel T. Braithwaite [aut], Kevin P. Keegan [aut], William L. Trimble [cre, ctb], University of Chicago [cph]
Maintainer: William L. Trimble <trimble@anl.gov>
Repository: CRAN
Date/Publication: 2018-05-04 20:34:53 UTC

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Package Matching updated to version 4.9-3 with previous version 4.9-2 dated 2015-12-25

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

Diff between Matching versions 4.9-2 dated 2015-12-25 and 4.9-3 dated 2018-05-06

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New package maditr with initial version 0.5.0
Package: maditr
Type: Package
Title: Pipe-Style Interface for 'data.table'
Version: 0.5.0
Date: 2018-05-05
Maintainer: Gregory Demin <gdemin@gmail.com>
Authors@R: person("Gregory", "Demin", email = "gdemin@gmail.com", role = c("aut", "cre"))
Depends: R (>= 3.3.0)
Imports: data.table (>= 1.10), magrittr (>= 1.5)
Suggests: knitr, testthat
Description: Package provides pipe-style interface for 'data.table'. It preserves all 'data.table' features without significant impact on performance. 'let' and 'take' functions are simplified interfaces for most common data manipulation tasks. For example, you can write 'mtcars %>% take(mean(mpg), by = am)' for aggregation or 'mtcars %>% let(hp_wt = hp/wt, hp_wt_mpg = hp_wt/mpg)' for modification. Use 'take_if/let_if' for conditional aggregation/modification. 'query_if' function translates its arguments one-to-one to '[.data.table' method. Additionally there are some conveniences such as automatic 'data.frame' conversion to 'data.table'.
License: GPL-2
URL: https://github.com/gdemin/maditr
BugReports: https://github.com/gdemin/maditr/issues
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-05 03:28:21 UTC; gregory
Author: Gregory Demin [aut, cre]
Repository: CRAN
Date/Publication: 2018-05-05 06:07:55 UTC

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Package live updated to version 1.5.3 with previous version 1.4.2 dated 2018-04-03

Title: Local Interpretable (Model-Agnostic) Visual Explanations
Description: Interpretability of complex machine learning models is a growing concern. This package helps to understand key factors that drive the decision made by complicated predictive model (so called black box model). This is achieved through local approximations that are either based on additive regression like model or CART like model that allows for higher interactions. The methodology is based on Tulio Ribeiro, Singh, Guestrin (2016) <doi:10.1145/2939672.2939778>. More details can be found in Staniak, Biecek (2018) <arXiv:1804.01955>.
Author: Mateusz Staniak [cre, aut], Przemysław Biecek [aut]
Maintainer: Mateusz Staniak <mateusz.staniak@math.uni.wroc.pl>

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New package leerSIECyL with initial version 1.0.1
Package: leerSIECyL
Type: Package
Title: Read Data from the SIE
Version: 1.0.1
Date: 2018-04-17
Author: Jess Mara Rodrguez Rodrguez
Maintainer: Jess M. Rodrguez Rodrguez <jesusmro@ono.com>
Description: Functions to download data from the SIE, which is the Statistical Information System (Sistema de Informacin Estadstica) in the Statistical Portal of the Government of Castilla y Len (Spain) <https://estadistica.jcyl.es>.
Depends: R (>= 3.2), RCurl
License: GPL-2
Encoding: latin1
NeedsCompilation: no
Packaged: 2018-05-03 11:41:57 UTC; rodrodje
Repository: CRAN
Date/Publication: 2018-05-03 12:33:25 UTC

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Package kerasformula updated to version 1.0.0 with previous version 0.1.1 dated 2018-01-24

Title: A High-Level R Interface for Neural Nets
Description: Adds a high-level interface for 'keras' neural nets. kms() fits neural net and accepts R formulas to aid data munging and hyperparameter selection. kms() can optionally accept a compiled keras_sequential_model() from 'keras'. kms() accepts a number of parameters (like loss and optimizer) and splits the data into sparse test and training matrices. kms() returns a single object with predictions, a confusion matrix, and function call details.
Author: Pete Mohanty [aut, cre]
Maintainer: Pete Mohanty <pete.mohanty@gmail.com>

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Package jsonld updated to version 2.0 with previous version 1.2 dated 2017-04-11

Title: JSON for Linking Data
Description: JSON-LD is a light-weight syntax for expressing linked data. It is primarily intended for web-based programming environments, interoperable web services and for storing linked data in JSON-based databases. This package provides bindings to the JavaScript library for converting, expanding and compacting JSON-LD documents.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>), rOpenSci [fnd] (https://ropensci.org)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package JoSAE updated to version 0.3.0 with previous version 0.2.3 dated 2015-08-09

Title: Unit-Level and Area-Level Small Area Estimation
Description: Implementation of some unit and area level EBLUP estimators as well as the estimators of their MSE also under heteroscedasticity. The package further documents the publications Breidenbach and Astrup (2012) <DOI:10.1007/s10342-012-0596-7>, Breidenbach et al. (2016) <DOI:10.1016/j.rse.2015.07.026> and Breidenbach et al. (2018 in press). The vignette further explains the use of the implemented functions.
Author: Johannes Breidenbach
Maintainer: Johannes Breidenbach <job@nibio.no>

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Package InterpretMSSpectrum updated to version 1.2 with previous version 1.1 dated 2017-09-20

Title: Interpreting High Resolution Mass Spectra
Description: Annotate and interpret deconvoluted mass spectra (mass*intensity pairs) from high resolution mass spectrometry devices.
Author: Jan Lisec [aut, cre]
Maintainer: Jan Lisec <jan.lisec@bam.de>

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Package httpuv updated to version 1.4.2 with previous version 1.4.1 dated 2018-04-21

Title: HTTP and WebSocket Server Library
Description: Provides low-level socket and protocol support for handling HTTP and WebSocket requests directly from within R. It is primarily intended as a building block for other packages, rather than making it particularly easy to create complete web applications using httpuv alone. httpuv is built on top of the libuv and http-parser C libraries, both of which were developed by Joyent, Inc. (See LICENSE file for libuv and http-parser license information.)
Author: Joe Cheng, Hector Corrada Bravo [ctb], Jeroen Ooms [ctb], Winston Chang [ctb]
Maintainer: Joe Cheng <joe@rstudio.com>

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Package hnp updated to version 1.2-5 with previous version 1.2-4 dated 2017-11-02

Title: Half-Normal Plots with Simulation Envelopes
Description: Generates (half-)normal plots with simulation envelopes using different diagnostics from a range of different fitted models. A few example datasets are included.
Author: Rafael de Andrade Moral [aut, cre], John Hinde [aut], Clarice Garcia Borges Demetrio [aut]
Maintainer: Rafael de Andrade Moral <rafael_moral@yahoo.com.br>

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Package GWLelast updated to version 1.2.1 with previous version 1.1 dated 2015-04-29

Title: Geographically Weighted Logistic Elastic Net Regression
Description: Fit a geographically weighted logistic elastic net regression. Detailed explanations can be found in Yoneoka et al. (2016): New algorithm for constructing area-based index with geographical heterogeneities and variable selection: An application to gastric cancer screening <doi:10.1038/srep26582>.
Author: Daisuke Yoneoka, Eiko Saito
Maintainer: Daisuke Yoneoka <blue.sky.sea.dy@gmail.com>

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Package gss updated to version 2.1-9 with previous version 2.1-8 dated 2018-04-19

Title: General Smoothing Splines
Description: A comprehensive package for structural multivariate function estimation using smoothing splines.
Author: Chong Gu <chong@purdue.edu>
Maintainer: Chong Gu <chong@purdue.edu>

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Package glm.predict updated to version 3.0-1 with previous version 3.0-0 dated 2017-12-06

Title: Predicted Values and Discrete Changes for GLM
Description: Functions to calculate predicted values and the difference between the two cases with confidence interval for glm(), glm.nb(), polr() and multinom().
Author: Benjamin Schlegel [aut,cre]
Maintainer: Benjamin Schlegel <kontakt@benjaminschlegel.ch>

Diff between glm.predict versions 3.0-0 dated 2017-12-06 and 3.0-1 dated 2018-05-06

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Package ggpmisc updated to version 0.2.17 with previous version 0.2.16 dated 2017-09-17

Title: Miscellaneous Extensions to 'ggplot2'
Description: Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Provides new statistics to locate and tag peaks and valleys in 2D plots, a statistics to add a label with the equation of a polynomial fitted with lm(), or R^2 or adjusted R^2 or information criteria for any model fitted with function lm(). Additional statistics give access to functions in package 'broom'. Provides a function for flexibly converting time series to data frames suitable for plotting with ggplot(). In addition provides statistics and ggplot geometries useful for diagnosing what data are passed to compute_group() and compute_panel() functions and to geometries.
Author: Pedro J. Aphalo [aut, cre] (<https://orcid.org/0000-0003-3385-972X>), Kamil Slowikowski [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

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Package ggeffects updated to version 0.3.3 with previous version 0.3.2 dated 2018-03-21

Title: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs
Description: Compute marginal effects at the mean or average marginal effects from statistical models and returns the result as tidy data frames. These data frames are ready to use with the 'ggplot2'-package. Marginal effects can be calculated for many different models. Interaction terms, splines and polynomial terms are also supported. The two main functions are ggpredict() and ggaverage(), however, there are some convenient wrapper-functions especially for polynomials or interactions. There is a generic plot()-method to plot the results using 'ggplot2'.
Author: Daniel Lüdecke <d.luedecke@uke.de>
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between ggeffects versions 0.3.2 dated 2018-03-21 and 0.3.3 dated 2018-05-06

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Package GetDFPData updated to version 0.7 with previous version 0.6 dated 2018-02-16

Title: Reading Annual Financial Reports from Bovespa's DFP, FRE and FCA System
Description: Reads annual financial reports including assets, liabilities, dividends history, stockholder composition and much more from Bovespa's DFP, FRE and FCA systems <http://www.bmfbovespa.com.br/en_us/products/listed-equities-and-derivatives/equities/listed-companies.htm>. These are web based interfaces for all financial reports of companies traded at Bovespa. The package is specially designed for large scale data importation, keeping a tabular (long) structure for easier processing.
Author: Marcelo Perlin [aut, cre]
Maintainer: Marcelo Perlin <marceloperlin@gmail.com>

Diff between GetDFPData versions 0.6 dated 2018-02-16 and 0.7 dated 2018-05-06

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Package future.callr updated to version 0.3.0 with previous version 0.2.0 dated 2018-02-13

Title: A Future API for Parallel Processing using 'callr'
Description: Implementation of the Future API on top of the 'callr' package. This allows you to process futures, as defined by the 'future' package, in parallel out of the box, on your local (Linux, macOS, Windows, ...) machine. Contrary to backends relying on the 'parallel' package (e.g. 'future::multisession'), the 'callr' backend provided here can run more than 125 parallel R processes.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between future.callr versions 0.2.0 dated 2018-02-13 and 0.3.0 dated 2018-05-06

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Package future.batchtools updated to version 0.7.0 with previous version 0.6.0 dated 2017-09-11

Title: A Future API for Parallel and Distributed Processing using 'batchtools'
Description: Implementation of the Future API on top of the 'batchtools' package. This allows you to process futures, as defined by the 'future' package, in parallel out of the box, not only on your local machine or ad-hoc cluster of machines, but also via high-performance compute ('HPC') job schedulers such as 'LSF', 'OpenLava', 'Slurm', 'SGE', and 'TORQUE' / 'PBS', e.g. 'y <- future_lapply(files, FUN = process)'.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between future.batchtools versions 0.6.0 dated 2017-09-11 and 0.7.0 dated 2018-05-06

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New package FRegSigCom with initial version 0.2.2
Package: FRegSigCom
Type: Package
Title: Functional Regression using Signal Compression Approach
Version: 0.2.2
Author: Ruiyan Luo, Xin Qi
Maintainer: Ruiyan Luo <rluo@gsu.edu>
Description: Signal compression methods for function-on-function regression with functional response and functional predictors, including linear models with both scalar and functional predictors for a small number of functional predictors, linear models with functional predictors for a large number of functional predictors, stepwise selection for FOF models with two-way interactions, and nonlinear models. References are linked to via the URL below.
URL: https://doi.org/10.1080/01621459.2016.1164053, https://www.sciencedirect.com/science/article/pii/S0047259X16302536?via%3Dihub.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
NeedsCompilation: yes
Imports: Rcpp
LinkingTo: Rcpp, RcppEigen
Depends: fda, Matrix
Suggests: refund, MASS
Collate: 'multiple_function_on_function.R' 'nonlinear_function_on_function.R' 'high_dimensional_function_on_function.R' 'ff.interaction.R' 'RcppExports.R'
RoxygenNote: 6.0.1.9000
Packaged: 2018-05-04 13:16:30 UTC; Xin Qi
X-CRAN-Comment: Archived on 2018-04-30 as wrote to memory it did not own. ASAN/valgrind showed array overrun.
Repository: CRAN
Date/Publication: 2018-05-05 22:17:21 UTC

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Package forecastHybrid updated to version 2.2.12 with previous version 2.1.11 dated 2018-03-27

Title: Convenient Functions for Ensemble Time Series Forecasts
Description: Convenient functions for ensemble forecasts in R combining approaches from the 'forecast' package. Forecasts generated from auto.arima(), ets(), thetam(), nnetar(), stlm(), and tbats() can be combined with equal weights, weights based on in-sample errors, or CV weights. Cross validation for time series data and user-supplied models and forecasting functions is also supported to evaluate model accuracy.
Author: David Shaub [aut, cre], Peter Ellis [aut]
Maintainer: David Shaub <davidshaub@gmx.com>

Diff between forecastHybrid versions 2.1.11 dated 2018-03-27 and 2.2.12 dated 2018-05-06

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Package fixerapi updated to version 0.1.5 with previous version 0.1.1 dated 2018-04-06

Title: An R Client for the "Fixer.io" Currency API
Description: An R client for the "fixer.io" currency conversion and exchange rate API. The API requires registration and some features are only available on paid accounts. The full documentation is available at <https://fixer.io/documentation>.
Author: Evan Odell [aut, cre] (<https://orcid.org/0000-0003-1845-808X>)
Maintainer: Evan Odell <evanodell91@gmail.com>

Diff between fixerapi versions 0.1.1 dated 2018-04-06 and 0.1.5 dated 2018-05-06

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Package filenamer updated to version 0.2.3 with previous version 0.2.2 dated 2018-01-16

Title: Easy Management of File Names
Description: Create descriptive file names with ease. New file names are automatically (but optionally) time stamped and placed in date stamped directories. Streamline your analysis pipeline with input and output file names that have informative tags and proper file extensions.
Author: David J. H. Shih
Maintainer: David J. H. Shih <djh.shih@gmail.com>

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Package FactoMineR updated to version 1.41 with previous version 1.40 dated 2018-03-28

Title: Multivariate Exploratory Data Analysis and Data Mining
Description: Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017) <DOI:10.1201/b10345-2>.
Author: Francois Husson, Julie Josse, Sebastien Le, Jeremy Mazet
Maintainer: Francois Husson <francois.husson@agrocampus-ouest.fr>

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Package FactoInvestigate updated to version 1.3 with previous version 1.1 dated 2017-10-04

Title: Automatic Description of Factorial Analysis
Description: Brings a set of tools to help and automatically realise the description of principal component analyses (from 'FactoMineR' functions). Detection of existing outliers, identification of the informative components, graphical views and dimensions description are performed threw dedicated functions. The Investigate() function performs all these functions in one, and returns the result as a report document (Word, PDF or HTML).
Author: Simon Thuleau, Francois Husson
Maintainer: Simon Thuleau <factoinvestigate@gmail.com>

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Package expoRkit updated to version 0.9.2 with previous version 0.9.1 dated 2018-04-21

Title: Expokit in R
Description: An R-interface to the Fortran package Expokit.
Author: Roger B. Sidje [aut, cph], Niels Richard Hansen [aut, cre, cph]
Maintainer: Niels Richard Hansen <Niels.R.Hansen@math.ku.dk>

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Package esc updated to version 0.4.1 with previous version 0.4.0 dated 2017-11-13

Title: Effect Size Computation for Meta Analysis
Description: Implementation of the web-based 'Practical Meta-Analysis Effect Size Calculator' from David B. Wilson (<http://www.campbellcollaboration.org/escalc/html/EffectSizeCalculator-Home.php>) in R. Based on the input, the effect size can be returned as standardized mean difference, Cohen's f, Hedges' g, Pearson's r or Fisher's transformation z, odds ratio or log odds, or eta squared effect size.
Author: Daniel Lüdecke <d.luedecke@uke.de>
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package epiR updated to version 0.9-96 with previous version 0.9-93 dated 2017-12-11

Title: Tools for the Analysis of Epidemiological Data
Description: Tools for the analysis of epidemiological data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, and computing confidence intervals around incidence risk and incidence rate estimates. Miscellaneous functions for use in meta-analysis, diagnostic test interpretation, and sample size calculations.
Author: Mark Stevenson <mark.stevenson1@unimelb.edu.au> with contributions from Telmo Nunes, Cord Heuer, Jonathon Marshall, Javier Sanchez, Ron Thornton, Jeno Reiczigel, Jim Robison-Cox, Paola Sebastiani, Peter Solymos, Kazuki Yoshida, Geoff Jones, Sarah Pirikahu, Simon Firestone, Ryan Kyle, Johann Popp and Mathew Jay.
Maintainer: Mark Stevenson <mark.stevenson1@unimelb.edu.au>

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Package enrichwith updated to version 0.1.1 with previous version 0.1 dated 2017-11-06

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 <i.kosmidis@ucl.ac.uk>

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Package elementR updated to version 1.3.6 with previous version 1.3.5 dated 2018-02-12

Title: An Framework for Reducing Elemental LAICPMS Data from Solid Structures
Description: Aims to facilitate the reduction of elemental microchemistry data from solid-phase LAICPMS analysis (laser ablation inductive coupled plasma mass spectrometry). The 'elementR' package provides a reactive and user friendly interface (based on a 'shiny' application) and a set of 'R6' classes for conducting all steps needed for an optimal data reduction while leaving maximum control for user.
Author: Charlotte Sirot, Francois Guilhaumon
Maintainer: Charlotte Sirot <charlott.sirot@gmail.com>

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Package ecoval updated to version 1.2 with previous version 1.1 dated 2017-01-20

Title: Procedures for Ecological Assessment of Surface Waters
Description: Functions for evaluating and visualizing ecological assessment procedures for surface waters containing physical, chemical and biological assessments in the form of value functions.
Author: Nele Schuwirth <nele.schuwirth@eawag.ch> and Peter Reichert <peter.reichert@eawag.ch> with contributions by Simone Langhans
Maintainer: Nele Schuwirth <nele.schuwirth@eawag.ch>

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Package easyPubMed updated to version 2.5 with previous version 2.3 dated 2017-02-27

Title: Search and Retrieve Scientific Publication Records from PubMed
Description: Query NCBI Entrez and retrieve PubMed records in XML or text format. Process PubMed records by extracting and aggregating data from selected fields. A large number of records can be easily downloaded via this simple-to-use interface to the NCBI PubMed API.
Author: Damiano Fantini
Maintainer: Damiano Fantini <damiano.fantini@gmail.com>

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Package difNLR updated to version 1.2.2 with previous version 1.2.1 dated 2018-03-05

Title: DIF and DDF Detection by Non-Linear Regression Models
Description: Detection of differential item functioning (DIF) among dichotomously scored items and differential distractor functioning (DDF) among unscored items with non-linear regression procedures based on generalized logistic regression models (Drabinova and Martinkova, 2017, <doi:10.1111/jedm.12158>).
Author: Adela Drabinova [aut, cre], Patricia Martinkova [aut], Karel Zvara [aut]
Maintainer: Adela Drabinova <drabinova@cs.cas.cz>

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Package diceR updated to version 0.5.0 with previous version 0.4.0 dated 2018-02-22

Title: Diverse Cluster Ensemble in R
Description: Performs cluster analysis using an ensemble clustering framework. 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 dendextend updated to version 1.8.0 with previous version 1.7.0 dated 2018-02-11

Title: Extending 'dendrogram' Functionality in R
Description: Offers a set of functions for extending 'dendrogram' objects in R, letting you visualize and compare trees of 'hierarchical clusterings'. You can (1) Adjust a tree's graphical parameters - the color, size, type, etc of its branches, nodes and labels. (2) Visually and statistically compare different 'dendrograms' to one another.
Author: Tal Galili [aut, cre, cph] (https://www.r-statistics.com), Gavin Simpson [ctb], Gregory Jefferis [aut, ctb] (imported code from his dendroextras package), Marco Gallotta [ctb] (a.k.a: marcog), Johan Renaudie [ctb] (https://github.com/plannapus), The R Core Team [ctb] (Thanks for the Infastructure, and code in the examples), Kurt Hornik [ctb], Uwe Ligges [ctb], Andrej-Nikolai Spiess [ctb], Steve Horvath [ctb], Peter Langfelder [ctb], skullkey [ctb], Mark Van Der Loo [ctb] (https://github.com/markvanderloo d3dendrogram), Andrie de Vries [ctb] (ggdendro author), Zuguang Gu [ctb] (circlize author), Cath [ctb] (https://github.com/CathG), John Ma [ctb] (https://github.com/JohnMCMa), Krzysiek G [ctb] (https://github.com/storaged), Manuela Hummel [ctb] (https://github.com/hummelma), Chase Clark [ctb] (https://github.com/chasemc), Yoav Benjamini [ths]
Maintainer: Tal Galili <tal.galili@gmail.com>

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Package DataVisualizations updated to version 1.0.0 with previous version 0.9.2 dated 2018-01-30

Title: Visualizations of High-Dimensional Data
Description: A collection of various visualizations methods is provided. With regards to high-dimensional data the heat map and silhouette plot for grouped data,visualizations of the distribution of distances, the scatter-density plot for two variables,the Shepard density plot as well as the Bland-Altman plot are presented here. For a classification of countries, a map of the world or Germany can be visualized. 'DataVisualizations' makes it possible to inspect the distribution of each feature of a dataset visually through the combination of four methods.More detailed explanations can be found in the book of Thrun, M.C.:"Projection-Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9>. Furthermore, for categorical features the ABC analysis improved Pie charts, slope charts and fan plots are usable. Additionally, for measurements across a geographic area an easy to use function for a Choropleth map is presented here.
Author: Michael Thrun [aut, cre, cph], Peter Kampstra [aut], Felix Pape [aut, rev], Onno Hansen-Goos [ctr, ctb], Fredericke Matz [ctr, ctb], Alfred Ultsch [dtc, ctb]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package dataMaid updated to version 1.1.2 with previous version 1.1.0 dated 2018-02-06

Title: A Suite of Checks for Identification of Potential Errors in a Data Frame as Part of the Data Screening Process
Description: Data screening is an important first step of any statistical analysis. dataMaid autogenerates a customizable data report with a thorough summary of the checks and the results that a human can use to identify possible errors. It provides an extendable suite of test for common potential errors in a dataset.
Author: Anne Helby Petersen [aut], Claus Thorn Ekstrøm [aut, cre]
Maintainer: Claus Thorn Ekstrøm <ekstrom@sund.ku.dk>

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Package DatabionicSwarm updated to version 1.0.3 with previous version 1.0.1 dated 2018-03-07

Title: Swarm Intelligence for Self-Organized Clustering
Description: Algorithms implementing populations of agents that interact with one another and sense their environment may exhibit emergent behavior such as self-organization and swarm intelligence. Here, a swarm system called databionic swarm (DBS) is introduced. DBS is able to adapt itself to structures of high-dimensional data such as natural clusters characterized by distance and/or density based structures in the data space. The first module is the parameter-free projection method called Pswarm (Pswarm()), which exploits the concepts of self-organization and emergence, game theory, swarm intelligence and symmetry considerations. The second module is the parameter-free high-dimensional data visualization technique, which generates projected points on the topographic map with hypsometric tints defined by the generalized U-matrix (GeneratePswarmVisualization()). The third module is the clustering method itself with non-critical parameters (DBSclustering()). Clustering can be verified by the visualization and vice versa. The term DBS refers to the method as a whole. It enables even a non-professional in the field of data mining to apply its algorithms for visualization and/or clustering to data sets with completely different structures drawn from diverse research fields. The package is based on the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9>. A comparison to 26 common clustering algorithms on 15 datasets is presented on the website.
Author: Michael Thrun [aut, cre, cph]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package DAC updated to version 0.1.1 with previous version 0.1.0 dated 2017-09-08

Title: Calculating Data Agreement Criterion Scores to Rank Experts Based on Their Beliefs
Description: Allows to calculate Data Agreement Criterion (DAC) scores. This can be done to determine prior-data conflict or to evaluate and compare multiple priors, which can be experts' predictions. Bousquet (2008) <doi.org/10.1080/02664760802192981>.
Author: Duco Veen [aut, cre], Naomi Schalken [aut], Rens van de Schoot [aut]
Maintainer: Duco Veen <ducoveen@gmail.com>

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Package Cyclops updated to version 1.3.2 with previous version 1.3.0 dated 2017-08-23

Title: Cyclic Coordinate Descent for Logistic, Poisson and Survival Analysis
Description: This model fitting tool incorporates cyclic coordinate descent and majorization-minimization approaches to fit a variety of regression models found in large-scale observational healthcare data. Implementations focus on computational optimization and fine-scale parallelization to yield efficient inference in massive datasets.
Author: Marc A. Suchard [aut, cre], Martijn J. Schuemie [aut], Trevor R. Shaddox [aut]
Maintainer: Marc A. Suchard <msuchard@ucla.edu>

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More information about Cyclops at CRAN
Permanent link

New package cyclestreets with initial version 0.1.5
Package: cyclestreets
Type: Package
Title: Cycle Routing and Data for Cycling Advocacy
Version: 0.1.5
Authors@R: c( person("Robin", "Lovelace", email = "rob00x@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5679-6536")), person("Martin", "Lucas-Smith", role = c("aut")), person("Eric", "Krueger", role = c("ctb")) )
Description: An interface to the cycle routing/data services provided by 'CycleStreets', a not-for-profit social enterprise and advocacy organisation. The application programming interfaces (APIs) provided by 'CycleStreets' are documented at (<https://www.cyclestreets.net/api/>). The focus of this package is the journey planning API, which aims to emulate the routes taken by a knowledgeable cyclist. An innovative feature of the routing service of its provision of fastest, quietest and balanced profiles. These represent routes taken to minimise time, avoid traffic and compromise between the two, respectively.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: sf, magrittr, jsonlite, httr, stringr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-03 11:56:01 UTC; rstudio
Author: Robin Lovelace [aut, cre] (<https://orcid.org/0000-0001-5679-6536>), Martin Lucas-Smith [aut], Eric Krueger [ctb]
Maintainer: Robin Lovelace <rob00x@gmail.com>
Repository: CRAN
Date/Publication: 2018-05-03 12:28:11 UTC

More information about cyclestreets at CRAN
Permanent link

New package crsra with initial version 0.2.3
Package: crsra
Title: Tidying and Analyzing 'Coursera' Research Export Data
Version: 0.2.3
Authors@R: c(person(given = "Aboozar", family = "Hadavand", email ="hadavand.a@gmail.com", role = c("aut", "cre")), person(given = "Jeff", family = "Leek", role = "aut"), person(given = "John", family = "Muschelli", role = "aut"))
Description: Tidies and performs preliminary analysis of 'Coursera' research export data. These export data can be downloaded by anyone who has classes on Coursera and wants to analyze the data. Coursera is one of the leading providers of MOOCs and was launched in January 2012. With over 25 million learners, Coursera is the most popular provider in the world being followed by EdX, the MOOC provider that was a result of a collaboration between Harvard University and MIT, with over 10 million users. Coursera has over 150 university partners from 29 countries and offers a total of 2000+ courses from computer science to philosophy. Besides, Coursera offers 180+ specialization, Coursera's credential system, and four fully online Masters degrees. For more information about Coursera check Coursera's About page on <https://blog.coursera.org/about/>.
Depends: R (>= 2.10)
License: GPL-2
Encoding: UTF-8
LazyData: true
Suggests: utils, testthat, rmarkdown
Imports: dplyr, purrr, readr, digest, tidytext, tibble, rcorpora, knitr
BugReports: https://github.com/jhudsl/crsra/issues
RoxygenNote: 6.0.1.9000
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-05-05 00:04:01 UTC; Hadzzz
Author: Aboozar Hadavand [aut, cre], Jeff Leek [aut], John Muschelli [aut]
Maintainer: Aboozar Hadavand <hadavand.a@gmail.com>
Repository: CRAN
Date/Publication: 2018-05-05 06:25:58 UTC

More information about crsra at CRAN
Permanent link

Package CRF updated to version 0.3-15 with previous version 0.3-14 dated 2017-02-01

Title: Conditional Random Fields
Description: Implements modeling and computational tools for conditional random fields (CRF) model as well as other probabilistic undirected graphical models of discrete data with pairwise and unary potentials.
Author: Ling-Yun Wu [aut, cre]
Maintainer: Ling-Yun Wu <wulingyun@gmail.com>

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Package covsep updated to version 1.1.0 with previous version 1.0.0 dated 2016-01-28

Title: Tests for Determining if the Covariance Structure of 2-Dimensional Data is Separable
Description: Functions for testing if the covariance structure of 2-dimensional data (e.g. samples of surfaces X_i = X_i(s,t)) is separable, i.e. if covariance(X) = C_1 x C_2. A complete descriptions of the implemented tests can be found in the paper Aston, John A. D.; Pigoli, Davide; Tavakoli, Shahin. Tests for separability in nonparametric covariance operators of random surfaces. Ann. Statist. 45 (2017), no. 4, 1431--1461. <doi:10.1214/16-AOS1495> <https://projecteuclid.org/euclid.aos/1498636862> <arXiv:1505.02023>.
Author: Shahin Tavakoli [aut, cre], Davide Pigoli [ctb], John Aston [ctb]
Maintainer: Shahin Tavakoli <s.tavakoli@warwick.ac.uk>

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Package configr updated to version 0.3.2.2 with previous version 0.3.2.1 dated 2018-02-26

Title: An Implementation of Parsing and Writing Configuration File (JSON/INI/YAML/TOML)
Description: Implements the JSON, INI, YAML and TOML parser for R setting and writing of configuration file. The functionality of this package is similar to that of package 'config'.
Author: Jianfeng Li [aut, cre] (<https://orcid.org/0000-0003-2349-208X>)
Maintainer: Jianfeng Li <lee_jianfeng@sjtu.edu.cn>

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Package comtradr updated to version 0.2.1 with previous version 0.1.0 dated 2017-10-23

Title: Interface with the United Nations Comtrade API
Description: Interface with and extract data from the United Nations Comtrade API <https://comtrade.un.org/data/>. Comtrade provides country level shipping data for a variety of commodities, these functions allow for easy API query and data returned as a tidy data frame.
Author: Chris Muir [aut, cre], Alicia Schep [rev] (<https://orcid.org/0000-0002-3915-0618>, Alicia reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/141), Rafael Hellwig [rev] (<https://orcid.org/0000-0002-3092-3493>, Rafael reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/141)
Maintainer: Chris Muir <chrismuirRVA@gmail.com>

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Package codemetar updated to version 0.1.6 with previous version 0.1.5 dated 2018-03-21

Title: Generate 'CodeMeta' Metadata for R Packages
Description: The 'Codemeta' Project defines a 'JSON-LD' format for describing software metadata, as detailed at <https://codemeta.github.io>. This package provides utilities to generate, parse, and modify 'codemeta.json' files automatically for R packages, as well as tools and examples for working with 'codemeta.json' 'JSON-LD' more generally.
Author: Carl Boettiger [aut, cre, cph] (<https://orcid.org/0000-0002-1642-628X>), Anna Krystalli [rev, ctb] (<https://orcid.org/0000-0002-2378-4915>), Toph Allen [rev] (<https://orcid.org/0000-0003-4580-091X>), Maëlle Salmon [ctb, aut] (<https://orcid.org/0000-0002-2815-0399>), rOpenSci [fnd] (https://ropensci.org/), Katrin Leinweber [ctb], Noam Ross [ctb] (<https://orcid.org/0000-0002-2136-0000>), Arfon Smith [ctb], Jeroen Ooms [ctb] (<https://orcid.org/0000-0002-4035-0289>)
Maintainer: Carl Boettiger <cboettig@gmail.com>

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Package cobalt updated to version 3.2.3 with previous version 3.2.2 dated 2018-03-13

Title: Covariate Balance Tables and Plots
Description: Generate balance tables and plots for covariates of groups preprocessed through matching, weighting or subclassification, for example, using propensity scores. Includes integration with 'MatchIt', 'twang', 'Matching', 'optmatch', 'CBPS', 'ebal', and 'WeightIt' for assessing balance on the output of their preprocessing functions. Users can also specify data for balance assessment not generated through the above packages. Also included are methods for assessing balance in clustered or multiply imputed data sets.
Author: Noah Greifer [aut, cre]
Maintainer: Noah Greifer <noah.greifer@gmail.com>

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Package clustrd updated to version 1.2.2 with previous version 1.2.1 dated 2018-04-16

Title: Methods for Joint Dimension Reduction and Clustering
Description: A class of methods that combine dimension reduction and clustering of continuous or categorical data. For continuous data, the package contains implementations of factorial K-means (Vichi and Kiers 2001; <DOI:10.1016/S0167-9473(00)00064-5>) and reduced K-means (De Soete and Carroll 1994; <DOI:10.1007/978-3-642-51175-2_24>); both methods that combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means (Hwang, Dillon and Takane 2006; <DOI:10.1007/s11336-004-1173-x>), i-FCB (Iodice D'Enza and Palumbo 2013, <DOI:10.1007/s00180-012-0329-x>) and Cluster Correspondence Analysis (van de Velden, Iodice D'Enza and Palumbo 2017; <DOI:10.1007/s11336-016-9514-0>), which combine multiple correspondence analysis with K-means.
Author: Angelos Markos [aut, cre], Alfonso Iodice D'Enza [aut], Michel van de Velden [ctb]
Maintainer: Angelos Markos <amarkos@gmail.com>

Diff between clustrd versions 1.2.1 dated 2018-04-16 and 1.2.2 dated 2018-05-06

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Package ClusterR updated to version 1.1.2 with previous version 1.1.1 dated 2018-02-26

Title: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans and K-Medoids Clustering
Description: Gaussian mixture models, k-means, mini-batch-kmeans and k-medoids 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>.
Author: Lampros Mouselimis <mouselimislampros@gmail.com>
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>

Diff between ClusterR versions 1.1.1 dated 2018-02-26 and 1.1.2 dated 2018-05-06

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Package clinDR updated to version 1.8 with previous version 1.7 dated 2018-02-19

Title: Simulation and Analysis Tools for Clinical Dose Response Modeling
Description: Bayesian and ML Emax model fitting, graphics and simulation for clinical dose response. The summary data from the dose response meta-analyses in Thomas, Sweeney, and Somayaji (2014) <doi:10.1080/19466315.2014.924876> and Thomas and Roy (2016) <doi:10.1080/19466315.2016.1256229> are included in the package. The prior distributions for the Bayesian analyses default to the posterior predictive distributions derived from these references.
Author: Neal Thomas [aut, cre] (<https://orcid.org/0000-0002-1915-8487>), Jing Wu [aut]
Maintainer: Neal Thomas <snthomas99@gmail.com>

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Package climatol updated to version 3.1.1 with previous version 3.1 dated 2018-04-26

Title: Climate Tools (Series Homogenization and Derived Products)
Description: Functions for the quality control, homogenization and missing data infilling of climatological series and to obtain climatological summaries and grids from the results. Also functions to draw wind-roses and Walter&Lieth climate diagrams.
Author: Jose A. Guijarro <jguijarrop@aemet.es>
Maintainer: Jose A. Guijarro <jguijarrop@aemet.es>

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Package civis updated to version 1.4.0 with previous version 1.3.0 dated 2018-03-30

Title: R Client for the 'Civis data science API'
Description: A set of tools around common workflows and a convenient interface to make requests directly to the 'Civis data science API' <https://www.civisanalytics.com/platform/>.
Author: Patrick Miller [cre, aut], Keith Ingersoll [aut], Bill Lattner [ctb], Anh Le [ctb], Michelangelo D'Agostino [ctb], Sam Weiss [ctb], Stephen Hoover [ctb], Danning Chen [ctb], Elizabeth Sander [ctb]
Maintainer: Patrick Miller <pmiller@civisanalytics.com>

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Package catenary updated to version 1.1.2 with previous version 1.1.1 dated 2015-11-18

Title: Fits a Catenary to Given Points
Description: Gives methods to create a catenary object and then plot it and get properties of it. Can construct from parameters or endpoints. Also can get catenary fitted to data.
Author: Jonathan Tuke [aut, cre], Matthew Roughan [aut]
Maintainer: Jonathan Tuke <simon.tuke@adelaide.edu.au>

Diff between catenary versions 1.1.1 dated 2015-11-18 and 1.1.2 dated 2018-05-06

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Package CAST updated to version 0.2.0 with previous version 0.1.0 dated 2018-01-09

Title: 'caret' Applications for Spatial-Temporal Models
Description: Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. This package includes functions to improve spatial-temporal modelling tasks using 'caret'. It prepares data for Leave-Location-Out and Leave-Time-Out cross-validation which are target-oriented validation strategies for spatial-temporal models. To decrease overfitting and improve model performances, the package implements a forward feature selection that selects suitable predictor variables in view to their contribution to the target-oriented performance.
Author: Hanna Meyer [cre, aut], Chris Reudenbach [ctb], Marvin Ludwig [ctb], Thomas Nauss [ctb]
Maintainer: Hanna Meyer <hanna.meyer@geo.uni-marburg.de>

Diff between CAST versions 0.1.0 dated 2018-01-09 and 0.2.0 dated 2018-05-06

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Package boral updated to version 1.6 with previous version 1.5 dated 2018-01-08

Title: Bayesian Ordination and Regression AnaLysis
Description: Bayesian approaches for analyzing multivariate data in ecology. Estimation is performed using Markov Chain Monte Carlo (MCMC) methods via Three. JAGS types of models may be fitted: 1) With explanatory variables only, boral fits independent column Generalized Linear Models (GLMs) to each column of the response matrix; 2) With latent variables only, boral fits a purely latent variable model for model-based unconstrained ordination; 3) With explanatory and latent variables, boral fits correlated column GLMs with latent variables to account for any residual correlation between the columns of the response matrix.
Author: Francis K.C. Hui <fhui28@gmail.com>, with contributions from Wafe Blanchard <wade.blanchard@anu.edu.au>
Maintainer: Francis Hui <fhui28@gmail.com>

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New package bioacoustics with initial version 0.1.0
Package: bioacoustics
Type: Package
Title: Analyse Audio Recordings and Automatically Extract Animal Vocalizations
Version: 0.1.0
Authors@R: c(person("Jean", "Marchal", email = "jean.marchal@wavx.ca", role = c("aut","cre")), person("Francois", "Fabianek", email = "francois.fabianek@wavx.ca", role = "aut"), person("Christopher", "Scott", role = "aut"), person("Chris", "Corben", role = c("ctb", "cph"), email = "chris@hoarybat.com", comment = "Read ZC files, original C code"), person("Peter", "Wilson", role = c("ctb", "cph"), email = "peter@peterwilson.id.au", comment = "Read ZC files, original R code"), person(family = "Wildlife Acoustics, Inc.", role = c("ctb", "cph"), comment = "Read WAC files, original C code"), person(family = "WavX Inc.", role = "cph"))
Maintainer: Jean Marchal <jean.marchal@wavx.ca>
Description: Contains all the necessary tools to process audio recordings of various formats (e.g., WAV, WAC, MP3, ZC), filter noisy files, display audio signals, detect and extract automatically acoustic features for further analysis such as classification.
License: GPL-3
Encoding: UTF-8
LazyData: true
SystemRequirements: C++11
Depends: R (>= 3.3.0)
LinkingTo: Rcpp
Imports: htmltools, graphics, grDevices, methods, moments, Rcpp (>= 0.12.13), stringr, tools, tuneR (>= 1.3.0)
Suggests: knitr, rmarkdown
URL: https://github.com/wavx/bioacoustics/
BugReports: https://github.com/wavx/bioacoustics/issues/
NeedsCompilation: yes
RoxygenNote: 6.0.1
VignetteBuilder: knitr
Biarch: TRUE
Packaged: 2018-04-27 17:52:58 UTC; JEMAR270
Author: Jean Marchal [aut, cre], Francois Fabianek [aut], Christopher Scott [aut], Chris Corben [ctb, cph] (Read ZC files, original C code), Peter Wilson [ctb, cph] (Read ZC files, original R code), Wildlife Acoustics, Inc. [ctb, cph] (Read WAC files, original C code), WavX Inc. [cph]
Repository: CRAN
Date/Publication: 2018-05-03 09:06:37 UTC

More information about bioacoustics at CRAN
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Package beam updated to version 1.0.2 with previous version 1.0.1 dated 2018-04-18

Title: Fast Bayesian Inference in Large Gaussian Graphical Models
Description: Fast Bayesian inference of marginal and conditional independence structures between variables from high-dimensional data (Leday and Richardson (2018) <arXiv:1803.08155>).
Author: Gwenael G.R. Leday [cre, aut], Ilaria Speranza [aut], Harry Gray [ctb]
Maintainer: Gwenael G.R. Leday <gwenael.leday@mrc-bsu.cam.ac.uk>

Diff between beam versions 1.0.1 dated 2018-04-18 and 1.0.2 dated 2018-05-06

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Package BDgraph updated to version 2.48 with previous version 2.47 dated 2018-04-25

Title: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC
Description: Provides statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <https://doi:10.1214/14-BA889> and Mohammadi et al. (2017) <https://doi:10.1111/rssc.12171>. To speed up the computations, the BDMCMC sampling algorithms are implemented in parallel using OpenMP in C++.
Author: Reza Mohammadi <https://orcid.org/0000-0001-9538-0648> and Ernst Wit <https://orcid.org/0000-0002-3671-9610>
Maintainer: Reza Mohammadi <a.mohammadi@uva.nl>

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Package BAS updated to version 1.5.0 with previous version 1.4.9 dated 2018-03-25

Title: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling
Description: Package for Bayesian Variable Selection and Model Averaging in linear models and generalized linear models using stochastic or deterministic sampling without replacement from posterior distributions. Prior distributions on coefficients are from Zellner's g-prior or mixtures of g-priors corresponding to the Zellner-Siow Cauchy Priors or the mixture of g-priors from Liang et al (2008) <DOI:10.1198/016214507000001337> for linear models or mixtures of g-priors in GLMs of Li and Clyde (2015) <arXiv:1503.06913>. Other model selection criteria include AIC, BIC and Empirical Bayes estimates of g. Sampling probabilities may be updated based on the sampled models using Sampling w/out Replacement or an efficient MCMC algorithm samples models using the BAS tree structure as an efficient hash table. Uniform priors over all models or beta-binomial prior distributions on model size are allowed, and for large p truncated priors on the model space may be used. The user may force variables to always be included. Details behind the sampling algorithm are provided in Clyde, Ghosh and Littman (2010) <DOI:10.1198/jcgs.2010.09049>. This material is based upon work supported by the National Science Foundation under Grant DMS-1106891. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Author: Merlise Clyde [aut, cre, cph] (<https://orcid.org/-5469>), Michael Littman [ctb], Quanli Wang [ctb], Joyee Ghosh [ctb], Yingbo Li [ctb]
Maintainer: Merlise Clyde <clyde@duke.edu>

Diff between BAS versions 1.4.9 dated 2018-03-25 and 1.5.0 dated 2018-05-06

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Package Barycenter updated to version 1.3.1 with previous version 1.3 dated 2018-03-05

Title: Regularized Wasserstein Distances and Barycenters
Description: Computations of entropy regularized Wasserstein Distances, a.k.a. dual-Sinkhorn divergences, and entropy regularized Wasserstein Barycenters. Relevant papers are Marco Cuturi (2013) <arXiv:1306.0895>, Marco Cuturi (2014) <arXiv:1310.4375> and Jason Altschuler et al. <arXiv:1705.09634>.
Author: Marcel Klatt
Maintainer: Marcel Klatt <marcel.klatt@stud.uni-goettingen.de>

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Package bartMachine updated to version 1.2.4.2 with previous version 1.2.4.1 dated 2018-04-06

Title: Bayesian Additive Regression Trees
Description: An advanced implementation of Bayesian Additive Regression Trees with expanded features for data analysis and visualization.
Author: Adam Kapelner and Justin Bleich (R package)
Maintainer: Adam Kapelner <kapelner@qc.cuny.edu>

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

Title: Allele Frequency Comparison
Description: When doing association analysis one does not always have the genotypes for the control population. In such cases it may be necessary to fall back on frequency based tests using well known sources for the frequencies in the control population, for instance, from the 1000 Genomes Project. The Allele Frequency Comparison ('AssocAFC') package performs multiple rare variant association analyses in both population and family-based GWAS (Genome-Wide Association Study) designs. It includes three score tests that are based on the difference of the sum of allele frequencies between cases and controls. Two of these tests, Wcorrected() and Wqls(), are collapsing-based tests and suffer from having protective and risk variants. The third test, afcSKAT(), is a score test that overcomes the mix of SNP (Single-Nucleotide Polymorphism) effect directions. For more details see Saad M and Wijsman EM (2017) <doi:10.1093/bib/bbx107>.
Author: Khalid B. Kunji [aut, cre], Mohamad Saad [aut]
Maintainer: Khalid B. Kunji <kkunji@hbku.edu.qa>

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Package aroma.core updated to version 3.1.3 with previous version 3.1.2 dated 2018-04-24

Title: Core Methods and Classes Used by 'aroma.*' Packages Part of the Aroma Framework
Description: Core methods and classes used by higher-level 'aroma.*' packages part of the Aroma Project, e.g. 'aroma.affymetrix' and 'aroma.cn'.
Author: Henrik Bengtsson [aut, cre, cph], Mark Robinson [ctb], Ken Simpson [ctb]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

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Package AMR updated to version 0.2.0 with previous version 0.1.1 dated 2018-03-14

Title: Antimicrobial Resistance Analysis
Description: Functions to simplify the analysis of Antimicrobial Resistance (AMR) of microbial isolates, by using new S3 classes and applying EUCAST expert rules on antibiograms according to Leclercq (2013) <doi:10.1111/j.1469-0691.2011.03703.x>.
Author: Matthijs S. Berends [aut, cre] (<https://orcid.org/0000-0001-7620-1800>), Christian F. Luz [aut, ctb] (<https://orcid.org/0000-0001-5809-5995>), Erwin E.A. Hassing [ctb]
Maintainer: Matthijs S. Berends <m.s.berends@umcg.nl>

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Package ameco updated to version 0.2.9 with previous version 0.2.8 dated 2017-11-13

Title: European Commission Annual Macro-Economic (AMECO) Database
Description: Annual macro-economic database provided by the European Commission.
Author: Eric Persson [aut, cre]
Maintainer: Eric Persson <expersso5@gmail.com>

Diff between ameco versions 0.2.8 dated 2017-11-13 and 0.2.9 dated 2018-05-06

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New package airr with initial version 1.1.0
Package: airr
Type: Package
Version: 1.1.0
Date: 2018-05-01
Authors@R: c(person("Jason", "Vander Heiden", role=c("aut", "cre"), email="jason.vanderheiden@yale.edu"), person("Susanna", "Marquez", role=c("aut"), email="susanna.marquez@yale.edu"), person("AIRR Community", role=c("cph")))
Title: AIRR Data Representation Standards
Description: Schema definitions and read, write and validation tools for data formatted in accordance with the AIRR Data Representation standards defined by the AIRR Community <http://docs.airr-community.org>.
License: CC BY 4.0
URL: http://docs.airr-community.org
BugReports: https://github.com/airr-community/airr-standards/issues
LazyData: true
BuildVignettes: true
VignetteBuilder: knitr
Depends: R (>= 3.1.2)
Imports: methods, readr, stats, stringi, yaml
Suggests: knitr, rmarkdown, testthat
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-02 22:55:55 UTC; jason
Author: Jason Vander Heiden [aut, cre], Susanna Marquez [aut], AIRR Community [cph]
Maintainer: Jason Vander Heiden <jason.vanderheiden@yale.edu>
Repository: CRAN
Date/Publication: 2018-05-03 11:09:29 UTC

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

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2015-01-13 0.1.0

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Package FisherEM (with last version 1.4) was removed from CRAN

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

2013-06-28 1.4
2013-02-21 1.3.2
2013-02-20 1.3.1
2013-02-13 1.3
2012-07-12 1.2
2011-05-29 1.1.2
2011-05-11 1.0

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Package Combine (with last version 1.0) was removed from CRAN

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2015-09-04 1.0

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Package CHAT (with last version 1.1) was removed from CRAN

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2014-08-08 1.1
2014-04-30 1.0

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Package CircE (with last version 1.1) was removed from CRAN

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2014-09-09 1.1
2014-04-11 1.0

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Package BANFF (with last version 2.0) was removed from CRAN

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2017-03-12 2.0
2016-07-12 1.1
2015-10-12 1.0
2015-02-16 0.3
2015-01-08 0.2
2014-12-29 0.1

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Package CompetingRisk (with last version 1.0) was removed from CRAN

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2017-03-02 1.0

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Package BioPhysConnectoR (with last version 1.6-10) was removed from CRAN

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2013-01-09 1.6-10
2012-11-16 1.6-9

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Package BlockFeST (with last version 1.3) was removed from CRAN

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2018-02-12 1.3

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Package EpiWeek (with last version 1.1) was removed from CRAN

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2016-04-28 1.1

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