Tue, 05 Dec 2017

Package regsem updated to version 1.0.6 with previous version 0.9.2 dated 2017-09-08

Title: Regularized Structural Equation Modeling
Description: Uses both ridge and lasso penalties (and extensions) to penalize specific parameters in structural equation models. The package offers additional cost functions, cross validation, and other extensions beyond traditional structural equation models.
Author: Ross Jacobucci[aut,cre], Kevin J. Grimm [ctb], Andreas M. Brandmaier [ctb], Sarfaraz Serang [ctb]
Maintainer: Ross Jacobucci <rcjacobuc@gmail.com>

Diff between regsem versions 0.9.2 dated 2017-09-08 and 1.0.6 dated 2017-12-05

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Package TriMatch updated to version 0.9.9 with previous version 0.9.7 dated 2016-02-26

Title: Propensity Score Matching of Non-Binary Treatments
Description: Propensity score matching for non-binary treatments.
Author: Jason Bryer <jason@bryer.org>
Maintainer: Jason Bryer <jason@bryer.org>

Diff between TriMatch versions 0.9.7 dated 2016-02-26 and 0.9.9 dated 2017-12-05

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Package netmeta updated to version 0.9-7 with previous version 0.9-6 dated 2017-08-09

Title: Network Meta-Analysis using Frequentist Methods
Description: A comprehensive set of functions providing frequentist methods for network meta-analysis and supporting Schwarzer et al. (2015) <DOI:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <DOI:10.1002/jrsm.1058>; - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) <DOI:10.1186/1471-2288-13-35>; - measures characterizing the flow of evidence between two treatments by König et al. (2013) <DOI:10.1002/sim.6001>; - ranking of treatments (frequentist analogue of SUCRA) according to Rücker & Schwarzer (2015) <DOI:10.1186/s12874-015-0060-8>; - partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) <DOI:10.1002/cem.2569>; (Rücker & Schwarzer, 2017) <DOI:10.1002/jrsm.1270>; - split direct and indirect evidence to check consistency (Dias et al., 2010) <DOI:10.1002/sim.3767>; - league table with network meta-analysis results; - additive network meta-analysis for combinations of treatments; - automated drawing of network graphs described in Rücker & Schwarzer (2016) <DOI:10.1002/jrsm.1143>.
Author: Gerta Rücker [aut], Guido Schwarzer [aut, cre], Ulrike Krahn [aut], Jochem König [aut]
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

Diff between netmeta versions 0.9-6 dated 2017-08-09 and 0.9-7 dated 2017-12-05

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Package metasens updated to version 0.3-2 with previous version 0.3-1 dated 2016-10-15

Title: Advanced Statistical Methods to Model and Adjust for Bias in Meta-Analysis
Description: The following methods are implemented to evaluate how sensitive the results of a meta-analysis are to potential bias in meta-analysis and to support Schwarzer et al. (2015) <DOI:10.1007/978-3-319-21416-0>, Chapter 5 "Small-Study Effects in Meta-Analysis": - Copas selection model described in Copas & Shi (2001) <DOI:10.1177/096228020101000402>; - limit meta-analysis by Rücker et al. (2011) <DOI:10.1093/biostatistics/kxq046>; - upper bound for outcome reporting bias by Copas & Jackson (2004) <DOI:10.1111/j.0006-341X.2004.00161.x>.
Author: Guido Schwarzer [aut, cre], James R. Carpenter [aut], Gerta Rücker [aut]
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

Diff between metasens versions 0.3-1 dated 2016-10-15 and 0.3-2 dated 2017-12-05

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Package meta updated to version 4.9-0 with previous version 4.8-4 dated 2017-08-11

Title: General Package for Meta-Analysis
Description: User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015): - fixed effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - statistical tests and trim-and-fill method to evaluate bias in meta-analysis; - import data from 'RevMan 5'; - prediction interval, Hartung-Knapp and Paule-Mandel method for random effects model; - cumulative meta-analysis and leave-one-out meta-analysis; - meta-regression (if R package 'metafor' is installed); - generalised linear mixed models (if R packages 'metafor', 'lme4', 'numDeriv', and 'BiasedUrn' are installed); - produce forest plot summarising several (subgroup) meta-analyses.
Author: Guido Schwarzer [cre, aut]
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

Diff between meta versions 4.8-4 dated 2017-08-11 and 4.9-0 dated 2017-12-05

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Package sptm updated to version 17.12-7 with previous version 16.7-9 dated 2016-07-10

Title: SemiParametric Transformation Model Methods
Description: Implements semiparametric transformation model two-phase estimation using calibration weights. The method in Fong and Gilbert (2015) Calibration weighted estimation of semiparametric transformation models for two-phase sampling. Statistics in Medicine <DOI:10.1002/sim.6439>.
Author: Youyi Fong [cre], Krisztian Sebestyen [aut], Martin Maechler [ctb]
Maintainer: Youyi Fong <youyifong@gmail.com>

Diff between sptm versions 16.7-9 dated 2016-07-10 and 17.12-7 dated 2017-12-05

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Package mmpf updated to version 0.0.4 with previous version 0.0.3 dated 2017-03-05

Title: Monte-Carlo Methods for Prediction Functions
Description: Marginalizes prediction functions using Monte-Carlo integration and computes permutation importance.
Author: Zachary Jones [aut, cre]
Maintainer: Zachary Jones <zmj@zmjones.com>

Diff between mmpf versions 0.0.3 dated 2017-03-05 and 0.0.4 dated 2017-12-05

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Package foghorn updated to version 1.0.0 with previous version 0.4.4 dated 2017-05-22

Title: Summarize CRAN Check Results in the Terminal
Description: The CRAN check results in your R terminal.
Author: Francois Michonneau [aut, cre], Ben Bolker [ctb]
Maintainer: Francois Michonneau <francois.michonneau@gmail.com>

Diff between foghorn versions 0.4.4 dated 2017-05-22 and 1.0.0 dated 2017-12-05

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Package sglg updated to version 0.1.2 with previous version 0.1.1 dated 2017-11-13

Title: Fitting Semi-Parametric Generalized log-Gamma Regression Models
Description: Set of tools to fit a linear multiple or semi-parametric regression models and non-informative right-censoring may be considered. Under this setup, the localization parameter of the response variable distribution is modeled by using linear multiple regression or semi-parametric functions, whose non-parametric components may be approximated by natural cubic spline or P-splines. The supported distribution for the model error is a generalized log-gamma distribution which includes the generalized extreme value distribution as an important special case.
Author: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com> and G. Paula and L. Vanegas
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>

Diff between sglg versions 0.1.1 dated 2017-11-13 and 0.1.2 dated 2017-12-05

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Package ioncopy updated to version 2.0 with previous version 1.0 dated 2015-08-26

Title: Calling Copy Number Alterations in Amplicon Sequencing Data
Description: Method for the calculation of copy numbers and calling of copy number alterations. The algorithm uses coverage data from amplicon sequencing of a sample cohort as input. The method includes significance assessment, correction for multiple testing and does not depend on normal DNA controls.
Author: Jan Budczies, Eva Romanovsky
Maintainer: Jan Budczies <jan.budczies@charite.de>

Diff between ioncopy versions 1.0 dated 2015-08-26 and 2.0 dated 2017-12-05

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Package VARSEDIG updated to version 1.5 with previous version 1.4 dated 2017-09-01

Title: An Algorithm for Morphometric Characters Selection and Statistical Validation in Morphological Taxonomy
Description: An algorithm (Guisande et al., 2016 <doi:10.11646/zootaxa.4162.3.10>) which identifies the morphometric features that significantly discriminate two taxa and validates the morphological distinctness between them via a Monte-Carlo test, polar coordinates and overlap of the area under the density curve.
Author: Cstor Guisande Gonzlez
Maintainer: Cstor Guisande Gonzlez <castor@uvigo.es>

Diff between VARSEDIG versions 1.4 dated 2017-09-01 and 1.5 dated 2017-12-05

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Package ghibli updated to version 0.1.1 with previous version 0.1.0 dated 2017-08-14

Title: Studio Ghibli Palette Generator
Description: Colour palettes inspired by Studio Ghibli films, ported to R for your enjoyment.
Author: Ewen Henderson [aut, cre]
Maintainer: Ewen Henderson <ewenhenderson@gmail.com>

Diff between ghibli versions 0.1.0 dated 2017-08-14 and 0.1.1 dated 2017-12-05

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Package mltools updated to version 0.3.4 with previous version 0.3.3 dated 2017-09-12

Title: Machine Learning Tools
Description: A collection of machine learning helper functions, particularly assisting in the Exploratory Data Analysis phase. Makes heavy use of the 'data.table' package for optimal speed and memory efficiency. Highlights include a versatile bin_data() function, sparsify() for converting a data.table to sparse matrix format with one-hot encoding, fast evaluation metrics, and empirical_cdf() for calculating empirical Multivariate Cumulative Distribution Functions.
Author: Ben Gorman
Maintainer: Ben Gorman <bgorman@GormAnalysis.com>

Diff between mltools versions 0.3.3 dated 2017-09-12 and 0.3.4 dated 2017-12-05

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New package Rnumerai with initial version 0.1
Package: Rnumerai
Title: Interface to the Numerai Machine Learning Tournament API
Version: 0.1
Authors@R: c( person("Omni Analytics Group", email = "services@omnianalytics.io", role = "aut"), person("Eric Hare", email = "eric@omnianalytics.io", role = "cre"))
Description: Routines to interact with the Numerai Machine Learning Tournament API <https://numer.ai>. The functionality includes the ability to automatically download the current tournament data, submit predictions, and to get information for your user. General 'GraphQL' queries can also be executed.
Depends: R (>= 3.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/Omni-Analytics-Group/Rnumerai
BugReports: https://github.com/Omni-Analytics-Group/Rnumerai/issues
RoxygenNote: 6.0.1
Imports: httr, lubridate
NeedsCompilation: no
Packaged: 2017-12-05 13:48:47 UTC; erichare
Author: Omni Analytics Group [aut], Eric Hare [cre]
Maintainer: Eric Hare <eric@omnianalytics.io>
Repository: CRAN
Date/Publication: 2017-12-05 18:31:49 UTC

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New package rENA with initial version 0.1.1
Package: rENA
Title: Epistemic Network Analysis
Type: Package
Author: Cody L Marquart [aut, cre], Zachari Swiecki [aut], Wesley Collier [aut], Brendan Eagan [aut], Roman Woodward [aut], David Williamson Shaffer [aut]
Authors@R: c(person("Cody L","Marquart", role = c("aut", "cre"), email="cody.marquart@wisc.edu"),person("Zachari","Swiecki", role = c("aut"), email="swiecki@wisc.edu"),person("Wesley","Collier", role = c("aut"), email="wcollier@wisc.edu"),person("Brendan","Eagan", role = c("aut"), email="beagan@wisc.edu"),person("Roman", "Woodward", role = c("aut"), email="rwoodward3@wisc.edu"),person("David", "Williamson Shaffer", role = c("aut"), email = "dws@education.wisc.edu"))
Maintainer: Cody L Marquart <cody.marquart@wisc.edu>
Version: 0.1.1
Description: ENA (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is a method used to identify meaningful and quantifiable patterns in discourse or reasoning. ENA moves beyond the traditional frequency-based assessments by examining the structure of the co-occurrence, or connections in coded data. Moreover, compared to other methodological approaches, ENA has the novelty of (1) modeling whole networks of connections and (2) affording both quantitative and qualitative comparisons between different network models. Shaffer, D.W., Collier, W., & Ruis, A.R. (2016) <doi:10.18608/jla.2016.33.3>.
LazyData: TRUE
Depends: R (>= 3.0.0)
License: GPL-3 | file LICENSE
LinkingTo: Rcpp, RcppArmadillo, RcppParallel, RcppEigen
Imports: data.table, Rcpp, R6, methods, foreach, stats, plotly, doParallel, parallel, RcppRoll, data.tree, scales, magrittr
Suggests: testthat
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2017-12-04 16:48:33 UTC; clmarquart
Repository: CRAN
Date/Publication: 2017-12-05 19:01:19 UTC

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New package polymapR with initial version 1.0.11
Package: polymapR
Type: Package
Title: Linkage Analysis in Outcrossing Polyploids
Version: 1.0.11
Date: 2017-12-01
Authors@R: c(person("Peter","Bourke", email = "pbourkey@gmail.com", role = c("aut","cre")), person("Geert","van Geest", role = "aut"))
Description: Creation of linkage maps in polyploid species from marker dosage scores of an F1 cross from two heterozygous parents. Currently works for autotriploid, autotetraploid and autohexaploid species, as well as segmental allotetraploids. Methods are described in a preprint manuscript of Bourke et al. (2017) <doi:10.1101/228817>.
Depends: R (>= 2.10)
License: GPL
Imports: igraph, doParallel, foreach, knitr, Rglpk, Matrix, combinat, RColorBrewer, reshape2, NMF, MDSMap
RoxygenNote: 6.0.1
Suggests: rmarkdown, Hmisc, LPmerge
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-12-05 15:34:16 UTC; bourk001
Author: Peter Bourke [aut, cre], Geert van Geest [aut]
Maintainer: Peter Bourke <pbourkey@gmail.com>
Repository: CRAN
Date/Publication: 2017-12-05 18:39:06 UTC

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New package Nonpareil with initial version 3.3
Package: Nonpareil
Title: Metagenome Coverage Estimation and Projections for 'Nonpareil'
Type: Package
Version: 3.3
Authors@R: c(person("Luis M.","Rodriguez-R",role=c("aut","cre"), email="lmrodriguezr@gmail.com"))
Author: Luis M. Rodriguez-R [aut, cre]
Maintainer: Luis M. Rodriguez-R <lmrodriguezr@gmail.com>
Description: Plot, process, and analyze NPO files produced by 'Nonpareil' <http://enve-omics.ce.gatech.edu/nonpareil>.
URL: http://enve-omics.ce.gatech.edu/nonpareil
Depends: R (>= 2.9)
Imports: methods
License: Artistic-2.0
LazyLoad: yes
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2017-12-05 18:11:05 UTC; lmr3
Repository: CRAN
Date/Publication: 2017-12-05 18:47:03 UTC

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New package lg with initial version 0.1.0
Package: lg
Title: Locally Gaussian Distributions: Estimation and Methods
Version: 0.1.0
Authors@R: person("Håkon", "Otneim", email = "hakon.otneim@nhh.no", role = c("aut", "cre"))
Description: An implementation of locally Gaussian distributions. It provides methods for implementing the locally Gaussian density estimator (LGDE) by Otneim and Tjøstheim (2017a) <doi:10.1007/s11222-016-9706-6>, as well as the corresponding estimator for conditional density functions by Otneim and Tjøstheim (2017b) <doi:10.1007/s11222-017-9732-z>.
Depends: R (>= 3.2.3)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat
Imports: mvtnorm, localgauss, logspline, ggplot2, ks
NeedsCompilation: no
Packaged: 2017-12-05 11:51:00 UTC; hakon
Author: Håkon Otneim [aut, cre]
Maintainer: Håkon Otneim <hakon.otneim@nhh.no>
Repository: CRAN
Date/Publication: 2017-12-05 18:12:07 UTC

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New package HMMEsolver with initial version 0.1.0
Package: HMMEsolver
Type: Package
Title: A Fast Solver for Henderson Mixed Model Equation via Row Operations
Version: 0.1.0
Authors@R: c(person("Jiwoong", "Kim", role="aut",email="jwboys26@gmail.com"), person("Kisung","You",role=c("aut","cre"),email="kyou@nd.edu"))
Description: Consider the linear mixed model with normal random effects. A typical method to solve Henderson's Mixed Model Equations (HMME) is recursive estimation of the fixed effects and random effects. We provide a fast, stable, and scalable solver to the HMME without computing matrix inverse. See Kim (2017) <arXiv:1710.09663> for more details.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: Rcpp, Rdpack
LinkingTo: Rcpp, RcppArmadillo
RdMacros: Rdpack
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-12-05 13:45:49 UTC; kisung
Author: Jiwoong Kim [aut], Kisung You [aut, cre]
Maintainer: Kisung You <kyou@nd.edu>
Repository: CRAN
Date/Publication: 2017-12-05 18:19:55 UTC

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New package deGradInfer with initial version 1.0.0
Package: deGradInfer
Title: Parameter Inference for Systems of Differential Equation
Version: 1.0.0
Authors@R: c(person("Benn", "Macdonald", email = "Benn.Macdonald@glasgow.ac.uk", role = c("aut")), person("Frank", "Dondelinger", email = "fdondelinger.work@gmail.com", role = c("aut", "cre")))
Description: Efficient Bayesian parameter inference for systems of ordinary differential equations. The inference is based on adaptive gradient matching (AGM, Dondelinger et al. 2013 <http://proceedings.mlr.press/v31/dondelinger13a.pdf>, Macdonald 2017 <http://theses.gla.ac.uk/7987/1/2017macdonaldphd.pdf>), which offers orders-of-magnitude improvements in computational efficiency over standard methods that require solving the differential equation system. Features of the package include flexible specification of custom ODE systems as R functions, support for missing variables, Bayesian inference via population MCMC.
Depends: R (>= 3.3.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: deSolve, gdata, gptk, graphics, stats
RoxygenNote: 6.0.1
Suggests: testthat, knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-12-05 12:47:44 UTC; dondelin
Author: Benn Macdonald [aut], Frank Dondelinger [aut, cre]
Maintainer: Frank Dondelinger <fdondelinger.work@gmail.com>
Repository: CRAN
Date/Publication: 2017-12-05 18:14:24 UTC

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Package x12 updated to version 1.9.0 with previous version 1.8.0 dated 2017-04-26

Title: Interface to 'X12-ARIMA'/'X13-ARIMA-SEATS' and Structure for Batch Processing of Seasonal Adjustment
Description: The 'X13-ARIMA-SEATS' <https://www.census.gov/srd/www/x13as/> methodology and software is a widely used software and developed by the US Census Bureau. It can be accessed from 'R' with this package and 'X13-ARIMA-SEATS' binaries are provided by the 'R' package 'x13binary'.
Author: Alexander Kowarik <alexander.kowarik@statistik.gv.at>, Angelika Meraner
Maintainer: Alexander Kowarik <alexander.kowarik@statistik.gv.at>

Diff between x12 versions 1.8.0 dated 2017-04-26 and 1.9.0 dated 2017-12-05

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Package qrnn updated to version 2.0 with previous version 1.1.3 dated 2015-07-23

Title: Quantile Regression Neural Network
Description: Fit quantile regression neural network models with optional left censoring, partial monotonicity constraints, generalized additive model constraints, and the ability to fit multiple non-crossing quantile functions following Cannon (2011) <doi:10.1016/j.cageo.2010.07.005> and Cannon (2017) <doi:10.17605/OSF.IO/WG7SN>.
Author: Alex J. Cannon
Maintainer: Alex J. Cannon <alex.cannon@canada.ca>

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Package olsrr updated to version 0.4.0 with previous version 0.3.0 dated 2017-08-31

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>

Diff between olsrr versions 0.3.0 dated 2017-08-31 and 0.4.0 dated 2017-12-05

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Package gambin updated to version 2.2.0 with previous version 2.1.1 dated 2017-07-25

Title: Fit the Gambin Model to Species Abundance Distributions
Description: Fits unimodal and multimodal gambin distributions to species-abundance distributions from ecological data. 'gambin' is short for 'gamma-binomial'. The main function is fit_abundances(), which estimates the 'alpha' parameter(s) of the gambin distribution using maximum likelihood. Functions are also provided to generate the gambin distribution and for calculating likelihood statistics.
Author: Thomas Matthews [aut, cre], Michael Krabbe Borregaard [aut], Karl Ugland [aut], Colin Gillespie [aut]
Maintainer: Thomas Matthews <txm676@gmail.com>

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Package emmeans updated to version 1.0 with previous version 0.9.1 dated 2017-11-05

Title: Estimated Marginal Means, aka Least-Squares Means
Description: Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and compact letter displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Author: Russell Lenth [aut, cre, cph], Jonathon Love [ctb], Maxime Herve [ctb]
Maintainer: Russell Lenth <russell-lenth@uiowa.edu>

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Package dlsem updated to version 2.0 with previous version 1.9 dated 2017-07-23

Title: Distributed-Lag Linear Structural Equation Models
Description: Inference functionalities for distributed-lag linear structural equation models (DLSEMs). DLSEMs were recently proposed by Magrini et al. (2016) <ISBN:978-88-619-7061-8> as an extension of linear structural causal models (Pearl, 2000) <ISBN:978-0-521-89560-6>, where each factor of the joint probability distribution is a distributed-lag linear regression with constrained lag shapes. Endpoint-constrained quadratic, quadratic decreasing and gamma lag shapes are available.
Author: Alessandro Magrini
Maintainer: Alessandro Magrini <magrini@disia.unifi.it>

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Package survrec (with last version 1.2-2) was removed from CRAN

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2012-03-26 1.2-2
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Package mixer (with last version 1.8) was removed from CRAN

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2015-01-15 1.8
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Package stringgaussnet (with last version 1.1) was removed from CRAN

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

2015-07-22 1.1
2015-06-16 1.0

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Package TestSurvRec (with last version 1.2.1) was removed from CRAN

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

2013-10-10 1.2.1
2013-08-29 1.01

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Package simone (with last version 1.0-3) was removed from CRAN

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

2016-01-22 1.0-3
2013-12-16 1.0-2

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Package icesTAF updated to version 1.4-1 with previous version 1.4-0 dated 2017-10-30

Title: Functions to Support the ICES Transparent Assessment Framework
Description: Functions to support the ICES Transparent Assessment Framework <http://taf.ices.dk> to organize data, methods, and results used in ICES assessments. ICES is an organization facilitating international collaboration in marine science.
Author: Arni Magnusson [aut, cre], Colin Millar [aut]
Maintainer: Arni Magnusson <arni.magnusson@ices.dk>

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Package R2BayesX updated to version 1.1-1 with previous version 1.1-0 dated 2016-11-17

Title: Estimate Structured Additive Regression Models with 'BayesX'
Description: An R interface to estimate structured additive regression (STAR) models with 'BayesX'.
Author: Nikolaus Umlauf [aut, cre], Thomas Kneib [aut], Stefan Lang [aut], Achim Zeileis [aut] (0000-0003-0918-3766)
Maintainer: Nikolaus Umlauf <Nikolaus.Umlauf@uibk.ac.at>

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Package msm updated to version 1.6.5 with previous version 1.6.4 dated 2016-10-04

Title: Multi-State Markov and Hidden Markov Models in Continuous Time
Description: Functions for fitting continuous-time Markov and hidden Markov multi-state models to longitudinal data. Designed for processes observed at arbitrary times in continuous time (panel data) but some other observation schemes are supported. Both Markov transition rates and the hidden Markov output process can be modelled in terms of covariates, which may be constant or piecewise-constant in time.
Author: Christopher Jackson <chris.jackson@mrc-bsu.cam.ac.uk>
Maintainer: Christopher Jackson <chris.jackson@mrc-bsu.cam.ac.uk>

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Package miic updated to version 1.0.1 with previous version 1.0 dated 2017-11-22

Title: Learning Causal or Non-Causal Graphical Models Using Information Theory
Description: We report an information-theoretic method which learns a large class of causal or non-causal graphical models from purely observational data, while including the effects of unobserved latent variables, commonly found in many datasets. Starting from a complete graph, the method iteratively removes dispensable edges, by uncovering significant information contributions from indirect paths, and assesses edge-specific confidences from randomization of available data. The remaining edges are then oriented based on the signature of causality in observational data. This approach can be applied on a wide range of datasets and provide new biological insights on regulatory networks from single cell expression data, genomic alterations during tumor development and co-evolving residues in protein structures. For more information you can refer to: Verny et al. Plos Comput Biol. (2017) <doi:10.1371/journal.pcbi.1005662>.
Author: Nadir Sella [aut, cre], Louis Verny [aut], Severine Affeldt [aut], Hervé Isambert [aut]
Maintainer: Nadir Sella <nadir.sella@curie.fr>

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Package MetaSubtract updated to version 1.3 with previous version 1.2 dated 2017-10-13

Title: Subtracting Summary Statistics of One or more Cohorts from Meta-GWAS Results
Description: If results from a meta-GWAS are used for validation in one of the cohorts that was included in the meta-analysis, this will yield biased (i.e. too optimistic) results. The validation cohort needs to be independent from the meta-GWAS results. MetaSubtract will subtract the results of the respective cohort from the meta-GWAS results analytically without having to redo the meta-GWAS analysis using the leave-one-out methodology. It can handle different meta-analyses methods and takes into account if single or double genomic control correction was applied to the original meta-analysis. It can be used for whole GWAS, but also for a limited set of SNPs or other genetic markers.
Author: Ilja M. Nolte
Maintainer: Ilja M. Nolte <i.m.nolte@umcg.nl>

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Package MCMCpack updated to version 1.4-1 with previous version 1.4-0 dated 2017-06-05

Title: Markov Chain Monte Carlo (MCMC) Package
Description: Contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library Version 1.0.3. All models return coda mcmc objects that can then be summarized using the coda package. Some useful utility functions such as density functions, pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization are provided.
Author: Andrew D. Martin [aut], Kevin M. Quinn [aut], Jong Hee Park [aut,cre], Ghislain Vieilledent [ctb], Michael Malecki[ctb], Matthew Blackwell [ctb]
Maintainer: Jong Hee Park <jongheepark@snu.ac.kr>

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Package ggimage updated to version 0.1.0 with previous version 0.0.7 dated 2017-11-01

Title: Use Image in 'ggplot2'
Description: Supports image files and graphic objects to be visualized in 'ggplot2' graphic system.
Author: Guangchuang Yu [aut, cre] (0000-0002-6485-8781)
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package edeaR updated to version 0.7.2 with previous version 0.7.1 dated 2017-09-07

Title: Exploratory and Descriptive Event-Based Data Analysis
Description: Exploratory and descriptive analysis of event based data. Provides methods for describing and selecting process data, and for preparing event log data for process mining. Builds on the S3-class for event logs implemented in the package 'bupaR'.
Author: Gert Janssenswillen [aut, cre], Marijke Swennen [ctb]
Maintainer: Gert Janssenswillen <gert.janssenswillen@uhasselt.be>

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Package antaresViz updated to version 0.11.2 with previous version 0.11 dated 2017-07-17

Title: Antares Visualizations
Description: Visualize results generated by Antares, a powerful software developed by RTE to simulate and study electric power systems (more information about Antares here: <https://antares.rte-france.com>). This package provides functions that create interactive charts to help Antares users visually explore the results of their simulations.
Author: Jalal-Edine ZAWAM [aut, cre], Francois Guillem [aut], Benoit Thieurmel [aut], Titouan Robert [aut], RTE [cph]
Maintainer: Jalal-Edine ZAWAM <jalal-edine.zawam@rte-france.com>

Diff between antaresViz versions 0.11 dated 2017-07-17 and 0.11.2 dated 2017-12-05

 DESCRIPTION                                                           |   20 
 MD5                                                                   |   72 
 NEWS                                                                  |    4 
 R/catColorPal.R                                                       |   66 
 R/get_data_for_comp.R                                                 |   92 
 R/leafletDragPoints.R                                                 |  104 
 R/map.R                                                               |  604 ++--
 R/map_deps.R                                                          |   60 
 R/map_helpers.R                                                       |  648 ++--
 R/map_layout.R                                                        |  698 ++---
 R/map_legends.R                                                       |  322 +-
 R/map_options.R                                                       |  216 -
 R/map_plugins.R                                                       |  182 -
 R/plot.R                                                              |  676 ++--
 R/plot_barplot.R                                                      |  118 
 R/plot_heatmap.R                                                      |  266 -
 R/plot_stats.R                                                        |  298 +-
 R/plot_ts.R                                                           |  188 -
 R/prettyNumbers.R                                                     |   68 
 R/savePlotAsPng.R                                                     |   68 
 R/setInteractivity.R                                                  |   54 
 R/stack.R                                                             |  238 -
 R/stack_aliases.R                                                     |  150 -
 R/stack_exchanges.R                                                   |  334 +-
 R/stack_prod.R                                                        |  674 ++--
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 tests/testthat.R                                                      |    8 
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Package bigsnpr (with last version 0.2.2) was removed from CRAN

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

2017-12-05 0.2.2

Permanent link
Package sdols updated to version 1.4 with previous version 1.3 dated 2017-12-01

Title: Summarizing Distributions of Latent Structures
Description: Summaries of distributions on clusterings and feature allocations are provided. Specifically, point estimates are obtained by the sequentially-allocated latent structure optimization (SALSO) algorithm to minimize squared error loss, absolute error loss, Binder loss, or the lower bound of the variation of information loss. Clustering uncertainty can be assessed with the confidence calculations and the associated plot.
Author: David B. Dahl [aut, cre], Peter Müller [aut]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

Diff between sdols versions 1.3 dated 2017-12-01 and 1.4 dated 2017-12-05

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Package hexSticker updated to version 0.4.2 with previous version 0.4.1 dated 2017-06-19

Title: Create Hexagon Sticker in R
Description: Helper functions for creating reproducible hexagon sticker purely in R.
Author: Guangchuang Yu [aut, cre], Laurent Gatto [ctb], Johannes Rainer [ctb], Sebastian Gibb [ctb]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between hexSticker versions 0.4.1 dated 2017-06-19 and 0.4.2 dated 2017-12-05

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Permanent link

Package eventdataR updated to version 0.1.2 with previous version 0.1.1 dated 2017-09-03

Title: Event Data Repository
Description: Event dataset repository including both real-life and artificial event logs. They can be used in combination with functionalities provided by the 'bupaR' packages 'edeaR', 'processmapR', etc.
Author: Gert Janssenswillen [aut, cre]
Maintainer: Gert Janssenswillen <gert.janssenswillen@uhasselt.be>

Diff between eventdataR versions 0.1.1 dated 2017-09-03 and 0.1.2 dated 2017-12-05

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Package DPpackage updated to version 1.1-7.1 with previous version 1.1-7 dated 2017-09-14

Title: Bayesian Nonparametric Modeling in R
Description: Functions to perform inference via simulation from the posterior distributions for Bayesian nonparametric and semiparametric models. Although the name of the package was motivated by the Dirichlet Process prior, the package considers and will consider other priors on functional spaces. So far, DPpackage includes models considering Dirichlet Processes, Dependent Dirichlet Processes, Dependent Poisson- Dirichlet Processes, Hierarchical Dirichlet Processes, Polya Trees, Linear Dependent Tailfree Processes, Mixtures of Triangular distributions, Random Bernstein polynomials priors and Dependent Bernstein Polynomials. The package also includes models considering Penalized B-Splines. Includes semiparametric models for marginal and conditional density estimation, ROC curve analysis, interval censored data, binary regression models, generalized linear mixed models, IRT type models, and generalized additive models. Also contains functions to compute Pseudo-Bayes factors for model comparison, and to elicitate the precision parameter of the Dirichlet Process. To maximize computational efficiency, the actual sampling for each model is done in compiled FORTRAN. The functions return objects which can be subsequently analyzed with functions provided in the 'coda' package.
Author: Alejandro Jara [aut, cre], Timothy Hanson [ctb], Fernando Quintana [ctb], Peter Mueller [ctb], Gary Rosner [ctb]
Maintainer: ORPHANED

Diff between DPpackage versions 1.1-7 dated 2017-09-14 and 1.1-7.1 dated 2017-12-05

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 src/ToolsDistributions.f |   92 ++++----
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 src/ToolsIntegrate.f     |    6 
 src/ToolsLDTFP.f         |  390 ++++++++++++++++++------------------
 src/ToolsMatrix.f        |   48 ++--
 src/ToolsPT.f            |  502 +++++++++++++++++++++++------------------------
 src/ToolsPTsampler.f     |   48 ++--
 src/ToolsPolynomials.f   |   14 -
 src/ToolsRSBA.f          |  146 ++++++-------
 src/ToolsRnumbers.f      |  151 +++++++-------
 src/ToolsSB.f            |   34 +--
 src/ToolsSlice.f         |   66 +++---
 src/ToolsStat.f          |    6 
 src/ToolsSweep.f         |    8 
 src/ToolsTDP.f           |   22 +-
 95 files changed, 4327 insertions(+), 4289 deletions(-)

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Package ordinalNet updated to version 2.4 with previous version 2.3 dated 2017-10-03

Title: Penalized Ordinal Regression
Description: Fits ordinal regression models with elastic net penalty. Supported model families include cumulative probability, stopping ratio, continuation ratio, and adjacent category. These families are a subset of vector glm's which belong to a model class we call the elementwise link multinomial-ordinal (ELMO) class. Each family in this class links a vector of covariates to a vector of class probabilities. Each of these families has a parallel form, which is appropriate for ordinal response data, as well as a nonparallel form that is appropriate for an unordered categorical response, or as a more flexible model for ordinal data. The parallel model has a single set of coefficients, whereas the nonparallel model has a set of coefficients for each response category except the baseline category. It is also possible to fit a model with both parallel and nonparallel terms, which we call the semi-parallel model. The semi-parallel model has the flexibility of the nonparallel model, but the elastic net penalty shrinks it toward the parallel model. For details, refer to Wurm, Hanlon, and Rathouz (2017) <arXiv:1706.05003>.
Author: Michael Wurm [aut, cre], Paul Rathouz [aut], Bret Hanlon [aut]
Maintainer: Michael Wurm <wurm@uwalumni.com>

Diff between ordinalNet versions 2.3 dated 2017-10-03 and 2.4 dated 2017-12-05

 DESCRIPTION |   10 +++++-----
 MD5         |    2 +-
 2 files changed, 6 insertions(+), 6 deletions(-)

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New package scatr with initial version 1.0.1
Package: scatr
Type: Package
Title: Create Scatter Plots with Marginal Density or Box Plots
Version: 1.0.1
Date: 2017-12-01
Author: Ravi Selker
Maintainer: Ravi Selker <selker.ravi@gmail.com>
Description: Allows you to make clean, good-looking scatter plots with the option to easily add marginal density or box plots on the axes. It is also available as a module for 'jamovi' (see <https://www.jamovi.org> for more information). 'Scatr' is based on the 'cowplot' package by Claus O. Wilke and the 'ggplot2' package by Hadley Wickham.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2)
Imports: jmvcore (>= 0.8.0), R6, ggplot2, cowplot, ggstance, ggridges
RoxygenNote: 6.0.1
URL: https://github.com/raviselker/scatr
BugReports: https://github.com/raviselker/scatr/issues
NeedsCompilation: no
Packaged: 2017-12-04 13:52:49 UTC; ravi
Repository: CRAN
Date/Publication: 2017-12-05 09:47:24 UTC

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New package CsChange with initial version 0.1.0
Package: CsChange
Type: Package
Title: Testing for Change in C-Statistic
Version: 0.1.0
Author: Zhicheng Du, Yuantao Hao
Maintainer: Zhicheng Du<dgdzc@hotmail.com>
Description: Calculate the confidence interval and p value for change in C-statistic. The adjusted C-statistic is calculated by using formula as "Somers' Dxy rank correlation"/2+0.5. The confidence interval was calculated by using the bootstrap method. The p value was calculated by using the Z testing method. Please refer to the article of Peter Ganz et al. (2016) <doi:10.1001/jama.2016.5951>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: rms, survival, boot, stats, Hmisc
NeedsCompilation: no
Packaged: 2017-12-04 08:32:38 UTC; dgdzc
Repository: CRAN
Date/Publication: 2017-12-05 09:39:05 UTC

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New package bigsnpr with initial version 0.2.2
Encoding: UTF-8
Package: bigsnpr
Type: Package
Title: Analysis of Massive SNP Arrays
Version: 0.2.2
Date: 2017-12-02
Authors@R: c( person("Florian", "Privé", email = "florian.prive.21@gmail.com", role = c("aut", "cre")), person("Michael", "Blum", email = "michael.blum@univ-grenoble-alpes.fr", role = "ths"), person("Hugues", "Aschard", email = "hugues.aschard@pasteur.fr", role = "ths"))
Description: Easy-to-use, efficient, flexible and scalable tools for the analysis of massive SNP arrays. Preprint: Privé et al. (2017) <doi:10.1101/190926>.
License: GPL-3
LazyData: TRUE
ByteCompile: TRUE
Depends: R (>= 3.3.2), bigstatsr (>= 0.2.3)
Imports: data.table, doParallel, foreach, ggplot2, gsubfn, Matrix, parallel, Rcpp, robustbase, stats, xgboost
LinkingTo: BH, bigstatsr, Rcpp, RcppArmadillo
Suggests: spelling, covr, dplyr, gaston, Hmisc, magrittr, pcadapt, testthat
RoxygenNote: 6.0.1
URL: https://privefl.github.io/bigsnpr
BugReports: https://github.com/privefl/bigsnpr/issues
NeedsCompilation: yes
Packaged: 2017-12-04 17:09:27 UTC; Florian
Author: Florian Privé [aut, cre], Michael Blum [ths], Hugues Aschard [ths]
Maintainer: Florian Privé <florian.prive.21@gmail.com>
Repository: CRAN
Date/Publication: 2017-12-05 09:54:23 UTC

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Package NHMSAR updated to version 1.7 with previous version 1.6 dated 2017-08-31

Title: Non-Homogeneous Markov Switching Autoregressive Models
Description: Calibration, simulation, validation of (non-)homogeneous Markov switching autoregressive models with Gaussian or von Mises innovations. Penalization methods are implemented for Markov Switching Vector Autoregressive Models of order 1 only. Most functions of the package handle missing values.
Author: Valerie Monbet
Maintainer: Valerie Monbet <valerie.monbet@gmail.com>

Diff between NHMSAR versions 1.6 dated 2017-08-31 and 1.7 dated 2017-12-05

 DESCRIPTION          |    8 ++++----
 MD5                  |    6 +++---
 R/Mstep.nh.MSAR.VM.R |   12 ++++++------
 R/cross.cor.MSAR.R   |    4 ++--
 4 files changed, 15 insertions(+), 15 deletions(-)

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Package asnipe updated to version 1.1.6 with previous version 1.1.5 dated 2017-11-15

Title: Animal Social Network Inference and Permutations for Ecologists
Description: Implements several tools that are used in animal social network analysis. In particular, this package provides the tools to infer groups and generate networks from observation data, perform permutation tests on the data, calculate lagged association rates, and performed multiple regression analysis on social network data.
Author: Damien R. Farine <dfarine@orn.mpg.de>
Maintainer: Damien R. Farine <dfarine@orn.mpg.de>

Diff between asnipe versions 1.1.5 dated 2017-11-15 and 1.1.6 dated 2017-12-05

 DESCRIPTION             |    8 ++++----
 MD5                     |   10 +++++-----
 R/network_permutation.R |   30 ++++++++++++++++++++++++++----
 R/network_swap.R        |   34 +++++++++++++++++++++++++++++-----
 man/asnipe-package.Rd   |    4 ++--
 man/network_swap.Rd     |    9 ++++++---
 6 files changed, 72 insertions(+), 23 deletions(-)

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