Thu, 24 Sep 2020

Package semantic.dashboard (with last version 0.1.5) was removed from CRAN

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

2020-04-07 0.1.5
2018-04-23 0.1.1

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

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

2020-03-16 1.0

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Package ChemometricsWithR (with last version 0.1.13) was removed from CRAN

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

2019-01-07 0.1.13
2017-09-01 0.1.11
2017-08-21 0.1.10
2015-09-04 0.1.9
2014-08-04 0.1.8
2012-10-12 0.1.7
2012-01-04 0.1.5
2011-02-17 0.1.3

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Package sjPlot updated to version 2.8.5 with previous version 2.8.4 dated 2020-05-24

Title: Data Visualization for Statistics in Social Science
Description: Collection of plotting and table output functions for data visualization. Results of various statistical analyses (that are commonly used in social sciences) can be visualized using this package, including simple and cross tabulated frequencies, histograms, box plots, (generalized) linear models, mixed effects models, principal component analysis and correlation matrices, cluster analyses, scatter plots, stacked scales, effects plots of regression models (including interaction terms) and much more. This package supports labelled data.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Alexander Bartel [ctb] (<https://orcid.org/0000-0002-1280-6138>), Carsten Schwemmer [ctb], Chuck Powell [ctb] (<https://orcid.org/0000-0002-3606-2188>), Amir Djalovski [ctb], Johannes Titz [ctb] (<https://orcid.org/0000-0002-1102-5719>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package psfmi updated to version 0.5.0 with previous version 0.2.0 dated 2020-02-03

Title: Prediction Model Selection and Performance Evaluation in Multiple Imputed Datasets
Description: Pooling, backward and forward selection of logistic and Cox regression models in multiply imputed datasets. Backward and forward selection can be done from the pooled model using Rubin's Rules (RR), the D1, D2, D3 and the median p-values method. This is also possible for Mixed models. The models can contain continuous, dichotomous, categorical and restricted cubic spline predictors and interaction terms between all these type of predictors. The stability of the models can be evaluated using bootstrapping and cluster bootstrapping. The package further contains functions to pool the model performance as ROC/AUC, R-squares, scaled Brier score and calibration plots for logistic regression models. Internal validation can be done with cross-validation or bootstrapping. The adjusted intercept after shrinkage of pooled regression coefficients can be obtained. Backward and forward selection as part of internal validation is possible. Also a function to externally validate logistic prediction models in multiple imputed datasets is available. Eekhout (2017) <doi:10.1186/s12874-017-0404-7>. Wiel (2009) <doi:10.1093/biostatistics/kxp011>. Marshall (2009) <doi:10.1186/1471-2288-9-57>.
Author: Martijn Heymans [cre, aut] (<https://orcid.org/0000-0002-3889-0921>), Iris Eekhout [ctb]
Maintainer: Martijn Heymans <mw.heymans@amsterdamumc.nl>

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Package import updated to version 1.2.0 with previous version 1.1.0 dated 2015-06-21

Title: An Import Mechanism for R
Description: Alternative mechanism for importing objects from packages and R modules. The syntax allows for importing multiple objects with a single command in an expressive way. The import package bridges some of the gap between using library (or require) and direct (single-object) imports. Furthermore the imported objects are not placed in the current environment.
Author: Stefan Milton Bache [aut], Magnus Thor Torfason [aut, cre]
Maintainer: Magnus Thor Torfason <m@zulutime.net>

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Package iml updated to version 0.10.1 with previous version 0.10.0 dated 2020-03-26

Title: Interpretable Machine Learning
Description: Interpretability methods to analyze the behavior and predictions of any machine learning model. Implemented methods are: Feature importance described by Fisher et al. (2018) <arXiv:1801.01489>, accumulated local effects plots described by Apley (2018) <arXiv:1612.08468>, partial dependence plots described by Friedman (2001) <www.jstor.org/stable/2699986>, individual conditional expectation ('ice') plots described by Goldstein et al. (2013) <doi:10.1080/10618600.2014.907095>, local models (variant of 'lime') described by Ribeiro et. al (2016) <arXiv:1602.04938>, the Shapley Value described by Strumbelj et. al (2014) <doi:10.1007/s10115-013-0679-x>, feature interactions described by Friedman et. al <doi:10.1214/07-AOAS148> and tree surrogate models.
Author: Christoph Molnar [aut, cre], Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>)
Maintainer: Christoph Molnar <christoph.molnar@gmail.com>

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Package gaston updated to version 1.5.7 with previous version 1.5.6 dated 2020-02-26

Title: Genetic Data Handling (QC, GRM, LD, PCA) & Linear Mixed Models
Description: Manipulation of genetic data (SNPs). Computation of GRM and dominance matrix, LD, heritability with efficient algorithms for linear mixed model (AIREML). Dandine et al <doi:10.1159/000488519>.
Author: Hervé Perdry [cre, aut, cph], Claire Dandine-Roulland [aut, cph], Deepak Bandyopadhyay [cph] (C++ gzstream class), Lutz Kettner [cph] (C++ gzstream class)
Maintainer: Hervé Perdry <herve.perdry@u-psud.fr>

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Package prioritylasso (with last version 0.2.4) was removed from CRAN

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

2020-09-07 0.2.4
2019-12-17 0.2.3
2019-06-05 0.2.2
2017-09-25 0.2.1
2017-07-17 0.2.0
2017-03-16 0.1.0

Permanent link
Package norris (with last version 0.1.1) was removed from CRAN

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

2019-01-18 0.1.1
2018-06-12 0.1.0

Permanent link
Package st updated to version 1.2.6 with previous version 1.2.5 dated 2015-07-08

Title: Shrinkage t Statistic and Correlation-Adjusted t-Score
Description: Implements the "shrinkage t" statistic introduced in Opgen-Rhein and Strimmer (2007) <DOI:10.2202/1544-6115.1252> and a shrinkage estimate of the "correlation-adjusted t-score" (CAT score) described in Zuber and Strimmer (2009) <DOI:10.1093/bioinformatics/btp460>. It also offers a convenient interface to a number of other regularized t-statistics commonly employed in high-dimensional case-control studies.
Author: Rainer Opgen-Rhein, Verena Zuber, and Korbinian Strimmer.
Maintainer: Korbinian Strimmer <strimmerlab@gmail.com>

Diff between st versions 1.2.5 dated 2015-07-08 and 1.2.6 dated 2020-09-24

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Package rprime updated to version 0.1.2 with previous version 0.1.0 dated 2015-05-29

Title: Functions for Working with 'Eprime' Text Files
Description: 'Eprime' is a set of programs for administering psychological experiments by computer. This package provides functions for loading, parsing, filtering and exporting data in the text files produced by 'Eprime' experiments.
Author: Tristan Mahr [aut, cre] (<https://orcid.org/0000-0002-8890-5116>)
Maintainer: Tristan Mahr <tristan.mahr@wisc.edu>

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Package orders updated to version 0.1.4 with previous version 0.1.3 dated 2019-05-16

Title: Sampling from Order Statistics of New Families of Distributions
Description: Set of tools to generate samples of order statistics and others quantities of interest from new families of distributions. The main references for this package are: Gentle, J. (2009), Computational Statistics, Springer-Verlag; Naradajah, S. and Rocha, R. (2016), <DOI:10.18637/jss.v069.i10> and Stasinopoulos, M. and Rigby, R. (2015), <DOI:10.1111/j.1467-9876.2005.00510.x>. The families of distributions are: Marshall Olkin G distributions, exponentiated G distributions, beta G distributions, gamma G distributions, Kumaraswamy G distributions, generalized beta G distributions, beta extended G distributions, gamma G distributions, gamma uniform G distributions, beta exponential G distributions, Weibull G distributions, log gamma G I distributions, log gamma G II distributions, exponentiated generalized G distributions, exponentiated Kumaraswamy G distributions, geometric exponential Poisson G distributions, truncated-exponential skew-symmetric G distributions, modified beta G distributions, and exponentiated exponential Poisson G distributions, Poisson-inverse gaussian distribution, Skew normal type 1 distributions, Skew student t distribution, Sinh-Arcsinh distribution, Sichel distribution and Zero inflated Poisson.
Author: Carlos Alberto Cardozo Delgado
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>

Diff between orders versions 0.1.3 dated 2019-05-16 and 0.1.4 dated 2020-09-24

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Package SubtypeDrug updated to version 0.1.2 with previous version 0.1.1 dated 2020-06-26

Title: Prioritization of Candidate Cancer Subtype Specific Drugs
Description: A systematic biology tool was developed to prioritize cancer subtype-specific drugs by integrating genetic perturbation, drug action, biological pathway, and cancer subtype. The capabilities of this tool include inferring patient-specific subpathway activity profiles in the context of gene expression profiles with subtype labels, calculating differentially expressed subpathways based on cultured human cells treated with drugs in the 'cMap' (connectivity map) database, prioritizing cancer subtype specific drugs according to drug-disease reverse association score based on subpathway, and visualization of results (Castelo (2013) <doi:10.1186/1471-2105-14-7>; Han et al (2019) <doi:10.1093/bioinformatics/btz894>; Lamb and Justin (2006) <DOI:10.1126/science.1132939>).
Author: Xudong Han, Junwei Han, Chonghui Liu
Maintainer: Junwei Han <hanjunwei1981@163.com>

Diff between SubtypeDrug versions 0.1.1 dated 2020-06-26 and 0.1.2 dated 2020-09-24

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New package uwo4419 with initial version 0.3.0
Package: uwo4419
Type: Package
Title: UWO POLSCI 4419/9715
Version: 0.3.0
Authors@R: c(person("Dave", "Armstrong", role=c("aut", "cre"), email="dave@quantoid.net"))
Description: Supports the course Introduction to Methodology (POLSCI 4419/9715) at the University of Western Ontario.
Depends: R (>= 3.5.0)
Imports: DescTools, RColorBrewer, gmodels, haven, psych, stats, ggplot2, tibble, tidyr, dplyr, magrittr, rio
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2020-09-18 17:33:49 UTC; parallels
Author: Dave Armstrong [aut, cre]
Maintainer: Dave Armstrong <dave@quantoid.net>
Repository: CRAN
Date/Publication: 2020-09-24 09:10:02 UTC

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Package ScriptMapR updated to version 0.0.3 with previous version 0.0.2 dated 2020-09-21

Title: R Script Visualization in Cytoscape
Description: Displays the content of a R script into the 'Cytoscape' network-visualization app <https://cytoscape.org/>.
Author: Raphael Bonnet [aut, cre], Marion Guernoté [ctb], Terry Gouin [ctb], Maxime Laurens [ctb], Thibault Meekel [ctb], Jean-François Peyron[aut,ths]
Maintainer: Raphaël Bonnet <raphael.bonnet@univ-cotedazur.fr>

Diff between ScriptMapR versions 0.0.2 dated 2020-09-21 and 0.0.3 dated 2020-09-24

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Package roundhouse updated to version 0.0.2 with previous version 0.0.1 dated 2018-09-16

Title: Random Chuck Norris Facts
Description: R functions for generating and/or displaying random Chuck Norris facts. Based on data from the 'Internet Chuck Norris database' ('ICNDb').
Author: Brandon Greenwell [aut, cre]
Maintainer: Brandon Greenwell <greenwell.brandon@gmail.com>

Diff between roundhouse versions 0.0.1 dated 2018-09-16 and 0.0.2 dated 2020-09-24

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New package panelr with initial version 0.7.4
Package: panelr
Title: Regression Models and Utilities for Repeated Measures and Panel Data
Version: 0.7.4
Authors@R: person("Jacob A.", "Long", email = "jacob.long@sc.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1582-6214"))
Description: Provides an object type and associated tools for storing and wrangling panel data. Implements several methods for creating regression models that take advantage of the unique aspects of panel data. Among other capabilities, automates the "within-between" (also known as "between-within" and "hybrid") panel regression specification that combines the desirable aspects of both fixed effects and random effects econometric models and fits them as multilevel models (Allison, 2009 <doi:10.4135/9781412993869.d33>; Bell & Jones, 2015 <doi:10.1017/psrm.2014.7>). These models can also be estimated via generalized estimating equations (GEE; McNeish, 2019 <doi:10.1080/00273171.2019.1602504>) and Bayesian estimation is (optionally) supported via 'Stan'. Supports estimation of asymmetric effects models via first differences (Allison, 2019 <doi:10.1177/2378023119826441>) as well as a generalized linear model extension thereof using GEE.
URL: https://panelr.jacob-long.com
BugReports: https://github.com/jacob-long/panelr
Depends: R (>= 3.4.0), lme4
Imports: crayon, dplyr, Formula, ggplot2, jtools (>= 2.0.1), lmerTest, magrittr, methods, purrr, rlang (>= 0.3.0), stringr, tibble (>= 2.0.0)
Suggests: brms, broom.mixed, car, clubSandwich, geepack, generics, nlme, plm, sandwich, skimr, tidyr (>= 0.8.3), testthat, covr, knitr, rmarkdown
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-24 00:19:39 UTC; jlong
Author: Jacob A. Long [aut, cre] (<https://orcid.org/0000-0002-1582-6214>)
Maintainer: Jacob A. Long <jacob.long@sc.edu>
Repository: CRAN
Date/Publication: 2020-09-24 09:10:08 UTC

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Package lorentz updated to version 1.0-5 with previous version 1.0-2 dated 2019-03-21

Title: The Lorentz Transform in Relativistic Physics
Description: The Lorentz transform in special relativity; also the gyrogroup structure of three-velocities. Includes active and passive transforms and the ability to use units in which the speed of light is not one. For general relativity, see the 'schwarzschild' package.
Author: Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>)
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

Diff between lorentz versions 1.0-2 dated 2019-03-21 and 1.0-5 dated 2020-09-24

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New package metamisc with initial version 0.2.3
Package: metamisc
Type: Package
Title: Meta-Analysis of Diagnosis and Prognosis Research Studies
Version: 0.2.3
Date: 2020-09-23
Authors@R: c(person(given = "Thomas", family = "Debray", role = c("aut", "cre"), email = "thomas.debray@gmail.com", comment="https://orcid.org/0000-0002-1790-2719"), person(given = "Valentijn", family = "de Jong", role = "aut", email="Valentijn.M.T.de.Jong@gmail.com", comment="https://orcid.org/0000-0001-9921-3468"))
Description: Facilitate meta-analysis of diagnosis and prognosis research studies. It includes functions to summarize multiple estimates of prediction model discrimination and calibration performance, as described by Debray et al. (2019) <doi:10.1177/0962280218785504>. It also includes functions to evaluate funnel plot asymmetry, as described by Debray et al. (2018) <doi:10.1002/jrsm.1266>. Finally, the package provides functions for developing multivariable prediction models from datasets with clustering.
Imports: metafor (>= 2.0.0), mvtnorm, lme4, plyr, methods, pROC, ggplot2
Depends: R (>= 3.5.0), stats, graphics
Suggests: runjags, rjags, logistf (>= 1.23), testthat (>= 1.0.2)
License: GPL-3
URL: https://r-forge.r-project.org/projects/metamisc/
RoxygenNote: 7.1.1
Author: Thomas Debray [aut, cre] (<https://orcid.org/0000-0002-1790-2719>), Valentijn de Jong [aut] (<https://orcid.org/0000-0001-9921-3468>)
Maintainer: Thomas Debray <thomas.debray@gmail.com>
Repository: CRAN
Repository/R-Forge/Project: metamisc
Repository/R-Forge/Revision: 567
Repository/R-Forge/DateTimeStamp: 2020-09-23 08:55:00
Date/Publication: 2020-09-24 09:20:02 UTC
NeedsCompilation: no
Packaged: 2020-09-23 09:08:09 UTC; rforge

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Package interval updated to version 1.1-0.7 with previous version 1.1-0.1 dated 2014-01-22

Title: Weighted Logrank Tests and NPMLE for Interval Censored Data
Description: Functions to fit nonparametric survival curves, plot them, and perform logrank or Wilcoxon type tests.
Author: Michael P. Fay
Maintainer: Michael P. Fay <mfay@niaid.nih.gov>

Diff between interval versions 1.1-0.1 dated 2014-01-22 and 1.1-0.7 dated 2020-09-24

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Package gSeg updated to version 1.0 with previous version 0.7 dated 2020-04-12

Title: Graph-Based Change-Point Detection (g-Segmentation)
Description: Using an approach based on similarity graph to estimate change-point(s) and the corresponding p-values. Can be applied to any type of data (high-dimensional, non-Euclidean, etc.) as long as a reasonable similarity measure is available.
Author: Hao Chen, Nancy R. Zhang, Lynna Chu, and Hoseung Song
Maintainer: Hao Chen <hxchen@ucdavis.edu>

Diff between gSeg versions 0.7 dated 2020-04-12 and 1.0 dated 2020-09-24

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New package akmbiclust with initial version 0.1.0
Package: akmbiclust
Title: Alternating K-Means Biclustering
Version: 0.1.0
Authors@R: c( person("Zichao", "Li", role = c("aut", "cre"), email = "lizichao@live.unc.edu"), person("Nicolas", "Fraiman", role = "aut", email = "fraiman@email.unc.edu"))
Description: Implements the alternating k-means biclustering algorithm in Fraiman and Li (2020) <arXiv:2009.04550>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-09-18 17:38:42 UTC; lizichao
Author: Zichao Li [aut, cre], Nicolas Fraiman [aut]
Maintainer: Zichao Li <lizichao@live.unc.edu>
Repository: CRAN
Date/Publication: 2020-09-24 09:10:15 UTC

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Package universals updated to version 0.0.4 with previous version 0.0.3 dated 2020-07-08

Title: S3 Generics for Bayesian Analyses
Description: Provides S3 generic methods and some default implementations for Bayesian analyses that generate Markov Chain Monte Carlo (MCMC) samples. The purpose of 'universals' is to reduce package dependencies and conflicts. The 'nlist' package implements many of the methods for its 'nlist' class.
Author: Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>), Kirill Müller [ctb] (<https://orcid.org/0000-0002-1416-3412>), Poisson Consulting [cph, fnd]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>

Diff between universals versions 0.0.3 dated 2020-07-08 and 0.0.4 dated 2020-09-24

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Package tsapp updated to version 1.0.2 with previous version 1.0.1 dated 2020-09-21

Title: Time Series, Analysis and Application
Description: Accompanies the book Rainer Schlittgen and Cristina Sattarhoff (2020) <https://www.degruyter.com/view/title/575978> "Angewandte Zeitreihenanalyse mit R, 4. Auflage" . The package contains the time series and functions used therein. It was developed over many years teaching courses about time series analysis.
Author: Rainer Schlittgen
Maintainer: Rainer Schlittgen <R.Schlittgen@t-online.de>

Diff between tsapp versions 1.0.1 dated 2020-09-21 and 1.0.2 dated 2020-09-24

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New package topsa with initial version 0.1.0
Package: topsa
Type: Package
Title: Topological Sensitivity Analysis
Version: 0.1.0
Authors@R: c( person(given = "Maikol", family = "Solís", email = "maikol.solis@ucr.ac.cr", role = c("aut", "cre")), person(given = "Alberto", family = "Hernández", email = "albertojose.hernandez@ucr.ac.cr", role = c("ctb")), person(given = "Ronald A.", family = "Zuñiga-Rojas", email = "ronald.zunigarojas@ucr.ac.cr", role = c("ctb")), person(given = "Carlos", family = "Pasquier", email = "carlos.pasquier@ucr.ac.cr", role = c("ctb")) )
Maintainer: Maikol Solís <maikol.solis@ucr.ac.cr>
Description: Estimate geometric sensitivity indices reconstructing the embedding manifold of the data. The reconstruction is done via a Vietoris Rips with a fixed radius. With the homology of order 2 we estimate symmetric reflections of the those manifold to determine a sensitivity index on of the input model. Detailed information of the methods can be found in <https://www.dropbox.com/s/0kcrjhhkl7899n1/article-symmetric-reflection.pdf> (WIP preprint).
License: MIT + file LICENSE
URL: https://github.com/maikol-solis/topsa
BugReports: https://github.com/maikol-solis/topsa/issues
Encoding: UTF-8
LazyData: true
Imports: ggplot2, scales, sf, TDA, parallel, methods
RoxygenNote: 7.1.0
Depends: R (>= 3.6.0)
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2020-09-18 12:45:23 UTC; maikol
Author: Maikol Solís [aut, cre], Alberto Hernández [ctb], Ronald A. Zuñiga-Rojas [ctb], Carlos Pasquier [ctb]
Repository: CRAN
Date/Publication: 2020-09-24 09:00:02 UTC

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New package simcross with initial version 0.3-6
Package: simcross
Version: 0.3-6
Date: 2020-09-17
Title: Simulate Experimental Crosses
Description: Simulate and plot general experimental crosses. The focus is on simulating genotypes with an aim towards flexibility rather than speed. Meiosis is simulated following the Stahl model, in which chiasma locations are the superposition of two processes: a proportion p coming from a process exhibiting no interference, and the remainder coming from a process following the chi-square model.
Author: Karl W Broman [aut, cre] (<https://orcid.org/0000-0002-4914-6671>)
Maintainer: Karl W Broman <broman@wisc.edu>
Authors@R: c(person("Karl W", "Broman", role=c("aut", "cre"), email="broman@wisc.edu", comment=c(ORCID = "0000-0002-4914-6671")))
Depends: R (>= 3.1.0)
Imports: graphics, stats, Rcpp (>= 0.12.17)
Suggests: qtl, knitr, rmarkdown, testthat, devtools, roxygen2
License: GPL-3
URL: https://kbroman.org/simcross/, https://github.com/kbroman/simcross
BugReports: https://github.com/kbroman/simcross/issues
VignetteBuilder: knitr
LinkingTo: Rcpp
LazyData: true
Encoding: UTF-8
ByteCompile: true
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-09-17 15:28:19 UTC; kbroman
Repository: CRAN
Date/Publication: 2020-09-24 08:50:02 UTC

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Package ProbReco updated to version 0.1.0.1 with previous version 0.1.0 dated 2020-08-18

Title: Score Optimal Probabilistic Forecast Reconciliation
Description: Training of reconciliation weights for probabilistic forecasts to optimise total energy (or variogram) score using Stochastic Gradient Descent with automatically differentiated gradients. See Panagiotelis, Gamakumara, Athanasopoulos and Hyndman, (2020) <https://www.monash.edu/business/ebs/research/publications/ebs/wp26-2020.pdf> for a description of the methods.
Author: Anastasios Panagiotelis [aut, cre] (<https://orcid.org/0000-0001-8678-7294>)
Maintainer: Anastasios Panagiotelis <anastasios.panagiotelis@sydney.edu.au>

Diff between ProbReco versions 0.1.0 dated 2020-08-18 and 0.1.0.1 dated 2020-09-24

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Package PHInfiniteEstimates updated to version 1.5 with previous version 1.3 dated 2020-03-29

Title: Tools for Inference in the Presence of a Monotone Likelihood
Description: Proportional hazards estimation in the presence of a partially monotone likelihood has difficulties, in that finite estimators do not exist. These difficulties are related to those arising from logistic and multinomial regression. References for methods are given in the separate function documents.
Author: John E. Kolassa and Juan Zhang
Maintainer: John E. Kolassa <kolassa@stat.rutgers.edu>

Diff between PHInfiniteEstimates versions 1.3 dated 2020-03-29 and 1.5 dated 2020-09-24

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New package KneeArrower with initial version 1.0.0
Package: KneeArrower
Type: Package
Title: Finds Cutoff Points on Knee Curves
Version: 1.0.0
Author: Alan Tseng
Maintainer: Alan Tseng <alan.tseng@alum.utoronto.ca>
Description: Given a set of points around a knee curve, analyzes first and second derivatives to find knee points.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: signal
RoxygenNote: 7.1.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-18 01:07:10 UTC; aklt
Repository: CRAN
Date/Publication: 2020-09-24 08:30:02 UTC

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Package fakemake updated to version 1.7.2 with previous version 1.7.1 dated 2020-04-12

Title: Mock the Unix Make Utility
Description: Use R as a minimal build system. This might come in handy if you are developing R packages and can not use a proper build system. Stay away if you can (use a proper build system).
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>

Diff between fakemake versions 1.7.1 dated 2020-04-12 and 1.7.2 dated 2020-09-24

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Package AnnotationBustR updated to version 1.3.0 with previous version 1.2 dated 2018-04-09

Title: Extract Subsequences from GenBank Annotations
Description: Extraction of subsequences into FASTA files from GenBank annotations where gene names may vary among accessions. Borstein & O'Meara (2018) <doi:10.7717/peerj.5179>.
Author: Samuel R. Borstein <sam@borstein.com>, Brian O'Meara <bomeara@utk.edu>
Maintainer: Samuel R. Borstein <sam@borstein.com>

Diff between AnnotationBustR versions 1.2 dated 2018-04-09 and 1.3.0 dated 2020-09-24

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Package xaringan updated to version 0.17 with previous version 0.16 dated 2020-03-31

Title: Presentation Ninja
Description: Create HTML5 slides with R Markdown and the JavaScript library 'remark.js' (<https://remarkjs.com>).
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Alessandro Gasparini [ctb] (<https://orcid.org/0000-0002-8319-7624>), Benjie Gillam [ctb], Claus Thorn Ekstrøm [ctb], Daniel Anderson [ctb], Dawei Lang [ctb], Emi Tanaka [ctb], Garrick Aden-Buie [ctb] (<https://orcid.org/0000-0002-7111-0077>), Iñaki Ucar [ctb] (<https://orcid.org/0000-0001-6403-5550>), John Little [ctb], Joselyn Chávez [ctb] (<https://orcid.org/0000-0002-4974-4591>), Joseph Casillas [ctb], Lucy D'Agostino McGowan [ctb] (<https://orcid.org/0000-0001-7297-9359>), Malcolm Barrett [ctb] (<https://orcid.org/0000-0003-0299-5825>), Matthew Mark Strasiotto [ctb] (mstr3336), Michael Wayne Kearney [ctb], Nan-Hung Hsieh [ctb], Ole Petter Bang [ctb] (CSS in rmarkdown/templates/xaringan/resources/default.css), Patrick Schratz [ctb], Paul Klemm [ctb] (<https://orcid.org/0000-0002-5985-1737>), Paul Lemmens [ctb], Sean Lopp [ctb], Yongfu Liao [ctb], Yue Jiang [ctb] (<https://orcid.org/0000-0002-9798-5517>)
Maintainer: Yihui Xie <xie@yihui.name>

Diff between xaringan versions 0.16 dated 2020-03-31 and 0.17 dated 2020-09-24

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Package koRpus updated to version 0.13-2 with previous version 0.13-1 dated 2020-09-21

Title: An R Package for Text Analysis
Description: A set of tools to analyze texts. Includes, amongst others, functions for automatic language detection, hyphenation, several indices of lexical diversity (e.g., type token ratio, HD-D/vocd-D, MTLD) and readability (e.g., Flesch, SMOG, LIX, Dale-Chall). Basic import functions for language corpora are also provided, to enable frequency analyses (supports Celex and Leipzig Corpora Collection file formats) and measures like tf-idf. Note: For full functionality a local installation of TreeTagger is recommended. It is also recommended to not load this package directly, but by loading one of the available language support packages from the 'l10n' repository <https://undocumeantit.github.io/repos/l10n/>. 'koRpus' also includes a plugin for the R GUI and IDE RKWard, providing graphical dialogs for its basic features. The respective R package 'rkward' cannot be installed directly from a repository, as it is a part of RKWard. To make full use of this feature, please install RKWard from <https://rkward.kde.org> (plugins are detected automatically). Due to some restrictions on CRAN, the full package sources are only available from the project homepage. To ask for help, report bugs, request features, or discuss the development of the package, please subscribe to the koRpus-dev mailing list (<https://korpusml.reaktanz.de>).
Author: Meik Michalke [aut, cre], Earl Brown [ctb], Alberto Mirisola [ctb], Alexandre Brulet [ctb], Laura Hauser [ctb]
Maintainer: Meik Michalke <meik.michalke@hhu.de>

Diff between koRpus versions 0.13-1 dated 2020-09-21 and 0.13-2 dated 2020-09-24

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Package doFuture updated to version 0.10.0 with previous version 0.9.0 dated 2020-01-11

Title: A Universal Foreach Parallel Adapter using the Future API of the 'future' Package
Description: Provides a '%dopar%' adapter such that any type of futures can be used as backends for the 'foreach' framework.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

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Package crossmap updated to version 0.2.0 with previous version 0.1.0 dated 2020-09-10

Title: Apply Functions to All Combinations of List Elements
Description: Provides an extension to the 'purrr' family of mapping functions to apply a function to each combination of elements in a list of inputs. Also includes functions for automatically detecting output type in mapping functions, finding every combination of elements of lists or rows of data frames, and applying multiple models to multiple subsets of a dataset.
Author: Alexander Rossell Hayes [aut, cre, cph] (<https://orcid.org/0000-0001-9412-0457>)
Maintainer: Alexander Rossell Hayes <alexander@rossellhayes.com>

Diff between crossmap versions 0.1.0 dated 2020-09-10 and 0.2.0 dated 2020-09-24

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New package irt with initial version 0.1.1
Package: irt
Type: Package
Title: Item Response Theory and Computerized Adaptive Testing Functions
Version: 0.1.1
Authors@R: c(person("Emre", "Gonulates", email = "egonulates@gmail.com", role = c("aut", "cre"), comment = c(ORCID="0000-0002-3834-3266")))
Maintainer: Emre Gonulates <egonulates@gmail.com>
Description: A collection of Item Response Theory (IRT) and Computerized Adaptive Testing (CAT) functions that are used in psychometrics.
License: GPL-3
Depends: methods
LinkingTo: Rcpp
Imports: Rcpp (>= 1.0.4), ggplot2, parallel
NeedsCompilation: yes
RoxygenNote: 7.1.1
Encoding: UTF-8
LazyData: true
Collate: 'Item-class.R' 'Item-class-methods.R' 'Itempool-class.R' 'Itempool-class-methods.R' 'RcppExports.R' 'Testlet-class-methods.R' 'ability_estimation.R' 'cat_sim.R' 'cat_sim_helper_functions.R' 'dif.R' 'info.R' 'ipd.R' 'irt.R' 'item_analysis.R' 'item_fit.R' 'misc.R' 'person_fit.R' 'plot_IRT.R' 'prob.R' 'resp_lik.R' 'resp_loglik.R' 'rsss.R' 'sim_resp.R'
Packaged: 2020-09-15 18:42:13 UTC; gonul
Author: Emre Gonulates [aut, cre] (<https://orcid.org/0000-0002-3834-3266>)
Repository: CRAN
Date/Publication: 2020-09-24 06:40:03 UTC

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Package DICOMread updated to version 0.0.0.2 with previous version 0.0.0.1 dated 2020-09-01

Title: Reading and Saving DICOM Image Files
Description: This function provides an interface between 'Matlab' and 'R' in facilitating fast processing for reading and saving DICOM images.
Author: Shu Jiang [aut, cre] (<https://orcid.org/0000-0003-1464-4838>)
Maintainer: Shu Jiang <jiang.shu@wustl.edu>

Diff between DICOMread versions 0.0.0.1 dated 2020-09-01 and 0.0.0.2 dated 2020-09-24

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Wed, 23 Sep 2020

Package SailoR updated to version 1.2 with previous version 1.1.2 dated 2020-07-16

Title: An Extension of the Taylor Diagram to Two-Dimensional Vector Data
Description: A new diagram for the verification of vector variables (wind, current, etc) generated by multiple models against a set of observations is presented in this package. It has been designed as a generalization of the Taylor diagram to two dimensional quantities. It is based on the analysis of the two-dimensional structure of the mean squared error matrix between model and observations. The matrix is divided into the part corresponding to the relative rotation and the bias of the empirical orthogonal functions of the data. The full set of diagnostics produced by the analysis of the errors between model and observational vector datasets comprises the errors in the means, the analysis of the total variance of both datasets, the rotation matrix corresponding to the principal components in observation and model, the angle of rotation of model-derived empirical orthogonal functions respect to the ones from observations, the standard deviation of model and observations, the root mean squared error between both datasets and the squared two-dimensional correlation coefficient. See the output of function UVError() in this package.
Author: Jon Sáenz [aut, cph] (<https://orcid.org/0000-0002-5920-7570>), Sheila Carreno-Madinabeitia [aut, cph] (<https://orcid.org/0000-0003-4625-6178>), Santos J. González-Rojí [aut, cre, cph] (<https://orcid.org/0000-0003-4737-0984>), Ganix Esnaola [ctb, cph] (<https://orcid.org/0000-0001-9058-043X>), Gabriel Ibarra-Berastegi [ctb, cph] (<https://orcid.org/0000-0001-8681-3755>), Alain Ulazia [ctb, cph] (<https://orcid.org/0000-0002-4124-2853>)
Maintainer: Santos J. González-Rojí <santosjose.gonzalez@ehu.eus>

Diff between SailoR versions 1.1.2 dated 2020-07-16 and 1.2 dated 2020-09-23

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Package ojsr updated to version 0.1.2 with previous version 0.1.1 dated 2020-07-01

Title: Crawler and Data Scraper for Open Journal System ('OJS')
Description: Crawler for 'OJS' pages and scraper for meta-data from articles. You can crawl 'OJS' archives, issues, articles, galleys, and search results. You can scrape articles metadata from their head tag in html, or from Open Archives Initiative ('OAI') records. Most of these functions rely on 'OJS' routing conventions (<https://docs.pkp.sfu.ca/dev/documentation/en/architecture-routes>).
Author: Gaston Becerra [aut, cre] (<https://orcid.org/0000-0001-9432-8848>)
Maintainer: Gaston Becerra <gaston.becerra@gmail.com>

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Package miic updated to version 1.5.2 with previous version 1.5.1 dated 2020-09-18

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: Cabeli et al. PLoS Comp. Bio. 2020 <doi:10.1371/journal.pcbi.1007866>, Verny et al. PLoS Comp. Bio. 2017 <doi:10.1371/journal.pcbi.1005662>.
Author: Vincent Cabeli [aut, cre], Honghao Li [aut], Marcel Ribeiro Dantas [aut], Nadir Sella [aut], Louis Verny [aut], Severine Affeldt [aut], Hervé Isambert [aut]
Maintainer: Vincent Cabeli <vincent.cabeli@curie.fr>

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Package asnipe updated to version 1.1.13 with previous version 1.1.12 dated 2019-08-19

Title: Animal Social Network Inference and Permutations for Ecologists
Description: Implements several tools that are used in animal social network analysis, as described in Whitehead (2007) Analyzing Animal Societies <University of Chicago Press> and Farine & Whitehead (2015) <doi: 10.1111/1365-2656.12418>. 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@ab.mpg.de>
Maintainer: Damien R. Farine <dfarine@ab.mpg.de>

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Package lessR updated to version 3.9.7 with previous version 3.9.6 dated 2020-06-11

Title: Less Code, More Results
Description: Each function accomplishes the work of several or more standard R functions. For example, two function calls, Read() and CountAll(), read the data and generate summary statistics for all variables in the data frame, plus histograms and bar charts as appropriate. Other functions provide for descriptive statistics, a comprehensive regression analysis, analysis of variance and t-test, plotting including the introduced here Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve, reading multiple data formats with the same function call, variable labels, color themes, Trellis graphics and a built-in help system. Also includes a confirmatory factor analysis of multiple indicator measurement models, pedagogical routines for data simulation such as for the Central Limit Theorem, and generation and rendering of R markdown instructions for interpretative output.
Author: David Gerbing, The School of Business, Portland State University
Maintainer: David W. Gerbing <gerbing@pdx.edu>

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Package gimme updated to version 0.7-3 with previous version 0.7-2 dated 2020-09-03

Title: Group Iterative Multiple Model Estimation
Description: Automated identification and estimation of group- and individual-level relations in time series data from within a structural equation modeling framework.
Author: Stephanie Lane [aut, trl], Kathleen Gates [aut, cre], Zachary Fisher [aut], Cara Arizmendi [aut], Peter Molenaar [aut], Michael Hallquist [ctb], Hallie Pike [ctb], Teague Henry [ctb], Kelly Duffy [ctb], Lan Luo [ctb], Adriene Beltz [csp]
Maintainer: KM Gates <gateskm@email.unc.edu>

Diff between gimme versions 0.7-2 dated 2020-09-03 and 0.7-3 dated 2020-09-23

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Package FHtest updated to version 1.5 with previous version 1.4 dated 2017-11-08

Title: Tests for Right and Interval-Censored Survival Data Based on the Fleming-Harrington Class
Description: Functions to compare two or more survival curves with: a) The Fleming-Harrington test for right-censored data based on permutations and on counting processes. b) An extension of the Fleming-Harrington test for interval-censored data based on a permutation distribution and on a score vector distribution.
Author: Ramon Oller, Klaus Langohr
Maintainer: Ramon Oller <ramon.oller@uvic.cat>

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Package rsample updated to version 0.0.8 with previous version 0.0.7 dated 2020-06-04

Title: General Resampling Infrastructure
Description: Classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).
Author: Max Kuhn [aut, cre], Fanny Chow [aut], Hadley Wickham [aut], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

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Package aziztest updated to version 0.2.0 with previous version 0.1.0 dated 2020-04-01

Title: Novel Statistical Test for Aberration Enrichment
Description: Testing for heterogeneous effects in a case-control setting. The aim here to discover an association that is beyond a mean difference between all cases and all controls. Instead, the signal of interest here is present in only a proportion of the cases. This test should be more powerful than a t-test or Wilcoxon test in this heterogeneous setting. Please cite the corresponding paper: Mezlini et al. (2020) <doi:10.1101/2020.03.23.002972>.
Author: Aziz M. Mezlini [aut,cre,cph]
Maintainer: Aziz M. Mezlini <mmezlini@mgh.harvard.edu>

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New package SLTCA with initial version 0.1.0
Package: SLTCA
Type: Package
Title: Scalable and Robust Latent Trajectory Class Analysis
Description: Conduct latent trajectory class analysis with longitudinal data. Our method supports longitudinal continuous, binary and count data. For more methodological details, please refer to Hart, K.R., Fei, T. and Hanfelt, J.J. (2020), Scalable and robust latent trajectory class analysis using artificial likelihood. Biometrics <doi:10.1111/biom.13366>.
Depends: R (>= 3.3.0)
Imports: stats, geepack, VGAM, Matrix, mvtnorm
Version: 0.1.0
Authors@R: c( person("Kari", "Hart", email = "khart@peddie.org", role = "aut"), person("Teng", "Fei", email = "tfei@emory.edu", role = c("cre","aut"), comment = c(ORCID = "0000-0001-7888-1715")), person("John", "Hanfelt", email = "jhanfel@emory.edu", role = "aut", comment = c(ORCID = "0000-0002-8488-6771")) )
Maintainer: Teng Fei <tfei@emory.edu>
BugReports: https://github.com/tengfei-emory/SLTCA/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-17 18:18:58 UTC; TFEI
Author: Kari Hart [aut], Teng Fei [cre, aut] (<https://orcid.org/0000-0001-7888-1715>), John Hanfelt [aut] (<https://orcid.org/0000-0002-8488-6771>)
Repository: CRAN
Date/Publication: 2020-09-23 15:30:07 UTC

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New package omxr with initial version 0.3.3
Package: omxr
Type: Package
Title: Read and Write Open Matrix Files
Version: 0.3.3
Date: 2020-09-16
Authors@R: c( person("Brian", "Gregor", email = "", role = "aut"), person("Ben", "Stabler", email = "", role = "aut"), person("Greg", "Macfarlane", email = "gregmacfarlane@gmail.com", role = "cre") )
Description: The Open Matrix (OMX) file type is an open specification for sharing data from transportation models. The specification is built on HDF5 <https://www.hdfgroup.org/>; APIs to read and write are available for 'Cube', 'Emme', 'Python', 'Java', and 'R'.
License: Apache License 2.0
LazyData: TRUE
Suggests: knitr, tidyverse
VignetteBuilder: knitr
biocViews: rhdf5, zlibbioc
Imports: rhdf5, hms, zlibbioc, tidyr (>= 0.8.0), readr, dplyr, purrr, magrittr, rlang
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-17 16:53:48 UTC; gregmacfarlane
Author: Brian Gregor [aut], Ben Stabler [aut], Greg Macfarlane [cre]
Maintainer: Greg Macfarlane <gregmacfarlane@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 15:30:03 UTC

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Package multcomp updated to version 1.4-14 with previous version 1.4-13 dated 2020-04-08

Title: Simultaneous Inference in General Parametric Models
Description: Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book "Multiple Comparisons Using R" (Bretz, Hothorn, Westfall, 2010, CRC Press).
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>), Frank Bretz [aut], Peter Westfall [aut], Richard M. Heiberger [ctb], Andre Schuetzenmeister [ctb], Susan Scheibe [ctb]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between multcomp versions 1.4-13 dated 2020-04-08 and 1.4-14 dated 2020-09-23

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New package combinedevents with initial version 0.1.0
Package: combinedevents
Title: Calculate Scores and Marks for Track and Field Combined Events
Version: 0.1.0
Authors@R: person(given = "Katie", family = "Frank", role = c("aut", "cre"), email = "katiexfrank@gmail.com", comment = c(ORCID = "0000-0002-0353-0328"))
Description: Includes functions to calculate scores and marks for track and field combined events competitions. The functions are based on the scoring tables for combined events set forth by the International Association of Athletics Federation (2001) <https://www.worldathletics.org/about-iaaf/documents/technical-information>.
License: GPL-3
URL: https://katie-frank.github.io/combinedevents/, https://github.com/katie-frank/combinedevents
BugReports: https://github.com/katie-frank/combinedevents/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: lubridate, magrittr, rlang, stats, stringr
Suggests: knitr, rmarkdown, testthat, spelling, covr
Depends: R (>= 2.10)
Language: en-US
NeedsCompilation: no
Packaged: 2020-09-17 14:16:45 UTC; katiefrank
Author: Katie Frank [aut, cre] (<https://orcid.org/0000-0002-0353-0328>)
Maintainer: Katie Frank <katiexfrank@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 14:00:02 UTC

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New package AGPRIS with initial version 1.0
Package: AGPRIS
Title: AGricultural PRoductivity in Space
Version: 1.0
Authors@R: person(given = "Edoardo", family = "Baldoni", role = c("aut", "cre"), email = "edoardo.baldoni@gmail.com", comment = c(ORCID = "https://orcid.org/0000-0002-5296-1212"))
Description: Functionalities to simulate space-time data and to estimate dynamic-spatial panel data models. Estimators implemented are the BCML (Elhorst (2010), <doi:10.1016/j.regsciurbeco.2010.03.003>), the MML (Elhorst (2010) <doi:10.1016/j.regsciurbeco.2010.03.003>) and the INLA Bayesian estimator (Lindgren and Rue, (2015) <doi:10.18637/jss.v063.i19>; Bivand, Gomez-Rubio and Rue, (2015) <doi:10.18637/jss.v063.i20>) adapted to panel data. The package contains functions to replicate the analyses of the scientific article entitled "Agricultural Productivity in Space" (Baldoni and Esposti (under revision)).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: methods, Matrix, plyr, rgdal, sp, spdep, spacetime, matrixcalc, maxLik
Suggests: INLA
NeedsCompilation: no
Packaged: 2020-09-17 16:34:57 UTC; Edoardo
Author: Edoardo Baldoni [aut, cre] (<https://orcid.org/0000-0002-5296-1212>)
Maintainer: Edoardo Baldoni <edoardo.baldoni@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 15:20:02 UTC

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New package contactdata with initial version 0.1
Package: contactdata
Title: Social Contact Matrices for 152 Countries
Version: 0.1
Authors@R: c(person(given = "Hugo", family = "Gruson", role = c("cre", "aut", "cph"), email = "hugo.gruson+R@normalesup.org", comment = c(ORCID = "0000-0002-4094-1476")), person(given = "Kiesha", family = "Prem", role = "dtc", comment = c(ORCID = "0000-0003-0528-798X")), person(given = c("Alex", "Richard"), family = "Cook", role = "dtc", comment = c(ORCID = "0000-0002-6271-5832")), person(given = "Mark", family = "Jit", role = "dtc", comment = c(ORCID = "0000-0001-6658-8255")))
Description: Data package for the supplementary data in Prem et al. (2017) <doi:10.1371/journal.pcbi.1005697>. Provides easy access to contact data for 152 countries, for use in epidemiological, demographic or social sciences research.
License: MIT + file LICENSE
Depends: R (>= 3.5)
Suggests: countrycode, ggplot2, knitr, rmarkdown, spelling, testthat, covr
URL: https://bisaloo.github.io/contactdata/, https://github.com/bisaloo/contactdata
BugReports: https://github.com/bisaloo/contactdata/issues
Encoding: UTF-8
Language: en-GB
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2020-09-17 11:19:25 UTC; hugo
Author: Hugo Gruson [cre, aut, cph] (<https://orcid.org/0000-0002-4094-1476>), Kiesha Prem [dtc] (<https://orcid.org/0000-0003-0528-798X>), Alex Richard Cook [dtc] (<https://orcid.org/0000-0002-6271-5832>), Mark Jit [dtc] (<https://orcid.org/0000-0001-6658-8255>)
Maintainer: Hugo Gruson <hugo.gruson+R@normalesup.org>
Repository: CRAN
Date/Publication: 2020-09-23 13:50:03 UTC

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New package EquiSurv with initial version 0.1.0
Package: EquiSurv
Type: Package
Title: Modeling, Confidence Intervals and Equivalence of Survival Curves
Version: 0.1.0
Author: Kathrin Moellenhoff
Maintainer: Kathrin Moellenhoff <kathrin.moellenhoff@rub.de>
Description: We provide a non-parametric and a parametric approach to investigate the equivalence (or non-inferiority) of two survival curves, obtained from two given datasets. The test is based on the creation of confidence intervals at pre-specified time points. For the non-parametric approach, the curves are given by Kaplan-Meier curves and the variance for calculating the confidence intervals is obtained by Greenwood's formula. The parametric approach is based on estimating the underlying distribution, where the user can choose between a Weibull, Exponential, Gaussian, Logistic, Log-normal or a Log-logistic distribution. Estimates for the variance for calculating the confidence bands are obtained by a (parametric) bootstrap approach. For this bootstrap censoring is assumed to be exponentially distributed and estimates are obtained from the datasets under consideration. All details can be found in K.Moellenhoff and A.Tresch: Survival analysis under non-proportional hazards: investigating non-inferiority or equivalence in time-to-event data <arXiv:2009.06699>.
Depends: survival, eha, graphics
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-17 08:47:18 UTC; Kathrin
Repository: CRAN
Date/Publication: 2020-09-23 13:30:02 UTC

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Package statgenSTA updated to version 1.0.6 with previous version 1.0.5 dated 2020-06-24

Title: Single Trial Analysis (STA) of Field Trials
Description: Phenotypic analysis of field trials using mixed models with and without spatial components. One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris. Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<http://www.vsni.co.uk/software/asreml-r>).
Author: Bart-Jan van Rossum [aut, cre], Fred van Eeuwijk [ctb] (<https://orcid.org/0000-0003-3672-2921>), Martin Boer [ctb], Marcos Malosetti [ctb] (<https://orcid.org/0000-0002-8150-1397>), Daniela Bustos-Korts [ctb] (<https://orcid.org/0000-0003-3827-6726>), Emilie J. Millet [ctb] (<https://orcid.org/0000-0002-2913-4892>), Joao Paulo [ctb] (<https://orcid.org/0000-0002-4180-0763>), Maikel Verouden [ctb] (<https://orcid.org/0000-0002-4893-3323>), Willem Kruijer [ctb] (<https://orcid.org/0000-0001-7179-1733>), Ron Wehrens [ctb] (<https://orcid.org/0000-0002-8798-5599>), Choazhi Zheng [ctb] (<https://orcid.org/0000-0001-6030-3933>)
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>

Diff between statgenSTA versions 1.0.5 dated 2020-06-24 and 1.0.6 dated 2020-09-23

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 vignettes/statgenSTA.Rmd            |   40 ++-
 51 files changed, 2197 insertions(+), 1645 deletions(-)

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Package nasapower updated to version 2.0.0 with previous version 1.1.3 dated 2019-11-18

Title: NASA POWER API Client
Description: Client for 'NASA' 'POWER' global meteorology, surface solar energy and climatology data 'API'. 'POWER' (Prediction Of Worldwide Energy Resource) data are freely available global meteorology and surface solar energy climatology data for download with a resolution of 1/2 by 1/2 arc degree longitude and latitude and are funded through the 'NASA' Earth Science Directorate Applied Science Program. For more on the data themselves, a web-based data viewer and web access, please see <https://power.larc.nasa.gov/>.
Author: Adam H. Sparks [aut, cre] (<https://orcid.org/0000-0002-0061-8359>), Scott Chamberlain [rev] (<https://orcid.org/0000-0003-1444-9135>, Scott Chamberlain reviewed nasapower for rOpenSci, see https://github.com/ropensci/software-review/issues/155), Hazel Kavili [rev] (Hazel Kavili reviewed nasapower for rOpenSci, see https://github.com/ropensci/software-review/issues/155), Alison Boyer [rev] (Alison Boyer reviewed nasapower for rOpenSci, see https://github.com/ropensci/software-review/issues/155)
Maintainer: Adam H. Sparks <adamhsparks@gmail.com>

Diff between nasapower versions 1.1.3 dated 2019-11-18 and 2.0.0 dated 2020-09-23

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Package cronR updated to version 0.4.2 with previous version 0.4.0 dated 2018-03-08

Title: Schedule R Scripts and Processes with the 'cron' Job Scheduler
Description: Create, edit, and remove 'cron' jobs on your unix-alike system. The package provides a set of easy-to-use wrappers to 'crontab'. It also provides an RStudio add-in to easily launch and schedule your scripts.
Author: Jan Wijffels [aut, cre, cph], BNOSAC [cph], Kevin Ushey [cph]
Maintainer: Jan Wijffels <jwijffels@bnosac.be>

Diff between cronR versions 0.4.0 dated 2018-03-08 and 0.4.2 dated 2020-09-23

 DESCRIPTION         |   11 -
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 README.md           |    5 
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 8 files changed, 297 insertions(+), 123 deletions(-)

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Package schoRsch updated to version 1.8 with previous version 1.7 dated 2019-11-12

Title: Tools for Analyzing Factorial Experiments
Description: Offers a helping hand to psychologists and other behavioral scientists who routinely deal with experimental data from factorial experiments. It includes several functions to format output from other R functions according to the style guidelines of the APA (American Psychological Association). This formatted output can be copied directly into manuscripts to facilitate data reporting. These features are backed up by a toolkit of several small helper functions, e.g., offering out-of-the-box outlier removal. The package lends its name to Georg "Schorsch" Schuessler, ingenious technician at the Department of Psychology III, University of Wuerzburg. For details on the implemented methods, see Roland Pfister and Markus Janczyk (2016) <doi: 10.20982/tqmp.12.2.p147>.
Author: Roland Pfister, Markus Janczyk
Maintainer: Roland Pfister <roland.pfister@psychologie.uni-wuerzburg.de>

Diff between schoRsch versions 1.7 dated 2019-11-12 and 1.8 dated 2020-09-23

 DESCRIPTION     |    8 ++++----
 MD5             |    6 +++---
 R/anova_out.R   |    8 ++++++--
 man/schoRsch.Rd |    9 +++++----
 4 files changed, 18 insertions(+), 13 deletions(-)

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New package RSmallTelescopes with initial version 1.0.2
Package: RSmallTelescopes
Title: Empirical Small Telescopes Analysis
Version: 1.0.2
Authors@R: c( person(given = "John", family = "Ruscio", role = c("aut", "cre"), email = "ruscio@tcnj.edu"), person(given = "Samantha", family = "Costigan", role = c("ctb"), email = "costigs1@tcnj.edu"))
Description: We provide functions to perform an empirical small telescopes analysis. This package contains 2 functions, SimulatePower() and EstimatePower(). Users only need to call SimulatePower() to conduct the analysis. For more information on small telescopes analysis see Uri Simonsohn (2015) <doi:10.1177/0956797614567341>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-16 18:21:48 UTC; ruthec
Author: John Ruscio [aut, cre], Samantha Costigan [ctb]
Maintainer: John Ruscio <ruscio@tcnj.edu>
Repository: CRAN
Date/Publication: 2020-09-23 09:10:08 UTC

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New package path.chain with initial version 0.2.0
Package: path.chain
Type: Package
Title: Concise Structure for Chainable Paths
Version: 0.2.0
Authors@R: person(given = "Krzysztof", family = "Joachimiak", role = c("aut", "cre"), email = "joachimiak.krzysztof@gmail.com", comment = c(ORCID = "0000-0003-4780-7947"))
Description: Provides path_chain class and functions, which facilitates loading and saving directory structure in YAML configuration files via 'config' package. The file structure you created during exploration can be transformed into legible section in the config file, and then easily loaded for further usage.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/krzjoa/path.chain/issues
URL: https://github.com/krzjoa/path.chain, https://krzjoa.github.io/path.chain/
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, config, yaml, fs, magrittr
VignetteBuilder: knitr
Imports: rlang, stringi, logger
NeedsCompilation: no
Packaged: 2020-09-16 21:03:38 UTC; krzysztof
Author: Krzysztof Joachimiak [aut, cre] (<https://orcid.org/0000-0003-4780-7947>)
Maintainer: Krzysztof Joachimiak <joachimiak.krzysztof@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 09:20:03 UTC

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New package mlquantify with initial version 0.1.4
Package: mlquantify
Type: Package
Title: Algorithms for Class Distribution Estimation
Version: 0.1.4
Authors@R: c( person("Andre", "Maletzke", email = "andregustavom@gmail.com", role = c("aut","cre")), person("Everton", "Cherman", email = "evertoncherman@gmail.com", role = "ctb"), person("Denis", "dos Reis", email = "denismr@gmail.com", role = "ctb"), person("Gustavo", "Batista", email = "g.batista@unsw.edu.au", role = "ths"))
Maintainer: Andre Maletzke <andregustavom@gmail.com>
Description: Quantification is a prominent machine learning task that has received an increasing amount of attention in the last years. The objective is to predict the class distribution of a data sample. This package is a collection of machine learning algorithms for class distribution estimation. This package include algorithms from different paradigms of quantification. These methods are described in the paper: A. Maletzke, W. Hassan, D. dos Reis, and G. Batista. The importance of the test set size in quantification assessment. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI20, pages 2640–2646, 2020. <doi:10.24963/ijcai.2020/366>.
License: GPL (>= 2.0)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Author: Andre Maletzke [aut, cre], Everton Cherman [ctb], Denis dos Reis [ctb], Gustavo Batista [ths]
RoxygenNote: 7.1.1
BugReports: https://github.com/andregustavom/mlquantify/issues
URL: https://github.com/andregustavom/mlquantify
Imports: caret, randomForest, stats
Suggests: CORElearn
Packaged: 2020-09-16 16:11:44 UTC; andregustavom
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2020-09-23 09:20:08 UTC

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New package fusionchartsR with initial version 0.0.1
Package: fusionchartsR
Type: Package
Version: 0.0.1
Title: Embedding 'FusionCharts Javascript' Library in R
Description: FusionCharts provides awesome and minimalist functions to make beautiful interactive charts <https://www.fusioncharts.com/>.
Authors@R: person(given = "Alex", family = "Yahiaoui Martinez", role = c("aut", "cre"), email = "yahiaoui-martinez.alex@outlook.com")
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: htmlwidgets, jsonlite, magrittr
Suggests: rmarkdown, knitr, shiny, testthat
NeedsCompilation: no
Packaged: 2020-09-16 16:28:11 UTC; yahia
Author: Alex Yahiaoui Martinez [aut, cre]
Maintainer: Alex Yahiaoui Martinez <yahiaoui-martinez.alex@outlook.com>
Repository: CRAN
Date/Publication: 2020-09-23 09:10:03 UTC

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New package corona with initial version 0.3.0
Package: corona
Title: Coronavirus ('Rona') Data Exploration
Version: 0.3.0
Depends: R (>= 3.5.0), plyr
Imports: gganimate, ggplot2, gridExtra, qicharts2, reshape2
Authors@R: person(given = "Jo", family = "van Schalkwyk", role = c("aut", "cre"), email = "jvanschalkwyk@gmail.com", comment = c(ORCID = "0000-0002-0082-5243"))
Maintainer: Jo van Schalkwyk <jvanschalkwyk@gmail.com>
Description: Manipulate and view coronavirus data and other societally relevant data at a basic level.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-09-17 01:16:56 UTC; jo
Author: Jo van Schalkwyk [aut, cre] (<https://orcid.org/0000-0002-0082-5243>)
Repository: CRAN
Date/Publication: 2020-09-23 09:30:03 UTC

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New package wordsalad with initial version 0.2.0
Package: wordsalad
Title: Provide Tools to Extract and Analyze Word Vectors
Version: 0.2.0
Authors@R: person(given = "Emil", family = "Hvitfeldt", role = c("aut", "cre"), email = "emilhhvitfeldt@gmail.com", comment = c(ORCID = "0000-0002-0679-1945"))
Description: Provides access to various word embedding methods (GloVe, fasttext and word2vec) to extract word vectors using a unified framework to increase reproducibility and correctness.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: tibble, text2vec, word2vec, fastTextR
Suggests: testthat
URL: https://github.com/EmilHvitfeldt/wordsalad
BugReports: https://github.com/EmilHvitfeldt/wordsalad/issues
NeedsCompilation: no
Packaged: 2020-09-15 20:34:24 UTC; emilhvitfeldthansen
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 08:10:03 UTC

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New package twenty48 with initial version 0.1.0
Package: twenty48
Title: Play a Game of 2048 in the Console
Version: 0.1.0
Authors@R: person(given = "Alexander", family = "Rossell Hayes", role = c("aut", "cre", "cph"), email = "alexander@rossellhayes.com", comment = c(ORCID = "0000-0001-9412-0457"))
Description: Generates a game of 2048 that can be played in the console. Supports grids of arbitrary sizes, undoing the last move, and resuming a game that was exited during the current session.
License: MIT + file LICENSE
URL: https://github.com/rossellhayes/twenty48
BugReports: https://github.com/rossellhayes/twenty48/issues
Depends: R (>= 2.10)
Imports: crayon, R6
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-16 08:18:35 UTC; Alex
Author: Alexander Rossell Hayes [aut, cre, cph] (<https://orcid.org/0000-0001-9412-0457>)
Maintainer: Alexander Rossell Hayes <alexander@rossellhayes.com>
Repository: CRAN
Date/Publication: 2020-09-23 08:40:03 UTC

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New package tibblify with initial version 0.1.0
Package: tibblify
Title: Rectangle Nested Lists
Version: 0.1.0
Authors@R: person(given = "Maximilian", family = "Girlich", role = c("aut", "cre"), email = "maximilian.girlich@outlook.com")
Description: A tool to rectangle a nested list, that is to convert it into a tibble. This is done automatically or according to a given specification. A common use case is for nested lists coming from parsing JSON files or the JSON response of REST APIs. It is supported by the 'vctrs' package and therefore offers a wide support of vector types.
License: GPL-3
Suggests: testthat, knitr, rmarkdown, covr, spelling
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: crayon, rlang, vctrs, purrr, tibble
VignetteBuilder: knitr
Depends: R (>= 3.4.0)
URL: https://github.com/mgirlich/tibblify
BugReports: https://github.com/mgirlich/tibblify/issues
Language: en-US
NeedsCompilation: no
Packaged: 2020-09-16 06:55:20 UTC; mgirlich
Author: Maximilian Girlich [aut, cre]
Maintainer: Maximilian Girlich <maximilian.girlich@outlook.com>
Repository: CRAN
Date/Publication: 2020-09-23 08:40:07 UTC

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New package T4cluster with initial version 0.1.0
Package: T4cluster
Type: Package
Title: Tools for Cluster Analysis
Version: 0.1.0
Authors@R: c(person("Kisung", "You", role = c("aut", "cre"), email = "kyoustat@gmail.com",comment=c(ORCID="0000-0002-8584-459X")))
Encoding: UTF-8
Description: Cluster analysis is one of the most fundamental problems in data science. We provide a variety of algorithms from clustering to the learning on the space of partitions. See Hennig, Meila, and Rocci (2016, ISBN:9781466551886) for general exposition to cluster analysis.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.5), Rdpack, Rdimtools, maotai, stats, utils
URL: http://kyoustat.com/T4cluster/
BugReports: https://github.com/kyoustat/T4cluster/issues
LinkingTo: Rcpp, RcppArmadillo
RdMacros: Rdpack
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-09-16 03:43:35 UTC; kisung
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyoustat@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 08:30:02 UTC

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New package SlaPMEG with initial version 1.0.0
Package: SlaPMEG
Type: Package
Title: Pathway Testing for Longitudinal Omics
Version: 1.0.0
Author: Mitra Ebrahimpoor
Maintainer: Mitra Ebrahimpoor <mitra.ebrahimpoor@gmail.com>
Description: A self-contained hypothesis is tested for a given pathway of longitudinal omics. 'SlaPMEG' is a two-step procedure. First, a shared latent process mixed model is fitted over the longitudinal measures of omics in a pathway. This shared model allows deviation from the shared process at subject level (a random intercept, slope, or both per subject) and also at omic level (a random effect per omic). These random effects summarize the longitudinal trend of the observations which can be used to test for group differences using 'Globaltest' in the second step. If the pathway is large or the shared effect is small, the package fits a series of pairwise models and estimates the shared random effects based on them.
License: GPL (>= 2)
Date: 2020-09-05
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: lme4 (>= 1.1.21), lcmm (>= 1.8.1), globaltest (>= 5.36.0), magic (>= 1.5.9), reshape2 (>= 1.4.3), ggplot2 (>= 3.2.1), mvtnorm
NeedsCompilation: no
Packaged: 2020-09-15 19:37:47 UTC; mebrahimpoor
Repository: CRAN
Date/Publication: 2020-09-23 08:10:08 UTC

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New package RJcluster with initial version 0.1.0
Package: RJcluster
Title: RJ Clustering Algorithm
Version: 0.1.0
Authors@R: c(person(given = "Rachael", family = "Shudde", role = c("aut", "cre"), email = "rachael.shudde@gmail.com"), person(given = "Shahina", family = "Rahman", role = c("aut"), email = "srahman@stat.tamu.edu"), person(given = "Valen", family = "Johnson", role = c("aut"), email = "vejohnson@exchange.tamu.edu"))
Description: Clustering algorithm for high dimensional data. This algorithm is ideal for data where n << p.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.2), matrixStats, infotheo, rlang, stats, graphics, profvis, mclust, doParallel, foreach, parallel
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 2.1.0), knitr, rmarkdown
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2020-09-15 18:02:51 UTC; rachaelshudde
Author: Rachael Shudde [aut, cre], Shahina Rahman [aut], Valen Johnson [aut]
Maintainer: Rachael Shudde <rachael.shudde@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 08:00:06 UTC

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New package mmb with initial version 0.13.3
Package: mmb
Type: Package
Title: Arbitrary Dependency Mixed Multivariate Bayesian Models
Version: 0.13.3
Author: Sebastian Hönel
Maintainer: Sebastian Hönel <sebastian.honel@lnu.se>
Description: Supports Bayesian models with full and partial (hence arbitrary) dependencies between random variables. Discrete and continuous variables are supported, and conditional joint probabilities and probability densities are estimated using Kernel Density Estimation (KDE). The full general form, which implements an extension to Bayes' theorem, as well as the simple form, which is just a Bayesian network, both support regression through segmentation and KDE and estimation of probability or relative likelihood of discrete or continuous target random variables. This package also provides true statistical distance measures based on Bayesian models. Furthermore, these measures can be facilitated on neighborhood searches, and to estimate the similarity and distance between data points. Related work is by Bayes (1763) <doi:10.1098/rstl.1763.0053> and by Scutari (2010) <doi:10.18637/jss.v035.i03>.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/MrShoenel/R-mmb
BugReports: https://github.com/MrShoenel/R-mmb/issues
LazyData: true
VignetteBuilder: knitr
Suggests: devtools, testthat, covr, e1071, caret, knitr, rmarkdown, ggplot2, ggpubr, cowplot, philentropy, Rtsne
RoxygenNote: 7.1.1
Imports: Rdpack, datasets, stats, foreach, parallel, doParallel
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2020-09-15 19:37:43 UTC; Admin
Repository: CRAN
Date/Publication: 2020-09-23 08:00:02 UTC

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New package MABOUST with initial version 1.0.0
Package: MABOUST
Type: Package
Title: Multi-Armed Bayesian Ordinal Utility-Based Sequential Trial
Version: 1.0.0
Author: Andrew Chapple
Maintainer: Andrew Chapple <achapp@lsuhsc.edu>
Description: Conducts and simulates the MABOUST design, including making interim decisions to stop a treatment for inferiority or stop the trial early for superiority or equivalency.
License: GPL-2
Imports: Rcpp (>= 0.12.18)
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-09-15 20:00:10 UTC; achapp
Repository: CRAN
Date/Publication: 2020-09-23 08:10:15 UTC

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Package crmReg updated to version 1.0.2 with previous version 1.0.1 dated 2020-04-06

Title: Cellwise Robust M-Regression and SPADIMO
Description: Method for fitting a cellwise robust linear M-regression model (CRM, Filzmoser et al. (2020) <DOI:10.1016/j.csda.2020.106944>) that yields both a map of cellwise outliers consistent with the linear model, and a vector of regression coefficients that is robust against vertical outliers and leverage points. As a by-product, the method yields an imputed data set that contains estimates of what the values in cellwise outliers would need to amount to if they had fit the model. The package also provides diagnostic tools for analyzing casewise and cellwise outliers using sparse directions of maximal outlyingness (SPADIMO, Debruyne et al. (2019) <DOI:10.1007/s11222-018-9831-5>).
Author: Peter Filzmoser [aut], Sebastiaan Hoppner [aut, cre], Irene Ortner [aut], Sven Serneels [aut], Tim Verdonck [aut]
Maintainer: Sebastiaan Hoppner <sebastiaan.hoppner@gmail.com>

Diff between crmReg versions 1.0.1 dated 2020-04-06 and 1.0.2 dated 2020-09-23

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 MD5                   |    4 ++--
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 3 files changed, 8 insertions(+), 8 deletions(-)

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Package centrifugeR updated to version 0.1.5 with previous version 0.1.4 dated 2020-04-17

Title: Non-Trivial Balance of Centrifuge Rotors
Description: Find the numbers of tubes that can be loaded in centrifuge rotors in a single operation and show how to balance these tubes in cases of equal or unequal masses. Refer to Pham (2020) <doi:10.31224/osf.io/4xs38> for more information on package functionality.
Author: Duy Nghia Pham [aut, cre] (<https://orcid.org/0000-0003-1349-1710>)
Maintainer: Duy Nghia Pham <nghiapham@yandex.com>

Diff between centrifugeR versions 0.1.4 dated 2020-04-17 and 0.1.5 dated 2020-09-23

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Package DRomics updated to version 2.1-3 with previous version 2.1-2 dated 2020-09-22

Title: Dose Response for Omics
Description: Several functions are provided for dose-response (or concentration-response) characterization from omics data. 'DRomics' is especially dedicated to omics data obtained using a typical dose-response design, favoring a great number of tested doses (or concentrations) rather than a great number of replicates (no need of three replicates). 'DRomics' provides functions 1) to check, normalize and or transform data, 2) to select monotonic or biphasic significantly responding items (e.g. probes, metabolites), 3) to choose the best-fit model among a predefined family of monotonic and biphasic models to describe each selected item, 4) to derive a benchmark dose or concentration and a typology of response from each fitted curve. In the available version data are supposed to be single-channel microarray data in log2, RNAseq data in raw counts, or already pretreated metabolomic data in log scale. In order to link responses across biological levels based on a common method, 'DRomics' also handles apical data as long as they are continuous and follow a Gaussian distribution for each dose or concentration, with a common standard error. For further details see Larras et al (2018) <DOI:10.1021/acs.est.8b04752> at <https://hal.archives-ouvertes.fr/hal-02309919>.
Author: Marie-Laure Delignette-Muller [aut], Elise Billoir [aut], Floriane Larras [ctb], Aurelie Siberchicot [aut, cre]
Maintainer: Aurelie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>

Diff between DRomics versions 2.1-2 dated 2020-09-22 and 2.1-3 dated 2020-09-23

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New package rmdcev with initial version 1.2.3
Package: rmdcev
Type: Package
Title: Kuhn-Tucker and Multiple Discrete-Continuous Extreme Value Models
Version: 1.2.3
Authors@R: c( person(given = "Patrick", family = "Lloyd-Smith", role = c("aut", "cre"), email = "patrick.lloydsmith@usask.ca"), person("Trustees of", "Columbia University", role = "cph"))
Maintainer: Patrick Lloyd-Smith <patrick.lloydsmith@usask.ca>
Description: Estimates and simulates Kuhn-Tucker demand models with individual heterogeneity. The package implements the multiple-discrete continuous extreme value (MDCEV) model and the Kuhn-Tucker specification common in the environmental economics literature on recreation demand. Latent class and random parameters specifications can be implemented and the models are fit using maximum likelihood estimation or Bayesian estimation. All models are implemented in Stan, which is a C++ package for performing full Bayesian inference (see Stan Development Team, 2019) <https://mc-stan.org/>. The package also implements demand forecasting (Pinjari and Bhat (2011) <https://repositories.lib.utexas.edu/handle/2152/23880>) and welfare calculation (Lloyd-Smith (2018) <doi:10.1016/j.jocm.2017.12.002>) for policy simulation.
License: MIT + file LICENSE
Depends: R (>= 3.6.0), Rcpp (>= 1.0.5), methods
Imports: rstan (>= 2.21.0), rstantools (>= 2.1.1), RcppParallel (>= 5.0.1), dplyr (>= 0.7.8), purrr, tibble, tidyr, utils, stats, Formula
LinkingTo: BH (>= 1.72.0), Rcpp, RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.21.0), StanHeaders (>= 2.21.0)
Encoding: UTF-8
LazyData: true
Repository: CRAN
SystemRequirements: GNU make
RoxygenNote: 7.1.1
Biarch: true
Suggests: knitr, rmarkdown, testthat
URL: https://github.com/plloydsmith/rmdcev
BugReports: https://github.com/plloydsmith/rmdcev/issues
Author: Patrick Lloyd-Smith [aut, cre], Trustees of Columbia University [cph]
NeedsCompilation: yes
Packaged: 2020-09-22 04:33:54 UTC; Pat
Date/Publication: 2020-09-23 06:30:02 UTC

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Package mlr3proba updated to version 0.2.2 with previous version 0.2.1 dated 2020-08-28

Title: Probabilistic Supervised Learning for 'mlr3'
Description: Provides extensions for probabilistic supervised learning for 'mlr3'. This includes extending the regression task to probabilistic and interval regression, adding a survival task, and other specialized models, predictions, and measures. mlr3extralearners is available from <https://github.com/mlr-org/mlr3extralearners>.
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>), Franz Kiraly [aut], Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Nurul Ain Toha [ctb], Andreas Bender [ctb] (<https://orcid.org/0000-0001-5628-8611>)
Maintainer: Raphael Sonabend <raphael.sonabend.15@ucl.ac.uk>

Diff between mlr3proba versions 0.2.1 dated 2020-08-28 and 0.2.2 dated 2020-09-23

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Package MAPITR updated to version 1.1.1 with previous version 1.0.5 dated 2020-09-17

Title: MArginal ePIstasis Test for Regions
Description: A genetic analysis tool and variance component model for identifying marginal epistasis between pathways and the rest of the genome. 'MAPITR' uses as input a matrix of genotypes, a vector of phenotypes, and a list of pathways. 'MAPITR' then iteratively tests each pathway for epistasis between any variants within the pathway versus any variants remaining in the rest of the genome. 'MAPITR' returns results in the form of p-values for every pathway indicating whether the null model of there being no epistatic interactions between a pathway and the rest of the genome can be rejected.
Author: Michael Turchin [aut, cre] (<https://orcid.org/0000-0003-3569-1529>), Gregory Darnell [aut, ctb] (<https://orcid.org/0000-0003-0425-940X>), Lorin Crawford [aut, ctb] (<https://orcid.org/0000-0003-0178-8242>), Sohini Ramachandran [aut] (<https://orcid.org/0000-0002-9588-7964>), Peter Carbonetto [ctb] (<https://orcid.org/0000-0003-1144-6780>)
Maintainer: Michael Turchin <michael_turchin@brown.edu>

Diff between MAPITR versions 1.0.5 dated 2020-09-17 and 1.1.1 dated 2020-09-23

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Package IRTBEMM updated to version 1.0.5 with previous version 1.0.4 dated 2020-09-17

Title: Family of Bayesian EMM Algorithm for Item Response Models
Description: Applying the family of the Bayesian Expectation-Maximization-Maximization (BEMM) algorithm to estimate: (1) Three parameter logistic (3PL) model proposed by Birnbaum (1968, ISBN:9780201043105); (2) four parameter logistic (4PL) model proposed by Barton & Lord (1981) <doi:10.1002/j.2333-8504.1981.tb01255.x>; (3) one parameter logistic guessing (1PLG) and (4) one parameter logistic ability-based guessing (1PLAG) models proposed by San Martín et al (2006) <doi:10.1177/0146621605282773>. The BEMM family includes (1) the BEMM algorithm for 3PL model proposed by Guo & Zheng (2019) <doi:10.3389/fpsyg.2019.01175>; (2) the BEMM algorithm for 1PLG model and (3) the BEMM algorithm for 1PLAG model proposed by Guo, Wu, Zheng, & Wang (2018) <https:www.ncme.org/news/past-meetings/2018-recap>; (4) the BEMM algorithm for 4PL model proposed by Zhang, Guo, & Zheng (2018) <https:www.ncme.org/news/past-meetings/2018-recap>; and (5) their maximum likelihood estimation versions proposed by Zheng, Meng, Guo, & Liu (2018) <doi:10.3389/fpsyg.2017.02302>. Thus, both Bayesian modal estimates and maximum likelihood estimates are available.
Author: Shaoyang Guo [aut, cre, cph], Chanjin Zheng [aut], Justin L Kern [aut]
Maintainer: Shaoyang Guo <syguo1992@outlook.com>

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New package GMMAT with initial version 1.3.1
Package: GMMAT
Version: 1.3.1
Date: 2020-09-14
Title: Generalized Linear Mixed Model Association Tests
Author: Han Chen, Matthew P. Conomos, Duy T. Pham
Maintainer: Han Chen <Han.Chen.2@uth.tmc.edu>
Description: Perform association tests using generalized linear mixed models (GLMMs) in genome-wide association studies (GWAS) and sequencing association studies. First, GMMAT fits a GLMM with covariate adjustment and random effects to account for population structure and familial or cryptic relatedness. For GWAS, GMMAT performs score tests for each genetic variant as proposed in Chen et al. (2016) <DOI:10.1016/j.ajhg.2016.02.012>. For candidate gene studies, GMMAT can also perform Wald tests to get the effect size estimate for each genetic variant. For rare variant analysis from sequencing association studies, GMMAT performs the variant Set Mixed Model Association Tests (SMMAT) as proposed in Chen et al. (2019) <DOI:10.1016/j.ajhg.2018.12.012>, including the burden test, the sequence kernel association test (SKAT), SKAT-O and an efficient hybrid test of the burden test and SKAT, based on user-defined variant sets.
License: GPL-3
Copyright: See COPYRIGHTS for details.
Imports: Rcpp, SeqArray, SeqVarTools, CompQuadForm, foreach, parallel, Matrix, methods
Suggests: doMC, testthat
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
NeedsCompilation: yes
Depends: R (>= 3.2.0)
Packaged: 2020-09-21 15:50:00 UTC; hchen
Repository: CRAN
Date/Publication: 2020-09-23 06:30:23 UTC

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Package GermaParl updated to version 1.5.2 with previous version 1.5.1 dated 2020-07-27

Title: Download and Augment the Corpus of Plenary Protocols of the German Bundestag
Description: Data package to disseminate the 'GermaParl' corpus of parliamentary debates of the German Bundestag prepared in the 'PolMine Project'. The package includes a small subset of the corpus for demonstration and testing purposes. The package includes functionality to download the full corpus and supplementary data from the open science repository 'Zenodo'.
Author: Andreas Blaette [aut, cre], Christoph Leonhardt [ctb]
Maintainer: Andreas Blaette <andreas.blaette@uni-due.de>

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Package rBiasCorrection updated to version 0.2.3 with previous version 0.2.2 dated 2020-09-22

Title: Correct Bias in DNA Methylation Analyses
Description: Implementation of the algorithms (with minor modifications) to correct bias in quantitative DNA methylation analyses as described by Moskalev et al. (2011) <doi:10.1093/nar/gkr213>.
Author: Lorenz A. Kapsner [cre, aut, cph] (<https://orcid.org/0000-0003-1866-860X>), Evgeny A. Moskalev [aut]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>

Diff between rBiasCorrection versions 0.2.2 dated 2020-09-22 and 0.2.3 dated 2020-09-23

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Package quanteda updated to version 2.1.2 with previous version 2.1.1 dated 2020-07-27

Title: Quantitative Analysis of Textual Data
Description: A fast, flexible, and comprehensive framework for quantitative text analysis in R. Provides functionality for corpus management, creating and manipulating tokens and ngrams, exploring keywords in context, forming and manipulating sparse matrices of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and distances, applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses, and more.
Author: Kenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (<https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (<https://orcid.org/0000-0003-4992-4311>), Paul Nulty [aut] (<https://orcid.org/0000-0002-7214-4666>), Adam Obeng [aut] (<https://orcid.org/0000-0002-2906-4775>), Stefan Müller [aut] (<https://orcid.org/0000-0002-6315-4125>), Akitaka Matsuo [aut] (<https://orcid.org/0000-0002-3323-6330>), Jiong Wei Lua [aut], Jouni Kuha [aut] (<https://orcid.org/0000-0002-1156-8465>), William Lowe [aut] (<https://orcid.org/0000-0002-1549-6163>), Christian Müller [ctb], Lori Young [dtc] (Lexicoder Sentiment Dictionary 2015), Stuart Soroka [dtc] (Lexicoder Sentiment Dictionary 2015), Ian Fellows [cph] (authored wordcloud C source code (modified)), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS)
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

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Package kofdata (with last version 0.1.3.4) was removed from CRAN

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

2020-03-28 0.1.3.4
2019-08-05 0.1.3.3

Permanent link

Tue, 22 Sep 2020

New package ERSA with initial version 0.1.3
Package: ERSA
Type: Package
Title: Exploratory Regression 'Shiny' App
Version: 0.1.3
Date: 2020-9-22
Author: Catherine B. Hurley
Maintainer: Catherine B. Hurley <catherine.hurley@mu.ie>
Description: Constructs a 'shiny' app function with interactive displays for summary and analysis of variance regression tables, and parallel coordinate plots of data and residuals.
License: GPL (>= 2.0)
Encoding: UTF-8
LazyData: true
Imports: shiny, miniUI,RColorBrewer, ggplot2, car, leaps, broom, dplyr, tidyr, purrr, combinat,stats, methods
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-22 19:54:07 UTC; catherine
Repository: CRAN
Date/Publication: 2020-09-22 23:00:02 UTC

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Package tables updated to version 0.9.6 with previous version 0.9.4 dated 2020-08-28

Title: Formula-Driven Table Generation
Description: Computes and displays complex tables of summary statistics. Output may be in LaTeX, HTML, plain text, or an R matrix for further processing.
Author: Duncan Murdoch
Maintainer: Duncan Murdoch <murdoch.duncan@gmail.com>

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Package shinyFeedback updated to version 0.3.0 with previous version 0.2.0 dated 2020-04-29

Title: Display User Feedback in Shiny Apps
Description: Easily display user feedback in Shiny apps.
Author: Andy Merlino [aut, cre], Patrick Howard [aut]
Maintainer: Andy Merlino <andy.merlino@tychobra.com>

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Package rticles updated to version 0.16 with previous version 0.15 dated 2020-08-26

Title: Article Formats for R Markdown
Description: A suite of custom R Markdown formats and templates for authoring journal articles and conference submissions.
Author: JJ Allaire [aut], Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), R Foundation [aut, cph], Hadley Wickham [aut], Journal of Statistical Software [aut, cph], RStudio [cph], Ramnath Vaidyanathan [aut, cph], Association for Computing Machinery [aut, cph], Carl Boettiger [aut, cph], Elsevier [aut, cph], Karl Broman [aut, cph], Kirill Mueller [aut, cph], Bastiaan Quast [aut, cph], Randall Pruim [aut, cph], Ben Marwick [aut, cph], Charlotte Wickham [aut, cph], Oliver Keyes [aut, cph], Miao Yu [aut, cph], Daniel Emaasit [aut, cph], Thierry Onkelinx [aut, cph], Alessandro Gasparini [aut, cph] (<https://orcid.org/0000-0002-8319-7624>), Marc-Andre Desautels [aut, cph], Dominik Leutnant [aut, cph] (<https://orcid.org/0000-0003-3293-2315>), MDPI [aut, cph], Taylor and Francis [aut, cph], Oğuzhan Öğreden [aut] (<https://orcid.org/0000-0002-9949-3348>), Dalton Hance [aut], Daniel Nüst [aut, cph] (<https://orcid.org/0000-0002-0024-5046>), Petter Uvesten [aut, cph], Elio Campitelli [aut, cph] (<https://orcid.org/0000-0002-7742-9230>), John Muschelli [aut, cph] (<https://orcid.org/0000-0001-6469-1750>), Alex Hayes [aut] (<https://orcid.org/0000-0002-4985-5160>), Zhian N. Kamvar [aut, cph] (<https://orcid.org/0000-0003-1458-7108>), Noam Ross [aut, cph] (<https://orcid.org/0000-0002-2136-0000>), Robrecht Cannoodt [aut, cph] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Duncan Luguern [aut], David M. Kaplan [aut, ctb] (<https://orcid.org/0000-0001-6087-359X>, dmkaplan2000), Sebastian Kreutzer [aut] (<https://orcid.org/0000-0002-0734-2199>), Shixiang Wang [aut, ctb] (<https://orcid.org/0000-0001-9855-7357>), Jay Hesselberth [aut, ctb] (<https://orcid.org/0000-0002-6299-179X>), Alfredo Hernández [ctb] (<https://orcid.org/0000-0002-2660-4545>), Christophe Dervieux [aut] (<https://orcid.org/0000-0003-4474-2498>)
Maintainer: Yihui Xie <xie@yihui.name>

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Package leafpop updated to version 0.0.6 with previous version 0.0.5 dated 2019-12-09

Title: Include Tables, Images and Graphs in Leaflet Pop-Ups
Description: Creates 'HTML' strings to embed tables, images or graphs in pop-ups of interactive maps created with packages like 'leaflet' or 'mapview'. Handles local images located on the file system or via remote URL. Handles graphs created with 'lattice' or 'ggplot2' as well as interactive plots created with 'htmlwidgets'.
Author: Tim Appelhans [cre, aut], Florian Detsch [aut]
Maintainer: Tim Appelhans <tim.appelhans@gmail.com>

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Package nat updated to version 1.8.16 with previous version 1.8.14 dated 2020-02-07

Title: NeuroAnatomy Toolbox for Analysis of 3D Image Data
Description: NeuroAnatomy Toolbox (nat) enables analysis and visualisation of 3D biological image data, especially traced neurons. Reads and writes 3D images in NRRD and 'Amira' AmiraMesh formats and reads surfaces in 'Amira' hxsurf format. Traced neurons can be imported from and written to SWC and 'Amira' LineSet and SkeletonGraph formats. These data can then be visualised in 3D via 'rgl', manipulated including applying calculated registrations, e.g. using the 'CMTK' registration suite, and analysed. There is also a simple representation for neurons that have been subjected to 3D skeletonisation but not formally traced; this allows morphological comparison between neurons including searches and clustering (via the 'nat.nblast' extension package).
Author: Gregory Jefferis [aut, cre] (<https://orcid.org/0000-0002-0587-9355>), James Manton [aut] (<https://orcid.org/0000-0001-9260-3156>)
Maintainer: Gregory Jefferis <jefferis@gmail.com>

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Package knitr updated to version 1.30 with previous version 1.29 dated 2020-06-23

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

Diff between knitr versions 1.29 dated 2020-06-23 and 1.30 dated 2020-09-22

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Package future updated to version 1.19.1 with previous version 1.18.0 dated 2020-07-09

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

Diff between future versions 1.18.0 dated 2020-07-09 and 1.19.1 dated 2020-09-22

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More information about future at CRAN
Permanent link

New package gutenbergr with initial version 0.2.0
Package: gutenbergr
Type: Package
Title: Download and Process Public Domain Works from Project Gutenberg
Version: 0.2.0
Authors@R: person("David", "Robinson", email = "admiral.david@gmail.com", role = c("aut", "cre"))
Description: Download and process public domain works in the Project Gutenberg collection <http://www.gutenberg.org/>. Includes metadata for all Project Gutenberg works, so that they can be searched and retrieved.
License: GPL-2
LazyData: TRUE
Maintainer: David Robinson <admiral.david@gmail.com>
URL: https://docs.ropensci.org/gutenbergr/, https://github.com/ropensci/gutenbergr
BugReports: https://github.com/ropensci/gutenbergr/issues
VignetteBuilder: knitr
Depends: R (>= 2.10)
Imports: dplyr, readr, purrr, urltools, stringr, lazyeval
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat, tidytext, ggplot2, tidyr, curl
Language: en-US
NeedsCompilation: no
Packaged: 2020-09-21 20:27:53 UTC; davidrobinson
Author: David Robinson [aut, cre]
Repository: CRAN
Date/Publication: 2020-09-22 17:00:02 UTC

More information about gutenbergr at CRAN
Permanent link

Package withr updated to version 2.3.0 with previous version 2.2.0 dated 2020-04-20

Title: Run Code 'With' Temporarily Modified Global State
Description: A set of functions to run code 'with' safely and temporarily modified global state. Many of these functions were originally a part of the 'devtools' package, this provides a simple package with limited dependencies to provide access to these functions.
Author: Jim Hester [aut, cre], Kirill Müller [aut], Kevin Ushey [aut], Hadley Wickham [aut], Winston Chang [aut], Jennifer Bryan [ctb], Richard Cotton [ctb], RStudio [cph]
Maintainer: Jim Hester <james.f.hester@gmail.com>

Diff between withr versions 2.2.0 dated 2020-04-20 and 2.3.0 dated 2020-09-22

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Package TreeTools updated to version 1.3.0 with previous version 1.2.0 dated 2020-08-03

Title: Create, Modify and Analyse Phylogenetic Trees
Description: Efficient implementations of functions for the creation, modification and analysis of phylogenetic trees. Applications include: generation of trees with specified shapes; analysis of tree shape; rooting of trees and extraction of subtrees; calculation and depiction of node support; calculation of ancestor-descendant relationships; import and export of trees from Newick, Nexus (Maddison et al. 1997) <doi:10.1093/sysbio/46.4.590>, and TNT <http://www.lillo.org.ar/phylogeny/tnt/> formats; and analysis of splits and cladistic information.
Author: Martin R. Smith [aut, cre, cph] (<https://orcid.org/0000-0001-5660-1727>), Emmanuel Paradis [cph] (<https://orcid.org/0000-0003-3092-2199>)
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

Diff between TreeTools versions 1.2.0 dated 2020-08-03 and 1.3.0 dated 2020-09-22

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More information about TreeTools at CRAN
Permanent link

Package simTool updated to version 1.1.7 with previous version 1.1.6 dated 2020-05-17

Title: Conduct Simulation Studies with a Minimal Amount of Source Code
Description: Tool for statistical simulations that have two components. One component generates the data and the other one analyzes the data. The main aims of the package are the reduction of the administrative source code (mainly loops and management code for the results) and a simple applicability of the package that allows the user to quickly learn how to work with it. Parallel computing is also supported. Finally, convenient functions are provided to summarize the simulation results.
Author: Marsel Scheer [aut, cre]
Maintainer: Marsel Scheer <scheer@freescience.de>

Diff between simTool versions 1.1.6 dated 2020-05-17 and 1.1.7 dated 2020-09-22

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Package Sim.DiffProc updated to version 4.7 with previous version 4.6 dated 2020-05-04

Title: Simulation of Diffusion Processes
Description: It provides users with a wide range of tools to simulate, estimate, analyze, and visualize the dynamics of stochastic differential systems in both forms Ito and Stratonovich. Statistical analysis with parallel Monte Carlo and moment equations methods of SDE's. Enabled many searchers in different domains to use these equations to modeling practical problems in financial and actuarial modeling and other areas of application, e.g., modeling and simulate of first passage time problem in shallow water using the attractive center (Boukhetala K, 1996) ISBN:1-56252-342-2.
Author: Arsalane Chouaib Guidoum [cre, aut], Kamal Boukhetala [aut]
Maintainer: Arsalane Chouaib Guidoum <acguidoum@usthb.dz>

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Package procmaps updated to version 0.0.3 with previous version 0.0.2 dated 2020-09-20

Title: Portable Address Space Mapping
Description: Portable '/proc/self/maps' as a data frame. Determine which library or other region is mapped to a specific address of a process. -- R packages can contain native code, compiled to shared libraries at build or installation time. When loaded, each shared library occupies a portion of the address space of the main process. When only a machine instruction pointer is available (e.g. from a backtrace during error inspection or profiling), the address space map determines which library this instruction pointer corresponds to.
Author: Kirill Müller [aut, cre] (<https://orcid.org/0000-0002-1416-3412>), R Consortium [fnd], Kostya Serebryany [ctb] (Bundled gperftools library), Sanjay Ghemawat [ctb] (Bundled gperftools library), Craig Silverstein [ctb] (Bundled gperftools library), Google Inc. [cph] (Bundled gperftools library)
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

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Package pcalg updated to version 2.6-12 with previous version 2.6-11 dated 2020-08-16

Title: Methods for Graphical Models and Causal Inference
Description: Functions for causal structure learning and causal inference using graphical models. The main algorithms for causal structure learning are PC (for observational data without hidden variables), FCI and RFCI (for observational data with hidden variables), and GIES (for a mix of data from observational studies (i.e. observational data) and data from experiments involving interventions (i.e. interventional data) without hidden variables). For causal inference the IDA algorithm, the Generalized Backdoor Criterion (GBC), the Generalized Adjustment Criterion (GAC) and some related functions are implemented. Functions for incorporating background knowledge are provided.
Author: Markus Kalisch [aut, cre], Alain Hauser [aut], Martin Maechler [aut], Diego Colombo [ctb], Doris Entner [ctb], Patrik Hoyer [ctb], Antti Hyttinen [ctb], Jonas Peters [ctb], Nicoletta Andri [ctb], Emilija Perkovic [ctb], Preetam Nandy [ctb], Philipp Ruetimann [ctb], Daniel Stekhoven [ctb], Manuel Schuerch [ctb], Marco Eigenmann [ctb]
Maintainer: Markus Kalisch <kalisch@stat.math.ethz.ch>

Diff between pcalg versions 2.6-11 dated 2020-08-16 and 2.6-12 dated 2020-09-22

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Package mlr3fselect updated to version 0.3.0 with previous version 0.2.1 dated 2020-09-10

Title: Feature Selection for 'mlr3'
Description: Implements methods for feature selection with 'mlr3', e.g. random search and sequential selection. Various termination criteria can be set and combined. The class 'AutoFSelect' provides a convenient way to perform nested resampling in combination with 'mlr3'.
Author: Marc Becker [aut, cre] (<https://orcid.org/0000-0002-8115-0400>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>)
Maintainer: Marc Becker <marcbecker@posteo.de>

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Package DRomics updated to version 2.1-2 with previous version 2.0-1 dated 2019-09-16

Title: Dose Response for Omics
Description: Several functions are provided for dose-response (or concentration-response) characterization from omics data. 'DRomics' is especially dedicated to omics data obtained using a typical dose-response design, favoring a great number of tested doses (or concentrations) rather than a great number of replicates (no need of three replicates). 'DRomics' provides functions 1) to check, normalize and or transform data, 2) to select monotonic or biphasic significantly responding items (e.g. probes, metabolites), 3) to choose the best-fit model among a predefined family of monotonic and biphasic models to describe each selected item, 4) to derive a benchmark dose or concentration and a typology of response from each fitted curve. In the available version data are supposed to be single-channel microarray data in log2, RNAseq data in raw counts, or already pretreated metabolomic data in log scale. In order to link responses across biological levels based on a common method, 'DRomics' also handles apical data as long as they are continuous and follow a Gaussian distribution for each dose or concentration, with a common standard error. For further details see Larras et al (2018) <DOI:10.1021/acs.est.8b04752> at <https://hal.archives-ouvertes.fr/hal-02309919>.
Author: Marie-Laure Delignette-Muller [aut], Elise Billoir [aut], Floriane Larras [ctb], Aurelie Siberchicot [aut, cre]
Maintainer: Aurelie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>

Diff between DRomics versions 2.0-1 dated 2019-09-16 and 2.1-2 dated 2020-09-22

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New package BiasCorrector with initial version 0.1.2
Package: BiasCorrector
Title: A GUI to Correct Measurement Bias in DNA Methylation Analyses
Version: 0.1.2
Date: 2020-09-22
Authors@R: c(person(given = "Lorenz A.", family = "Kapsner", role = c("cre", "aut", "cph"), email = "lorenz.kapsner@gmail.com", comment = c(ORCID = "0000-0003-1866-860X")), person(given = "Evgeny A.", family = "Moskalev", role = "aut"))
Description: A GUI to correct measurement bias in DNA methylation analyses. The 'BiasCorrector' package just wraps the functions implemented in the 'R' package 'rBiasCorrection' into a shiny web application in order to make them more easily accessible.
License: GPL-3
URL: https://github.com/kapsner/BiasCorrector
BugReports: https://github.com/kapsner/BiasCorrector/issues
Depends: R (>= 2.10)
Imports: data.table, DT, magrittr, rBiasCorrection, shiny, shinydashboard, shinyjs
Suggests: lintr, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-22 11:51:59 UTC; user
Author: Lorenz A. Kapsner [cre, aut, cph] (<https://orcid.org/0000-0003-1866-860X>), Evgeny A. Moskalev [aut]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-22 15:20:21 UTC

More information about BiasCorrector at CRAN
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Package azuremlsdk updated to version 1.10.0 with previous version 0.6.85 dated 2020-02-05

Title: Interface to the 'Azure Machine Learning' 'SDK'
Description: Interface to the 'Azure Machine Learning' Software Development Kit ('SDK'). Data scientists can use the 'SDK' to train, deploy, automate, and manage machine learning models on the 'Azure Machine Learning' service. To learn more about 'Azure Machine Learning' visit the website: <https://docs.microsoft.com/en-us/azure/machine-learning/service/overview-what-is-azure-ml>.
Author: Diondra Peck [cre, aut], Minna Xiao [aut], AzureML R SDK Team [ctb], Microsoft [cph, fnd], Google Inc. [cph] (Examples and Tutorials), The TensorFlow Authors [cph] (Examples and Tutorials), RStudio Inc. [cph] (Examples and Tutorials)
Maintainer: Diondra Peck <Diondra.Peck@microsoft.com>

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 azuremlsdk-1.10.0/azuremlsdk/man/cancel_run.Rd                                                           |   34 
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 azuremlsdk-1.10.0/azuremlsdk/man/delete_model.Rd                                                         |   38 
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Permanent link

Package sigr updated to version 1.1.1 with previous version 1.1.0 dated 2020-09-15

Title: Succinct and Correct Statistical Summaries for Reports
Description: Succinctly and correctly format statistical summaries of various models and tests (F-test, Chi-Sq-test, Fisher-test, T-test, and rank-significance). The main purpose is unified reporting of experimental results, working around issue such as the difficulty of extracting model summary facts (such as with 'lm'/'glm'). This package also includes empirical tests, such as bootstrap estimates.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between sigr versions 1.1.0 dated 2020-09-15 and 1.1.1 dated 2020-09-22

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 NEWS.md                                    |    6 
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Permanent link

Package neonstore updated to version 0.2.3 with previous version 0.2.2 dated 2020-09-08

Title: NEON Data Store
Description: The National Ecological Observatory Network (NEON) provides access to its numerous data products through its REST API, <https://data.neonscience.org/data-api/>. This package provides a high-level user interface for downloading and storing NEON data products. While each of NEON data products consist of hundreds or thousands of individual files. Unlike 'neonUtilities', this package will avoid repeated downloading, provides persistent storage, and improves performance. This package does not provide expose interactions with the individual low-level NEON API endpoints.
Author: Carl Boettiger [aut, cre] (<https://orcid.org/0000-0002-1642-628X>), Quinn Thomas [aut] (<https://orcid.org/0000-0003-1282-7825>), Christine Laney [aut] (<https://orcid.org/0000-0002-4944-2083>), Claire Lunch [aut] (<https://orcid.org/0000-0001-8753-6593>)
Maintainer: Carl Boettiger <cboettig@gmail.com>

Diff between neonstore versions 0.2.2 dated 2020-09-08 and 0.2.3 dated 2020-09-22

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 tests/testthat/test-store.R      |   24 +++++++++++++++++++++---
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More information about neonstore at CRAN
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Package jsTreeR updated to version 1.0.0 with previous version 0.1.0 dated 2020-08-31

Title: A Wrapper of the JavaScript Library 'jsTree'
Description: Creates interactive trees that can be included in 'Shiny' apps and R markdown documents. A tree allows to represent hierarchical data (e.g. the contents of a directory). Similar to the 'shinyTree' package but offers more features and options, such as the grid extension, restricting the drag-and-drop behavior, and settings for the search functionality. It is possible to attach some data to the nodes of a tree and then to get these data in 'Shiny' when a node is selected. Also provides a 'Shiny' gadget allowing to manipulate one or more folders.
Author: Stéphane Laurent [aut, cre], jQuery contributors [ctb, cph] (jQuery), Ivan Bozhanov [ctb, cph] (jsTree), Vedran Opacic [ctb, cph] (jsTree bootstrap theme), Avi Deitcher [ctb, cph] (jsTreeGrid), Terence Eden [ctb, cph] (SuperTinyIcons)
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>

Diff between jsTreeR versions 0.1.0 dated 2020-08-31 and 1.0.0 dated 2020-09-22

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Permanent link

Package LSX updated to version 0.9.2 with previous version 0.9.1 dated 2020-09-14

Title: Model for Semisupervised Text Analysis Based on Word Embeddings
Description: A word embeddings-based semisupervised models for document scaling Watanabe (2017) <doi:10.1177/0267323117695735>. LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove).
Author: Kohei Watanabe [aut, cre, cph]
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

Diff between LSX versions 0.9.1 dated 2020-09-14 and 0.9.2 dated 2020-09-22

 DESCRIPTION                     |   12 +++----
 MD5                             |   10 ++---
 NEWS.md                         |    8 ++++
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 6 files changed, 58 insertions(+), 50 deletions(-)

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Package SWIM updated to version 0.2.2 with previous version 0.2.1 dated 2020-05-22

Title: Scenario Weights for Importance Measurement
Description: An efficient sensitivity analysis for stochastic models based on Monte Carlo samples. Provides weights on simulated scenarios from a stochastic model, such that stressed random variables fulfil given probabilistic constraints (e.g. specified values for risk measures), under the new scenario weights. Scenario weights are selected by constrained minimisation of the relative entropy to the baseline model. The 'SWIM' package is based on Pesenti S.M, Millossovich P., Tsanakas A. (2019) "Reverse Sensitivity Testing: What does it take to break the model", <openaccess.city.ac.uk/id/eprint/18896/>.
Author: Silvana M. Pesenti [aut, cre], Alberto Bettini [aut], Pietro Millossovich [aut], Andreas Tsanakas [aut]
Maintainer: Silvana M. Pesenti <swimpackage@gmail.com>

Diff between SWIM versions 0.2.1 dated 2020-05-22 and 0.2.2 dated 2020-09-22

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Package SpatialPack updated to version 0.3-8196 with previous version 0.3-819 dated 2020-06-21

Title: Tools for Assessment the Association Between Two Spatial Processes
Description: Tools to assess the association between two spatial processes. Currently, several methodologies are implemented: A modified t-test to perform hypothesis testing about the independence between the processes, a suitable nonparametric correlation coefficient, the codispersion coefficient, and an F test for assessing the multiple correlation between one spatial process and several others. Functions for image processing and computing the spatial association between images are also provided.
Author: Felipe Osorio [aut, cre] (<https://orcid.org/0000-0002-4675-5201>), Ronny Vallejos [aut] (<https://orcid.org/0000-0001-5519-0946>), Francisco Cuevas [ctb], Diego Mancilla [ctb]
Maintainer: Felipe Osorio <felipe.osorios@usm.cl>

Diff between SpatialPack versions 0.3-819 dated 2020-06-21 and 0.3-8196 dated 2020-09-22

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Package SpatialExtremes updated to version 2.0-9 with previous version 2.0-8 dated 2020-03-09

Title: Modelling Spatial Extremes
Description: Tools for the statistical modelling of spatial extremes using max-stable processes, copula or Bayesian hierarchical models. More precisely, this package allows (conditional) simulations from various parametric max-stable models, analysis of the extremal spatial dependence, the fitting of such processes using composite likelihoods or least square (simple max-stable processes only), model checking and selection and prediction. Other approaches (although not completely in agreement with the extreme value theory) are available such as the use of (spatial) copula and Bayesian hierarchical models assuming the so-called conditional assumptions. The latter approaches is handled through an (efficient) Gibbs sampler. Some key references: Davison et al. (2012) <doi:10.1214/11-STS376>, Padoan et al. (2010) <doi:10.1198/jasa.2009.tm08577>, Dombry et al. (2013) <doi:10.1093/biomet/ass067>.
Author: Mathieu Ribatet [aut, cre], Richard Singleton [ctb], R Core team [ctb]
Maintainer: Mathieu Ribatet <mathieu.ribatet@ec-nantes.fr>

Diff between SpatialExtremes versions 2.0-8 dated 2020-03-09 and 2.0-9 dated 2020-09-22

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Package smoothedLasso updated to version 1.4 with previous version 1.3 dated 2020-06-14

Title: A Framework to Smooth L1 Penalized Regression Operators using Nesterov Smoothing
Description: We provide full functionality to smooth L1 penalized regression operators and to compute regression estimates thereof. For this, the objective function of a user-specified regression operator is first smoothed using Nesterov smoothing (see Y. Nesterov (2005) <doi:10.1007/s10107-004-0552-5>), resulting in a modified objective function with explicit gradients everywhere. The smoothed objective function and its gradient are minimized via BFGS, and the obtained minimizer is returned. Using Nesterov smoothing, the smoothed objective function can be made arbitrarily close to the original (unsmoothed) one. In particular, the Nesterov approach has the advantage that it comes with explicit accuracy bounds, both on the L1/L2 difference of the unsmoothed to the smoothed objective functions as well as on their respective minimizers (see G. Hahn, S.M. Lutz, N. Laha, C. Lange (2020) <doi:10.1101/2020.09.17.301788>). A progressive smoothing approach is provided which iteratively smoothes the objective function, resulting in more stable regression estimates.
Author: Georg Hahn [aut,cre], Sharon M. Lutz [ctb], Nilanjana Laha [ctb], Christoph Lange [ctb]
Maintainer: Georg Hahn <ghahn@hsph.harvard.edu>

Diff between smoothedLasso versions 1.3 dated 2020-06-14 and 1.4 dated 2020-09-22

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Package rasciidoc updated to version 2.2.0 with previous version 2.1.3 dated 2020-08-16

Title: Create Reports Using R and 'asciidoc'
Description: Inspired by Karl Broman`s reader on using 'knitr' with 'asciidoc' (<http://kbroman.org/knitr_knutshell/pages/asciidoc.html>), this is merely a wrapper to 'knitr' and 'asciidoc'.
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>

Diff between rasciidoc versions 2.1.3 dated 2020-08-16 and 2.2.0 dated 2020-09-22

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 4 files changed, 49 insertions(+), 13 deletions(-)

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Package image.textlinedetector updated to version 0.1.2 with previous version 0.1.1 dated 2020-09-21

Title: Segment Images in Text Lines and Words
Description: Find text lines in scanned images and segment the lines into words. Includes implementations of the paper 'Novel A* Path Planning Algorithm for Line Segmentation of Handwritten Documents' by Surinta O. et al (2014) <doi:10.1109/ICFHR.2014.37> available at <https://github.com/smeucci/LineSegm>, an implementation of 'A Statistical approach to line segmentation in handwritten documents' by Arivazhagan M. et al (2007) <doi:10.1117/12.704538>, and a wrapper for an image segmentation technique to detect words in text lines as described in the paper 'Scale Space Technique for Word Segmentation in Handwritten Documents' by Manmatha R. and Srimal N. (1999) paper at <doi:10.1007/3-540-48236-9_3>, wrapper for code available at <https://github.com/arthurflor23/text-segmentation>.
Author: Jan Wijffels [aut, cre, cph] (R wrapper), Vrije Universiteit Brussel - DIGI: Brussels Platform for Digital Humanities [cph] (R wrapper), Jeroen Ooms [ctb, cph] (More details in LICENSE.note file), Arthur Flôr [ctb, cph] (More details in LICENSE.note file), Saverio Meucci [ctb, cph] (More details in LICENSE.note file), Yeara Kozlov [ctb, cph] (More details in LICENSE.note file), Tino Weinkauf [ctb, cph] (More details in LICENSE.note file)
Maintainer: Jan Wijffels <jan.wijffels@vub.be>

Diff between image.textlinedetector versions 0.1.1 dated 2020-09-21 and 0.1.2 dated 2020-09-22

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 4 files changed, 11 insertions(+), 7 deletions(-)

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Package emba updated to version 0.1.7 with previous version 0.1.6 dated 2020-07-08

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

Diff between emba versions 0.1.6 dated 2020-07-08 and 0.1.7 dated 2020-09-22

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 11 files changed, 60 insertions(+), 48 deletions(-)

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New package usemodels with initial version 0.0.1
Package: usemodels
Title: Boilerplate Code for 'Tidymodels' Analyses
Version: 0.0.1
Authors@R: c( person( given = "Max", family = "Kuhn", email = "max@rstudio.com", comment = c(ORCID = "0000-0003-2402-136X"), role = c("aut", "cre") ), person("RStudio", role = "cph"))
Description: Code snippets to fit models using the tidymodels framework can be easily created for a given data set.
URL: https://tidymodels.github.io/usemodels/, https://github.com/tidymodels/usemodels
BugReports: https://github.com/tidymodels/usemodels/issues
License: MIT + file LICENSE
Suggests: testthat, spelling, covr, palmerpenguins
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Language: en-US
Imports: tune (>= 0.1.1), cli, recipes, rlang, purrr, dplyr, tidyr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2020-09-15 02:15:15 UTC; max
Author: Max Kuhn [aut, cre] (<https://orcid.org/0000-0003-2402-136X>), RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>
Repository: CRAN
Date/Publication: 2020-09-22 09:30:03 UTC

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New package unnest with initial version 0.0.2
Package: unnest
Title: Unnest Hierarchical Data Structures
Version: 0.0.2
Authors@R: person(given = "Vitalie", family = "Spinu", role = c("aut", "cre"), email = "spinuvit@gmail.com")
Description: Fast flattening of hierarchical data structures (e.g. JSON and XML documents) into data.frames with a flexible spec language.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: data.table, dplyr, knitr, repurrrsive, rmarkdown, roxygen2, testthat, tibble, tidyr
VignetteBuilder: knitr
URL: https://github.com/vspinu/unnest
BugReports: https://github.com/vspinu/unnest/issues
NeedsCompilation: yes
Packaged: 2020-09-15 09:29:25 UTC; vspinu
Author: Vitalie Spinu [aut, cre]
Maintainer: Vitalie Spinu <spinuvit@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-22 09:40:02 UTC

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New package Riemann with initial version 0.1.0
Package: Riemann
Type: Package
Title: Learning with Data on Riemannian Manifolds
Version: 0.1.0
Authors@R: c(person("Kisung", "You", role = c("aut", "cre"), email = "kyoustat@gmail.com",comment=c(ORCID="0000-0002-8584-459X")))
Description: We provide a variety of algorithms for manifold-valued data, including Fréchet summaries, hypothesis testing, clustering, visualization, and other learning tasks. See Bhattacharya and Bhattacharya (2012) <doi:10.1017/CBO9781139094764> for general exposition to statistics on manifolds.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.5), Rdpack, RiemBase, maotai, stats, utils
Encoding: UTF-8
URL: http://kyoustat.com/Riemann/
BugReports: https://github.com/kyoustat/Riemann/issues
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
RdMacros: Rdpack
NeedsCompilation: yes
Packaged: 2020-09-15 11:49:51 UTC; kisung
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyoustat@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-22 09:40:06 UTC

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New package MonteCarloSEM with initial version 0.0.1
Type: Package
Package: MonteCarloSEM
Title: Monte Carlo Data Simulation Package
Version: 0.0.1
Authors@R: person(given = "Fatih", family = "Orcan", role = c("aut", "cre"), email = "fatihorcan84@gmail.com", comment = c(ORCID = "0000-0003-1727-0456"))
Description: Monte Carlo simulation allows to test different conditions given to the correct structural equation models. This package runs Monte Carlo simulations under different conditions (such as sample size or normality of data). Within the package data sets can be simulated and run based on the given model. First, continuous and normal data sets are generated based on the given model. Later Fleishman's power method (1978) <DOI:10.1007/BF02293811> is used to add non-normality if exists. When data generation is completed (or when generated data sets are given) model test can also be run.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.1.1
Imports: Matrix, stats, utils, lavaan
Copyright: Fatih Orcan, Trabzon University, Turkey
LazyData: true
NeedsCompilation: no
Packaged: 2020-09-15 17:26:50 UTC; FO
Author: Fatih Orcan [aut, cre] (<https://orcid.org/0000-0003-1727-0456>)
Maintainer: Fatih Orcan <fatihorcan84@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-22 09:50:12 UTC

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New package LifeInsuranceContracts with initial version 0.0.2
Package: LifeInsuranceContracts
Type: Package
Version: 0.0.2
Date: 2020-09-14
Title: Framework for Traditional Life Insurance Contracts
Description: R6 classes to model traditional life insurance contracts like annuities, whole life insurances or endowments. Such life insurance contracts provide a guaranteed interest and are not directly linked to the performance of a particular investment vehicle. However, they typically provide (discretionary) profit participation. This package provides a framework to model such contracts in a very generic (cash-flow-based) way and includes modelling profit participation schemes, dynamic increases or more general contract layers, as well as contract changes (like sum increases or premium waivers). All relevant quantities like premium decomposition, reserves and benefits over the whole contract period are calculated and potentially exported to excel. Mortalities are given using the 'MortalityTables' package.
Authors@R: c(person("Reinhold", "Kainhofer", role=c("aut", "cre"), email="reinhold@kainhofer.com"))
Author: Reinhold Kainhofer [aut, cre]
Maintainer: Reinhold Kainhofer <reinhold@kainhofer.com>
Encoding: UTF-8
Imports: R6, MortalityTables, objectProperties, lubridate, openxlsx, dplyr, scales, abind, stringr, methods, rlang
License: GPL (>= 2)
RoxygenNote: 7.1.1
Collate: 'HelperFunctions.R' 'InsuranceParameters.R' 'ProfitParticipation_Functions.R' 'ProfitParticipation.R' 'InsuranceTarif.R' 'InsuranceContract.R' 'addDataTableWorksheet.R' 'contractGrid.R' 'exportInsuranceContract_xlsx.R' 'showVmGlgExamples.R' 'exportInsuranceContractExample.R'
Suggests: knitr, rmarkdown, pander, kableExtra, magrittr, tibble, testthat
VignetteBuilder: knitr
URL: https://gitlab.open-tools.net/R/r-life-insurance-contracts
BugReports: https://gitlab.open-tools.net/R/r-life-insurance-contracts/-/issues
NeedsCompilation: no
Packaged: 2020-09-14 21:45:38 UTC; reinhold
Repository: CRAN
Date/Publication: 2020-09-22 09:10:02 UTC

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Package incidence2 updated to version 0.2.0 with previous version 0.1.0 dated 2020-09-07

Title: Compute, Handle and Plot Incidence of Dated Events
Description: Provides functions and classes to compute, handle and visualise incidence from dated events for a defined time interval. Dates can be provided in various standard formats. The class 'incidence2' is used to store computed incidence and can be easily manipulated, subsetted, and plotted. This package is part of the RECON (<https://www.repidemicsconsortium.org/>) toolkit for outbreak analysis.
Author: Tim Taylor [aut, cre] (<https://orcid.org/0000-0002-8587-7113>), Thibaut Jombart [aut], Zhian N. Kamvar [aut] (<https://orcid.org/0000-0003-1458-7108>), Rich FitzJohn [aut], Jun Cai [ctb] (<https://orcid.org/0000-0001-9495-1226>), Sangeeta Bhatia [ctb], Jakob Schumacher [ctb], Juliet R.C. Pulliam [ctb] (<https://orcid.org/0000-0003-3314-8223>)
Maintainer: Tim Taylor <tim.taylor@hiddenelephants.co.uk>

Diff between incidence2 versions 0.1.0 dated 2020-09-07 and 0.2.0 dated 2020-09-22

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 build/vignette.rds                        |binary
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 tests/testthat/test-incidence.R           |    9 ++++++
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 21 files changed, 171 insertions(+), 128 deletions(-)

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New package gauseR with initial version 1.0
Package: gauseR
Title: Lotka-Volterra Models for Gause's 'Struggle for Existence'
Version: 1.0
Authors@R: c(person("Adam", "Clark", role = c("aut", "cre"), email = c("adam.tclark@gmail.com"), comment = c(ORCID = "0000-0002-8843-3278")), person("Lina", "Mühlbauer", role = c("aut")), person("Maximilienne", "Schulze", role = c("aut")))
Description: A collection of tools and data for analyzing the Gause microcosm experiments, and for fitting Lotka-Volterra models to time series data. Includes methods for fitting single-species logistic growth, and multi-species interaction models, e.g. of competition, predator/prey relationships, or mutualism. See documentation for individual functions for examples. In general, see the lv_optim() function for examples of how to fit parameter values in multi-species systems. Note that the general methods applied here, as well as the form of the differential equations that we use, are described in detail in the Quantitative Ecology textbook by Lehman et al., available at <http://hdl.handle.net/11299/204551>, and in Lina K. Mühlbauer, Maximilienne Schulze, W. Stanley Harpole, and Adam T. Clark. 'gauseR': Simple methods for fitting Lotka-Volterra models describing Gause's 'Struggle for Existence' in the journal Ecology and Evolution.
Imports: deSolve, stats, graphics
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-15 13:55:51 UTC; adamt
Author: Adam Clark [aut, cre] (<https://orcid.org/0000-0002-8843-3278>), Lina Mühlbauer [aut], Maximilienne Schulze [aut]
Maintainer: Adam Clark <adam.tclark@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-22 09:50:07 UTC

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New package cat2cat with initial version 0.1.3
Package: cat2cat
Title: Mapping of a Categorical Variable in a Panel Dataset
Version: 0.1.3
Authors@R: person("Maciej", "Nasinski", email = "nasinski.maciej@gmail.com", role = c("aut", "cre"))
Maintainer: Maciej Nasinski <nasinski.maciej@gmail.com>
Description: There are offered automatic methods to map a categorical variable according to a specific encoding across different time points. The main rule is to replicate the observation if it could be assign to a few categories. Then using simple frequencies or statistical methods to approximate probabilities of being assign to each of them. This algorithm was invented and implemented in the paper by Nasinski, Majchrowska and Broniatowska (2020) <doi:10.24425/cejeme.2020.134747>).
Depends: R (>= 3.6)
License: GPL (>= 2)
URL: https://github.com/Polkas/cat2cat
BugReports: https://github.com/Polkas/cat2cat/issues
Encoding: UTF-8
Imports: methods, rlang, caret, progress, magrittr, randomForest, MASS, tidyr, dplyr, data.table
Suggests: knitr, rmarkdown, pacman, testthat
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-09-15 17:55:13 UTC; maciej
Author: Maciej Nasinski [aut, cre]
Repository: CRAN
Date/Publication: 2020-09-22 10:00:02 UTC

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New package BayesianLaterality with initial version 0.1.0
Package: BayesianLaterality
Type: Package
Title: Predict Brain Asymmetry Based on Handedness and Dichotic Listening
Version: 0.1.0
Author: Oystein Sorensen
Maintainer: Oystein Sorensen <oystein.sorensen.1985@gmail.com>
Description: Functional differences between the cerebral hemispheres are a fundamental characteristic of the human brain. Researchers interested in studying these differences often infer underlying hemispheric dominance for a certain function (e.g., language) from laterality indices calculated from observed performance or brain activation measures . However, any inference from observed measures to latent (unobserved) classes has to consider the prior probability of class membership in the population. The provided functions implement a Bayesian model for predicting hemispheric dominance from observed laterality indices (Sorensen and Westerhausen, Laterality: Asymmetries of Body, Brain and Cognition, 2020, <doi:10.1080/1357650X.2020.1769124>).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: dplyr (>= 1.0.2), purrr (>= 0.3.4), rlang (>= 0.4.7), tidyr (>= 1.1.2), tmvtnorm (>= 1.4-10), Rdpack
Suggests: roxygen2, testthat (>= 2.1.0)
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2020-09-15 05:09:29 UTC; oyss
Repository: CRAN
Date/Publication: 2020-09-22 09:30:07 UTC

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New package tipitaka with initial version 0.1.0
Package: tipitaka
Type: Package
Title: A Package for Analyzing the Pali Canon
Version: 0.1.0
Authors@R: person(given = "Dan", family = "Zigmond", role = c("aut", "cre"), email = "djz@shmonk.com")
Description: Provides access to the complete Pali Canon, or Tipitaka, the canonical scripture for Theravadin Buddhists worldwide.
License: CC0
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: stringr, dplyr, magrittr, stringi
NeedsCompilation: no
Packaged: 2020-09-13 22:42:30 UTC; danzigmond
Author: Dan Zigmond [aut, cre]
Maintainer: Dan Zigmond <djz@shmonk.com>
Repository: CRAN
Date/Publication: 2020-09-22 08:30:03 UTC

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New package testComplexity with initial version 0.1.0
Package: testComplexity
Title: Asymptotic Complexity Testing Framework
Version: 0.1.0
Author: Anirban Chetia <bloodraven166@gmail.com>
Maintainer: Anirban Cheta <bloodraven166@gmail.com>
Description: It classifies the asymptotic time/memory complexity class for an algorithm/function through the complexity classifiers, with data frames returned by the quantifiers. The data frames can be passed onto the plotting functions for obtaining a visual description of the benchmarks against data sizes if the user intends to diagnose the trend via the traditional method. For testing the algorithm against an expected time complexity class, the user can directly use the expect functions. Please check <https://anirban166.github.io/testComplexity/articles/testComplexity> to get started.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
URL: https://github.com/Anirban166/testComplexity
BugReports: https://github.com/Anirban166/testComplexity/issues
VignetteBuilder: knitr
Imports: boot, utils, microbenchmark, bench, ggplot2, stats, testthat (>= 2.1.0)
Suggests: covr, knitr, rmarkdown, PeakSegDP, PeakSegOptimal
NeedsCompilation: no
Packaged: 2020-09-14 05:21:00 UTC; HP
Repository: CRAN
Date/Publication: 2020-09-22 08:30:08 UTC

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New package SDCNway with initial version 1.0.0
Version: 1.0.0
Date: 2020-08-19
Title: Tools to Evaluate Disclosure Risk
Authors@R: c(person(given = "John", family = "Riddles", role = c("aut", "cre"), email = "JohnRiddles@westat.com"), person("Westat", role = "cph"))
Maintainer: John Riddles <JohnRiddles@westat.com>
Depends: R (>= 3.6.0), Rdpack
Imports: methods, plyr (>= 1.8.5), dplyr (>= 0.8.4), ggplot2 (>= 3.2.1), MASS (>= 3.6.0)
RdMacros: Rdpack
Description: Tools for calculating disclosure risk measures, including record-level measures primarily using exhaustive tabulation, as well as file-level measures using a loglinear model. Funded by the National Center for Education Statistics. See El Emam (2011) <doi:10.1186/gm239> for a description of risk measures.
Note: This publication was prepared for NCES under Contract No. ED-IES-12-D-0009/0005 with Sanametrix and Westat. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. Government.
Package: SDCNway
License: GPL-2
Encoding: UTF-8
LazyData: true
ByteCompile: true
NeedsCompilation: no
RoxygenNote: 7.1.0
Packaged: 2020-09-08 14:04:48 UTC; riddles_j
Author: John Riddles [aut, cre], Westat [cph]
Repository: CRAN
Date/Publication: 2020-09-22 08:40:07 UTC

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New package sanic with initial version 0.0.1
Package: sanic
Type: Package
Title: Solving Ax = b Nimbly in C++
Version: 0.0.1
Date: 2020-09-04
Authors@R: c(person("Nikolas", "Kuschnig", role = c("aut", "cre"), email = "nikolas.kuschnig@wu.ac.at", comment = c(ORCID = "0000-0002-6642-2543")))
Author: Nikolas Kuschnig [aut, cre] (<https://orcid.org/0000-0002-6642-2543>)
Maintainer: Nikolas Kuschnig <nikolas.kuschnig@wu.ac.at>
Description: Routines for solving large systems of linear equations in R. Direct and iterative solvers from the Eigen C++ library are made available. Solvers include Cholesky, LU, QR, and Krylov subspace methods (Conjugate Gradient, BiCGSTAB). Both dense and sparse problems are supported.
URL: https://github.com/nk027/sanic
BugReports: https://github.com/nk027/sanic/issues
Depends: R (>= 3.3.0)
Imports: Rcpp (>= 1.0.5), Matrix, methods
License: GPL-3
Encoding: UTF-8
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-09-14 09:39:36 UTC; nikolas
Repository: CRAN
Date/Publication: 2020-09-22 08:40:03 UTC

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New package rumidas with initial version 0.1.0
Package: rumidas
Title: Univariate GARCH-MIDAS, Double-Asymmetric GARCH-MIDAS and MEM-MIDAS
Version: 0.1.0
Authors@R: person("Vincenzo", "Candila", email="vincenzo.candila@uniroma1.it", role=c("aut", "cre"))
Description: Adds the MIxing Data Sampling (MIDAS, Ghysels et al. (2007) <doi:10.1080/07474930600972467>) components within the GARCH (Engle et al. (2013) <doi:10.1162/REST_a_00300>) and MEM (Engle (2002) <doi:10.1002/jae.683>) frameworks, with the aim of predicting the volatility with additional low-frequency (that is, MIDAS) terms. The estimation takes place through simple functions, which provide in-sample and (if present) and out-of-sample evaluations. 'rumidas' also offers a summary tool, which synthesizes the main information of the estimated model. Finally, an option to generate one-step-ahead volatility forecasts automatically divides the whole period into a training and testing samples.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
RdMacros: Rdpack
Depends: R (>= 4.0.0), maxLik (>= 1.3-8)
Imports: highfrequency (>= 0.6.5), roll (>= 1.1.4), xts (>= 0.12.0), tseries (>= 0.10.47), Rdpack (>= 1.0.0), lubridate (>= 1.7.9), zoo (>= 1.8.8), stats (>= 4.0.2), utils (>= 4.0.2)
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-09-14 13:40:42 UTC; Vincenzo
Author: Vincenzo Candila [aut, cre]
Maintainer: Vincenzo Candila <vincenzo.candila@uniroma1.it>
Repository: CRAN
Date/Publication: 2020-09-22 08:50:02 UTC

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New package mrregression with initial version 1.0.0
Package: mrregression
Type: Package
Title: Regression Analysis for Very Large Data Sets via Merge and Reduce
Version: 1.0.0
Author: Esther Denecke [aut], Leo N. Geppert [aut, cre], Steffen Maletz [ctb], R Core Team [ctb]
Maintainer: Leo N. Geppert <geppert@statistik.uni-dortmund.de>
Description: Frequentist and Bayesian linear regression for large data sets. Useful when the data does not fit into memory (for both frequentist and Bayesian regression), to make running time manageable (mainly for Bayesian regression), and to reduce the total running time because of reduced or less severe memory-spillover into the virtual memory. This is an implementation of Merge & Reduce for linear regression as described in Geppert, L.N., Ickstadt, K., Munteanu, A., & Sohler, C. (2020). 'Streaming statistical models via Merge & Reduce'. International Journal of Data Science and Analytics, 1-17, <doi:10.1007/s41060-020-00226-0>.
Depends: R (>= 4.0.0), Rcpp (>= 1.0.5),
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat (>= 2.3.2),
Imports: data.table (>= 1.12.8),
Enhances: rstan (>= 2.19.3),
NeedsCompilation: no
Packaged: 2020-09-13 15:47:51 UTC; leo
Repository: CRAN
Date/Publication: 2020-09-22 08:20:02 UTC

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Package lasso2 updated to version 1.2-21.1 with previous version 1.2-20 dated 2018-11-27

Title: L1 Constrained Estimation aka `lasso'
Description: Routines and documentation for solving regression problems while imposing an L1 constraint on the estimates, based on the algorithm of Osborne et al. (1998).
Author: Justin Lokhorst, Bill Venables and Berwin Turlach; port to R, tests etc: Martin Maechler <maechler@stat.math.ethz.ch>
Maintainer: Berwin Turlach <Berwin.Turlach@gmail.com>

Diff between lasso2 versions 1.2-20 dated 2018-11-27 and 1.2-21.1 dated 2020-09-22

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Package ICAMS updated to version 2.2.4 with previous version 2.2.3 dated 2020-09-18

Title: In-depth Characterization and Analysis of Mutational Signatures ('ICAMS')
Description: Analysis and visualization of experimentally elucidated mutational signatures -- the kind of analysis and visualization in Boot et al., "In-depth characterization of the cisplatin mutational signature in human cell lines and in esophageal and liver tumors", Genome Research 2018, <doi:10.1101/gr.230219.117> and "Characterization of colibactin-associated mutational signature in an Asian oral squamous cell carcinoma and in other mucosal tumor types", Genome Research 2020 <doi:10.1101/gr.255620.119>. 'ICAMS' stands for In-depth Characterization and Analysis of Mutational Signatures. 'ICAMS' has functions to read in variant call files (VCFs) and to collate the corresponding catalogs of mutational spectra and to analyze and plot catalogs of mutational spectra and signatures. Handles both "counts-based" and "density-based" catalogs of mutational spectra or signatures.
Author: Steve Rozen, Nanhai Jiang, Arnoud Boot, Mo Liu
Maintainer: Steve Rozen <steverozen@gmail.com>

Diff between ICAMS versions 2.2.3 dated 2020-09-18 and 2.2.4 dated 2020-09-22

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New package BVARverse with initial version 0.0.1
Package: BVARverse
Type: Package
Title: Tidy Bayesian Vector Autoregression
Version: 0.0.1
Date: 2020-09-07
Authors@R: c(person("Lukas", "Vashold", role = c("aut", "cre"), email = "lukas.vashold@wu.ac.at", comment = c(ORCID = "0000-0002-3562-3414")), person("Nikolas", "Kuschnig", role = c("aut"), comment = c(ORCID = "0000-0002-6642-2543")))
Author: Lukas Vashold [aut, cre] (<https://orcid.org/0000-0002-3562-3414>), Nikolas Kuschnig [aut] (<https://orcid.org/0000-0002-6642-2543>)
Maintainer: Lukas Vashold <lukas.vashold@wu.ac.at>
Description: Functions to prepare tidy objects from estimated models via 'BVAR' (see Kuschnig & Vashold, 2019 <doi:10.13140/RG.2.2.25541.60643>) and visualisation thereof. Bridges the gap between estimating models with 'BVAR' and plotting the results in a more sophisticated way with 'ggplot2' as well as passing them on in a tidy format.
URL: https://github.com/nk027/bvarverse
BugReports: https://github.com/nk027/bvarverse/issues
Depends: R (>= 3.5.0), BVAR
Imports: ggplot2, tidyr, generics, rlang
Suggests: tinytest
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-13 20:09:25 UTC; lukas
Repository: CRAN
Date/Publication: 2020-09-22 08:20:12 UTC

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New package bravo with initial version 1.0.3
Package: bravo
Type: Package
Title: Bayesian Screening and Variable Selection
Version: 1.0.3
Author: Dongjin Li [aut, cre], Somak Dutta [aut], Vivekananda Roy [ctb]
Maintainer: Dongjin Li <dongjl@iastate.edu>
Description: Performs Bayesian variable selection with embedded screening for ultra-high dimensional Gaussian linear regression models. The methodology is described in Li, Dutta and Roy (2020) <arXiv:2006.07561>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.2), methods
Imports: Rcpp (>= 1.0.2), Matrix (>= 1.2-17), compiler
LinkingTo: Rcpp
NeedsCompilation: yes
RoxygenNote: 7.1.1
Packaged: 2020-09-04 03:18:30 UTC; liyangxiaobei
Repository: CRAN
Date/Publication: 2020-09-22 08:20:06 UTC

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Package seqmagick updated to version 0.1.4 with previous version 0.1.3 dated 2019-12-19

Title: Sequence Manipulation Utilities
Description: Supports reading and writing sequences for different formats (currently interleaved and sequential formats for 'FASTA' and 'PHYLIP'), file conversion, and manipulation (e.g. filter sequences that contain specify pattern, export consensus sequence from an alignment).
Author: Guangchuang Yu [aut, cre] (<https://orcid.org/0000-0002-6485-8781>)
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between seqmagick versions 0.1.3 dated 2019-12-19 and 0.1.4 dated 2020-09-22

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Package polmineR updated to version 0.8.5 with previous version 0.8.4 dated 2020-07-22

Title: Verbs and Nouns for Corpus Analysis
Description: Package for corpus analysis using the Corpus Workbench ('CWB', <http://cwb.sourceforge.net/>) as an efficient back end for indexing and querying large corpora. The package offers functionality to flexibly create subcorpora and to carry out basic statistical operations (count, co-occurrences etc.). The original full text of documents can be reconstructed and inspected at any time. Beyond that, the package is intended to serve as an interface to packages implementing advanced statistical procedures. Respective data structures (document-term matrices, term-co-occurrence matrices etc.) can be created based on the indexed corpora.
Author: Andreas Blaette [aut, cre] (<https://orcid.org/0000-0001-8970-8010>), Christoph Leonhardt [ctb]
Maintainer: Andreas Blaette <andreas.blaette@uni-due.de>

Diff between polmineR versions 0.8.4 dated 2020-07-22 and 0.8.5 dated 2020-09-22

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Package tinytex updated to version 0.26 with previous version 0.25 dated 2020-07-24

Title: Helper Functions to Install and Maintain TeX Live, and Compile LaTeX Documents
Description: Helper functions to install and maintain the 'LaTeX' distribution named 'TinyTeX' (<https://yihui.org/tinytex/>), a lightweight, cross-platform, portable, and easy-to-maintain version of 'TeX Live'. This package also contains helper functions to compile 'LaTeX' documents, and install missing 'LaTeX' packages automatically.
Author: Yihui Xie [aut, cre, cph] (<https://orcid.org/0000-0003-0645-5666>), RStudio, PBC [cph], Fernando Cagua [ctb], Ethan Heinzen [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between tinytex versions 0.25 dated 2020-07-24 and 0.26 dated 2020-09-22

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Package TestDimorph updated to version 0.3.4 with previous version 0.3.3 dated 2020-09-20

Title: Analysis Of The Interpopulation Difference In Degree of Sexual Dimorphism Using Summary Statistics
Description: Provides two approaches of comparison; the univariate and the multivariate analysis in two or more populations. Since the main obstacle of performing systematic comparisons in anthropological studies is the absence of raw data, the current package offer a solution for this problem by allowing the use of published summary statistics of metric data (mean, standard deviation and sex specific sample size) as illustrated by the works of Greene, D. L. (1989) <doi:10.1002/ajpa.1330790113> and Konigsberg, L. W. (1991) <doi:10.1002/ajpa.1330840110>.
Author: Bassam A. Abulnoor [aut, cre] (<https://orcid.org/0000-0003-4351-2754>), MennattAllah H. Attia [aut] (<https://orcid.org/0000-0002-2304-532X>), Lyle W. Konigsberg [aut] (<https://orcid.org/0000-0003-4052-1575>)
Maintainer: Bassam A. Abulnoor <bas12@fayoum.edu.eg>

Diff between TestDimorph versions 0.3.3 dated 2020-09-20 and 0.3.4 dated 2020-09-22

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New package TestCor with initial version 0.0.2.1
Package: TestCor
Title: FWER and FDR Controlling Procedures for Multiple Correlation Tests
Version: 0.0.2.1
Date: 2020-09-18
Authors@R: c( person("Gannaz", "Irene", email = "irene.gannaz@insa-lyon.fr", role = c("aut","cre")))
Maintainer: Gannaz Irene <irene.gannaz@insa-lyon.fr>
Description: Different multiple testing procedures for correlation tests are implemented. These procedures were shown to theoretically control asymptotically the Family Wise Error Rate (Roux (2018) <https://tel.archives-ouvertes.fr/tel-01971574v1>) or the False Discovery Rate (Cai & Liu (2016) <doi:10.1080/01621459.2014.999157>). The package gather four test statistics used in correlation testing, four FWER procedures with either single step or stepdown versions, and four FDR procedures.
Depends: R (>= 3.4)
Encoding: UTF-8
License: GPL (>= 2)
Imports: Rcpp, MASS, stats
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
NeedsCompilation: yes
Author: Gannaz Irene [aut, cre]
Packaged: 2020-09-21 12:33:36 UTC; igannaz
Repository: CRAN
Date/Publication: 2020-09-22 06:30:25 UTC

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New package rBiasCorrection with initial version 0.2.2
Package: rBiasCorrection
Title: Correct Bias in DNA Methylation Analyses
Version: 0.2.2
Authors@R: c(person(given = "Lorenz A.", family = "Kapsner", role = c("cre", "aut", "cph"), email = "lorenz.kapsner@gmail.com", comment = c(ORCID = "0000-0003-1866-860X")), person(given = "Evgeny A.", family = "Moskalev", role = "aut"))
Description: Implementation of the algorithms (with minor modifications) to correct bias in quantitative DNA methylation analyses as described by Moskalev et al. (2011) <doi:10.1093/nar/gkr213>.
License: GPL-3
URL: https://github.com/kapsner/rBiasCorrection
BugReports: https://github.com/kapsner/rBiasCorrection/issues
Depends: R (>= 2.10)
Imports: data.table, future, future.apply, ggplot2, ggpubr, magrittr, nls2, polynom, stats
Suggests: knitr, lintr, microbenchmark, rmarkdown, testthat
VignetteBuilder: knitr
Date/Publication: 2020-09-22 06:30:07 UTC
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-13 19:52:45 UTC; user
Author: Lorenz A. Kapsner [cre, aut, cph] (<https://orcid.org/0000-0003-1866-860X>), Evgeny A. Moskalev [aut]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>
Repository: CRAN

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Package FHDI updated to version 1.4.1 with previous version 1.4.0 dated 2020-04-23

Title: Fractional Hot Deck and Fully Efficient Fractional Imputation
Description: Impute general multivariate missing data with the fractional hot deck imputation based on Jaekwang Kim (2011) <doi:10.1093/biomet/asq073>.
Author: Inho Cho [aut, cre], Jaekwang Kim [aut], Jongho Im [aut], Yicheng Yang [aut]
Maintainer: Inho Cho <icho@iastate.edu>

Diff between FHDI versions 1.4.0 dated 2020-04-23 and 1.4.1 dated 2020-09-22

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New package faux with initial version 0.0.1.5
Package: faux
Title: Simulation for Factorial Designs
Version: 0.0.1.5
Date: 2020-09-11
Authors@R: c( person( given = "Lisa", family = "DeBruine", role = c("aut", "cre"), email = "debruine@gmail.com", comment = c(ORCID = "0000-0002-7523-5539") ), person( given = "Anna", family = "Krystalli", role = c("ctb"), email = "annakrystalli@googlemail.com", comment = c(ORCID = "0000-0002-2378-4915") ), person( given = "Andrew", family = "Heiss", role = c("ctb"), email = "andrew@andrewheiss.com", comment = c(ORCID = "0000-0002-3948-3914") ))
Description: Create datasets with factorial structure through simulation by specifying variable parameters. Extended documentation at <https://debruine.github.io/faux/>. Described in DeBruine (2020) <doi:10.5281/zenodo.2669586>.
Depends: R (>= 3.2.4)
Imports: lme4, dplyr, ggplot2 (>= 3.3.0), jsonlite, truncnorm
License: MIT + file LICENSE
Suggests: testthat (>= 2.1.0), tidyr, knitr, rmarkdown, roxygen2, covr, cowplot, ggExtra, purrr, broom, broom.mixed, psych
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Encoding: UTF-8
LazyData: true
URL: https://github.com/debruine/faux
BugReports: https://github.com/debruine/faux/issues
NeedsCompilation: no
Packaged: 2020-09-21 13:33:30 UTC; lisad
Author: Lisa DeBruine [aut, cre] (<https://orcid.org/0000-0002-7523-5539>), Anna Krystalli [ctb] (<https://orcid.org/0000-0002-2378-4915>), Andrew Heiss [ctb] (<https://orcid.org/0000-0002-3948-3914>)
Maintainer: Lisa DeBruine <debruine@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-22 06:30:13 UTC

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Package DRIP updated to version 1.6 with previous version 1.5 dated 2020-09-10

Title: Discontinuous Regression and Image Processing
Description: This is a collection of functions for discontinuous regression analysis and image processing (DRIP). This version removes the dependence on the GNU Scientific Library.
Author: Yicheng Kang <kangx276@umn.edu>
Maintainer: Yicheng Kang <kangx276@umn.edu>

Diff between DRIP versions 1.5 dated 2020-09-10 and 1.6 dated 2020-09-22

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Package brant updated to version 0.3-0 with previous version 0.2-0 dated 2018-01-10

Title: Test for Parallel Regression Assumption
Description: Tests the parallel regression assumption wit the brant test by Brant (1990) <doi: 10.2307/2532457> for ordinal logit models generated with the function polr() from the package 'MASS'.
Author: Benjamin Schlegel [aut,cre], Marco Steenbergen [aut]
Maintainer: Benjamin Schlegel <kontakt@benjaminschlegel.ch>

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Package cmdfun (with last version 1.0.1) was removed from CRAN

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

2020-09-20 1.0.1

Permanent link
Package scipub updated to version 1.2.0 with previous version 1.1.0 dated 2020-06-04

Title: Summarize Data for Scientific Publication
Description: Create and format tables and APA statistics for scientific publication. This includes making a 'Table 1' to summarize demographics across groups, correlation tables with significance indicated by stars, and extracting formatted statistical summarizes from simple tests for in-text notation. The package also includes functions for Winsorizing data based on a Z-statistic cutoff.
Author: David Pagliaccio [aut, cre] (<https://orcid.org/0000-0002-1214-1965>)
Maintainer: David Pagliaccio <david.pagliaccio@gmail.com>

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Package readtext updated to version 0.80 with previous version 0.76 dated 2020-03-04

Title: Import and Handling for Plain and Formatted Text Files
Description: Functions for importing and handling text files and formatted text files with additional meta-data, such including '.csv', '.tab', '.json', '.xml', '.html', '.pdf', '.doc', '.docx', '.rtf', '.xls', '.xlsx', and others.
Author: Kenneth Benoit [aut, cre, cph], Adam Obeng [aut], Kohei Watanabe [ctb], Akitaka Matsuo [ctb], Paul Nulty [ctb], Stefan Müller [ctb]
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

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Package rdbnomics updated to version 0.6.3 with previous version 0.6.2 dated 2020-07-06

Title: Download DBnomics Data
Description: R access to hundreds of millions data series from DBnomics API (<https://db.nomics.world/>).
Author: Sebastien Galais [cre, ctb], Thomas Brand [aut]
Maintainer: Sebastien Galais <s915.stem@gmail.com>

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Package krige updated to version 0.5.7 with previous version 0.5.6 dated 2020-06-20

Title: Geospatial Kriging with Metropolis Sampling
Description: Estimates kriging models for geographical point-referenced data. Method is described in Gill (2020) <doi:10.1177/1532440020930197>.
Author: Jason S. Byers [aut, cre], Le Bao [aut], Jamie Carson [aut], Jeff Gill [aut]
Maintainer: Jason S. Byers <jaybyers55@gmail.com>

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Mon, 21 Sep 2020

Package splmm updated to version 1.1 with previous version 1.0 dated 2020-09-21

Title: Simultaneous Penalized Linear Mixed Effects Models
Description: Contains functions that fit linear mixed-effects models for high-dimensional data (p>>n) with penalty for both the fixed effects and random effects for variable selection. The details of the algorithm can be found in Luoying Yang PhD thesis (available soon). The algorithm implementation is based on the R package 'lmmlasso'.
Author: Luoying Yang, Tong Tong Wu
Maintainer: Luoying Yang <lyang19@u.rochester.edu>

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Package metropolis updated to version 0.1.8 with previous version 0.1.5 dated 2020-01-23

Title: The Metropolis Algorithm
Description: Learning and using the Metropolis algorithm for Bayesian fitting of a generalized linear model. The package vignette includes examples of hand-coding a logistic model using several variants of the Metropolis algorithm. The package also contains R functions for simulating posterior distributions of Bayesian generalized linear model parameters using guided, adaptive, guided-adaptive and random walk Metropolis algorithms. The random walk Metropolis algorithm was originally described in Metropolis et al (1953); <doi:10.1063/1.1699114>.
Author: Alexander Keil [aut, cre]
Maintainer: Alexander Keil <akeil@unc.edu>

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Package koRpus updated to version 0.13-1 with previous version 0.11-5 dated 2018-10-28

Title: An R Package for Text Analysis
Description: A set of tools to analyze texts. Includes, amongst others, functions for automatic language detection, hyphenation, several indices of lexical diversity (e.g., type token ratio, HD-D/vocd-D, MTLD) and readability (e.g., Flesch, SMOG, LIX, Dale-Chall). Basic import functions for language corpora are also provided, to enable frequency analyses (supports Celex and Leipzig Corpora Collection file formats) and measures like tf-idf. Note: For full functionality a local installation of TreeTagger is recommended. It is also recommended to not load this package directly, but by loading one of the available language support packages from the 'l10n' repository <https://undocumeantit.github.io/repos/l10n/>. 'koRpus' also includes a plugin for the R GUI and IDE RKWard, providing graphical dialogs for its basic features. The respective R package 'rkward' cannot be installed directly from a repository, as it is a part of RKWard. To make full use of this feature, please install RKWard from <https://rkward.kde.org> (plugins are detected automatically). Due to some restrictions on CRAN, the full package sources are only available from the project homepage. To ask for help, report bugs, request features, or discuss the development of the package, please subscribe to the koRpus-dev mailing list (<https://korpusml.reaktanz.de>).
Author: Meik Michalke [aut, cre], Earl Brown [ctb], Alberto Mirisola [ctb], Alexandre Brulet [ctb], Laura Hauser [ctb]
Maintainer: Meik Michalke <meik.michalke@hhu.de>

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Package freesurferformats updated to version 0.1.13 with previous version 0.1.12 dated 2020-08-26

Title: Read and Write 'FreeSurfer' Neuroimaging File Formats
Description: Provides functions to read and write neuroimaging data in various file formats, with a focus on 'FreeSurfer' <http://freesurfer.net/> formats. This includes, but is not limited to, the following file formats: 1) MGH/MGZ format files, which can contain multi-dimensional images or other data. Typically they contain time-series of three-dimensional brain scans acquired by magnetic resonance imaging (MRI). They can also contain vertex-wise measures of surface morphometry data. The MGH format is named after the Massachusetts General Hospital, and the MGZ format is a compressed version of the same format. 2) 'FreeSurfer' morphometry data files in binary 'curv' format. These contain vertex-wise surface measures, i.e., one scalar value for each vertex of a brain surface mesh. These are typically values like the cortical thickness or brain surface area at each vertex. 3) Annotation file format. This contains a brain surface parcellation derived from a cortical atlas. 4) Surface file format. Contains a brain surface mesh, given by a list of vertices and a list of faces.
Author: Tim Schäfer [aut, cre] (<https://orcid.org/0000-0002-3683-8070>)
Maintainer: Tim Schäfer <ts+code@rcmd.org>

Diff between freesurferformats versions 0.1.12 dated 2020-08-26 and 0.1.13 dated 2020-09-21

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Package SuperGauss updated to version 2.0.0 with previous version 1.0.2 dated 2020-02-27

Title: Superfast Likelihood Inference for Stationary Gaussian Time Series
Description: Likelihood evaluations for stationary Gaussian time series are typically obtained via the Durbin-Levinson algorithm, which scales as O(n^2) in the number of time series observations. This package provides a "superfast" O(n log^2 n) algorithm written in C++, crossing over with Durbin-Levinson around n = 300. Efficient implementations of the score and Hessian functions are also provided, leading to superfast versions of inference algorithms such as Newton-Raphson and Hamiltonian Monte Carlo. The C++ code provides a Toeplitz matrix class packaged as a header-only library, to simplify low-level usage in other packages and outside of R.
Author: Yun Ling [aut], Martin Lysy [aut, cre]
Maintainer: Martin Lysy <mlysy@uwaterloo.ca>

Diff between SuperGauss versions 1.0.2 dated 2020-02-27 and 2.0.0 dated 2020-09-21

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Package mc.heterogeneity updated to version 0.1.2 with previous version 0.1.1 dated 2020-06-24

Title: A Monte Carlo Based Heterogeneity Test for Meta-Analysis
Description: Implements a Monte Carlo Based Heterogeneity Test for standardized mean differences (d), Fisher-transformed Pearson's correlations (r), and natural-logarithm-transformed odds ratio (OR) in Meta-Analysis Studies. Depending on the presence of moderators, this Monte Carlo Based Test can be implemented in the random or mixed-effects model. This package uses rma() function from the R package 'metafor' to obtain parameter estimates and likelihood, so installation of R package 'metafor' is required. This approach refers to the studies of Hedges (1981) <doi:10.3102/10769986006002107>, Hedges & Olkin (1985, ISBN:978-0123363800), Silagy, Lancaster, Stead, Mant, & Fowler (2004) <doi:10.1002/14651858.CD000146.pub2>, Viechtbauer (2010) <doi:10.18637/jss.v036.i03>, and Zuckerman (1994, ISBN:978-0521432009).
Author: Han Du [aut], Ge Jiang [aut, cre], Zijun Ke [ctb]
Maintainer: Ge Jiang <gejiang2@illinois.edu>

Diff between mc.heterogeneity versions 0.1.1 dated 2020-06-24 and 0.1.2 dated 2020-09-21

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Package wedge (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:

2019-09-04 1.0-3
2019-06-27 1.0-2
2019-05-01 1.0-1

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Package periscope updated to version 0.5.2 with previous version 0.5.1 dated 2020-07-03

Title: Enterprise Streamlined 'Shiny' Application Framework
Description: An enterprise-targeted scalable and UI-standardized 'shiny' framework including a variety of developer convenience functions with the goal of both streamlining robust application development while assisting with creating a consistent user experience regardless of application or developer.
Author: Constance Brett [aut, cre], Isaac Neuhaus [aut] (canvasXpress JavaScript Library Maintainer), Ger Inberg [ctb], Bristol-Meyers Squibb (BMS) [cph]
Maintainer: Constance Brett <connie@aggregate-genius.com>

Diff between periscope versions 0.5.1 dated 2020-07-03 and 0.5.2 dated 2020-09-21

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New package tidystats with initial version 0.5
Package: tidystats
Type: Package
Title: Save Output of Statistical Tests
Version: 0.5
Author: Willem Sleegers
Maintainer: Willem Sleegers <w.sleegers@me.com>
Description: Save the output of statistical tests in an organized file that can be shared with others or used to report statistics in scientific papers.
URL: https://willemsleegers.github.io/tidystats/
BugReports: https://github.com/WillemSleegers/tidystats/issues
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.1.1
LazyData: true
Depends: R (>= 3.2.0)
Imports: dplyr, tidyr, purrr, stringr, readr, jsonlite, tibble
Suggests: knitr, rmarkdown, testthat, BayesFactor, lme4, lmerTest
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-21 10:07:04 UTC; willem
Repository: CRAN
Date/Publication: 2020-09-21 16:50:02 UTC

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Package SmallCountRounding updated to version 0.5.0 with previous version 0.4.0 dated 2019-10-17

Title: Small Count Rounding of Tabular Data
Description: A statistical disclosure control tool to protect frequency tables in cases where small values are sensitive. The function PLSrounding() performs small count rounding of necessary inner cells so that all small frequencies of cross-classifications to be published (publishable cells) are rounded. This is equivalent to changing micro data since frequencies of unique combinations are changed. Thus, additivity and consistency are guaranteed. The methodology is described in Langsrud and Heldal (2018) <https://www.researchgate.net/publication/327768398_An_Algorithm_for_Small_Count_Rounding_of_Tabular_Data>.
Author: Øyvind Langsrud [aut, cre], Johan Heldal [aut]
Maintainer: Øyvind Langsrud <oyl@ssb.no>

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Package parameters updated to version 0.8.6 with previous version 0.8.5 dated 2020-09-12

Title: Processing of Model Parameters
Description: Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see support list of insight; Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut] (<https://orcid.org/0000-0001-5375-9967>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Indrajeet Patil [aut] (<https://orcid.org/0000-0003-1995-6531>), Søren Højsgaard [aut], Zen J. Lau [ctb]
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package mlt.docreg updated to version 1.0-8 with previous version 1.0-7 dated 2020-08-31

Title: Most Likely Transformations: Documentation and Regression Tests
Description: Additional documentation, a package vignette and regression tests for package mlt.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between mlt.docreg versions 1.0-7 dated 2020-08-31 and 1.0-8 dated 2020-09-21

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Package labelled updated to version 2.7.0 with previous version 2.6.0 dated 2020-08-27

Title: Manipulating Labelled Data
Description: Work with labelled data imported from 'SPSS' or 'Stata' with 'haven' or 'foreign'. This package provides useful functions to deal with "haven_labelled" and "haven_labelled_spss" classes introduced by 'haven' package.
Author: Joseph Larmarange [aut, cre] (<https://orcid.org/0000-0001-7097-700X>), Daniel Ludecke [ctb], Hadley Wickham [ctb], Michal Bojanowski [ctb], François Briatte [ctb]
Maintainer: Joseph Larmarange <joseph@larmarange.net>

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Package image.textlinedetector updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-15

Title: Segment Images in Text Lines and Words
Description: Find text lines in scanned images and segment the lines into words. Includes implementations of the paper 'Novel A* Path Planning Algorithm for Line Segmentation of Handwritten Documents' by Surinta O. et al (2014) <doi:10.1109/ICFHR.2014.37> available at <https://github.com/smeucci/LineSegm>, an implementation of 'A Statistical approach to line segmentation in handwritten documents' by Arivazhagan M. et al (2007) <doi:10.1117/12.704538>, and a wrapper for an image segmentation technique to detect words in text lines as described in the paper 'Scale Space Technique for Word Segmentation in Handwritten Documents' by Manmatha R. and Srimal N. (1999) paper at <doi:10.1007/3-540-48236-9_3>, wrapper for code available at <https://github.com/arthurflor23/text-segmentation>.
Author: Jan Wijffels [aut, cre, cph] (R wrapper), Vrije Universiteit Brussel - DIGI: Brussels Platform for Digital Humanities [cph] (R wrapper), Jeroen Ooms [ctb, cph] (More details in LICENSE.note file), Arthur Flôr [ctb, cph] (More details in LICENSE.note file), Saverio Meucci [ctb, cph] (More details in LICENSE.note file), Yeara Kozlov [ctb, cph] (More details in LICENSE.note file), Tino Weinkauf [ctb, cph] (More details in LICENSE.note file)
Maintainer: Jan Wijffels <jan.wijffels@vub.be>

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Package HSAUR3 updated to version 1.0-10 with previous version 1.0-9 dated 2018-05-28

Title: A Handbook of Statistical Analyses Using R (3rd Edition)
Description: Functions, data sets, analyses and examples from the third edition of the book ''A Handbook of Statistical Analyses Using R'' (Torsten Hothorn and Brian S. Everitt, Chapman & Hall/CRC, 2014). The first chapter of the book, which is entitled ''An Introduction to R'', is completely included in this package, for all other chapters, a vignette containing all data analyses is available. In addition, Sweave source code for slides of selected chapters is included in this package (see HSAUR3/inst/slides). The publishers web page is '<http://www.crcpress.com/product/isbn/9781482204582>'.
Author: Torsten Hothorn and Brian S. Everitt
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package fairmodels updated to version 0.2.2 with previous version 0.1.1 dated 2020-08-20

Title: Flexible Tool for Bias Detection, Visualization, and Mitigation
Description: Measure fairness metrics in one place for many models. Check how big is model's bias towards different races, sex, nationalities etc. Use measures such as Statistical Parity, Equal odds to detect the discrimination against unprivileged groups. Visualize the bias using heatmap, radar plot, biplot, bar chart (and more!). There are various pre-processing and post-processing bias mitigation algorithms implemented.
Author: Jakub Wiśniewski [aut, cre], Przemysław Biecek [aut] (<https://orcid.org/0000-0001-8423-1823>)
Maintainer: Jakub Wiśniewski <jakwisn@gmail.com>

Diff between fairmodels versions 0.1.1 dated 2020-08-20 and 0.2.2 dated 2020-09-21

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New package diseq with initial version 0.0.13
Package: diseq
Title: Estimation Methods for Markets in Disequilibrium
Version: 0.0.13
Date: 2020-09-14
Authors@R: person( "Pantelis", "Karapanagiotis", email = "pikappa.devel@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9871-1908"))
Description: Provides estimation methods for markets in equilibrium and disequilibrium. Specifically, it supports the estimation of an equilibrium and four disequilibrium models with both correlated and independent shocks. It also provides post-estimation analysis tools, such as aggregation and marginal effects calculations. The estimation methods are based on full information maximum likelihood techniques given in Maddala and Nelson (1974) <doi:10.2307/1914215>. They are implemented using the analytic derivative expressions calculated in Karapanagiotis (2020) <doi:10.2139/ssrn.3525622>. The equilibrium estimation constitutes a special case of a system of simultaneous equations. The disequilibrium models, instead, replace the market clearing condition with a short side rule and allow for different specifications of price dynamics.
Language: en-US
URL: https://github.com/pi-kappa-devel/diseq/
BugReports: https://github.com/pi-kappa-devel/diseq/issues
Depends: R (>= 3.5.0)
Imports: bbmle (>= 1.0.20), dplyr (>= 0.7.6), magrittr (>= 1.5), MASS (>= 7.3-50), methods, rlang (>= 0.2.1), systemfit (>= 1.1), tibble (>= 1.4.2), tidyr (>= 1.0.2)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: ggplot2 (>= 3.0.0), knitr (>= 1.20), numDeriv (>= 2016.8.1.1), rmarkdown (>= 1.10), testthat (>= 2.0.0)
VignetteBuilder: knitr
Collate: 'equation_base.R' 'system_base.R' 'equation_basic.R' 'system_basic.R' 'derivatives_basic.R' 'equation_deterministic_adjustment.R' 'system_deterministic_adjustment.R' 'derivatives_deterministic_adjustment.R' 'equation_directional.R' 'system_directional.R' 'derivatives_directional.R' 'system_fiml.R' 'derivatives_fiml.R' 'equation_stochastic_adjustment.R' 'system_stochastic_adjustment.R' 'derivatives_stochastic_adjustment.R' 'diseq.R' 'model_logger.R' 'model_base.R' 'diseq_base.R' 'diseq_basic.R' 'diseq_deterministic_adjustment.R' 'diseq_directional.R' 'diseq_stochastic_adjustment.R' 'eq_base.R' 'eq_2sls.R' 'eq_fiml.R' 'model_simulation.R'
NeedsCompilation: no
Packaged: 2020-09-13 22:32:37 UTC; ntelispak
Author: Pantelis Karapanagiotis [aut, cre] (<https://orcid.org/0000-0001-9871-1908>)
Maintainer: Pantelis Karapanagiotis <pikappa.devel@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-21 16:50:11 UTC

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Package cplexAPI updated to version 1.4.0 with previous version 1.3.6 dated 2019-06-21

Title: R Interface to C API of IBM ILOG CPLEX
Description: This is the R Interface to the C API of IBM ILOG CPLEX. It necessarily depends on IBM ILOG CPLEX (>= 12.1).
Author: Mayo Roettger [cre], Gabriel Gelius-Dietrich [aut], C. Jonathan Fritzemeier [ctb]
Maintainer: Mayo Roettger <mayo.roettger@hhu.de>

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New package colocalization with initial version 1.0.2
Package: colocalization
Type: Package
Title: Normalized Spatial Intensity Correlation
Version: 1.0.2
Author: Jiahui Xu, Xueyan Liu, Lin Li, Cheng Cheng, Hui Zhang
Maintainer: Hui Zhang <hzhang@northwestern.edu>
Depends: R (>= 2.10)
Description: Calculate the colocalization index, NSInC, in two different ways as described in the paper (Liu et al., 2019. Manuscript submitted for publication.) for multiple-species spatial data which contain the precise locations and membership of each spatial point. The two main functions are nsinc.d() and nsinc.z(). They provide the Pearson’s correlation coefficients of signal proportions in different memberships within a concerned proximity of every signal (or every base signal if single direction colocalization is considered) across all (base) signals using two different ways of normalization. The proximity sizes could be an individual value or a range of values, where the default ranges of values are different for the two functions.
License: GPL-3
Encoding: UTF-8
Suggests: testthat, rgl
Imports: utils, stats, ggplot2
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2020-09-13 22:00:43 UTC; lli3188
Repository: CRAN
Date/Publication: 2020-09-21 16:50:16 UTC

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Package boot.heterogeneity updated to version 0.1.1 with previous version 0.1.0 dated 2020-05-08

Title: A Bootstrap-Based Heterogeneity Test for Meta-Analysis
Description: Implements a bootstrap-based heterogeneity test for standardized mean differences (d), Fisher-transformed Pearson's correlations (r), and natural-logarithm-transformed odds ratio (or) in meta-analysis studies. Depending on the presence of moderators, this Monte Carlo based test can be implemented in the random- or mixed-effects model. This package uses rma() function from the R package 'metafor' to obtain parameter estimates and likelihoods, so installation of R package 'metafor' is required. This approach refers to the studies of Anscombe (1956) <doi:10.2307/2332926>, Haldane (1940) <doi:10.2307/2332614>, Hedges (1981) <doi:10.3102/10769986006002107>, Hedges & Olkin (1985, ISBN:978-0123363800), Silagy, Lancaster, Stead, Mant, & Fowler (2004) <doi:10.1002/14651858.CD000146.pub2>, Viechtbauer (2010) <doi:10.18637/jss.v036.i03>, and Zuckerman (1994, ISBN:978-0521432009).
Author: Ge Jiang [aut, cre], Han Du [aut], Zijun Ke [ctb]
Maintainer: Ge Jiang <gejiang2@illinois.edu>

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Package bahc updated to version 0.3.0 with previous version 0.2.0 dated 2020-05-15

Title: Filter Covariance and Correlation Matrices with Bootstrapped-Averaged Hierarchical Ansatz
Description: A method to filter correlation and covariance matrices by averaging bootstrapped filtered hierarchical clustering and boosting. See Ch. Bongiorno and D. Challet, Covariance matrix filtering with bootstrapped hierarchies (2020) <arXiv:2003.05807> and Ch. Bongiorno and D. Challet, Reactive Global Minimum Variance Portfolios with k-BAHC covariance cleaning (2020) <arXiv:2005.08703>.
Author: Christian Bongiorno and Damien Challet
Maintainer: Damien Challet <damien.challet@gmail.com>

Diff between bahc versions 0.2.0 dated 2020-05-15 and 0.3.0 dated 2020-09-21

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Package tsapp updated to version 1.0.1 with previous version 1.0.0 dated 2020-03-20

Title: Time Series, Analysis and Application
Description: Accompanies the book Rainer Schlittgen and Cristina Sattarhoff (2020) <https://www.degruyter.com/view/title/575978> "Angewandte Zeitreihenanalyse mit R, 4. Auflage" . The package contains the time series and functions used therein. It was developed over many years teaching courses about time series analysis.
Author: Rainer Schlittgen
Maintainer: Rainer Schlittgen <R.Schlittgen@t-online.de>

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Package nvmix updated to version 0.0-5 with previous version 0.0-4 dated 2020-06-12

Title: Multivariate Normal Variance Mixtures
Description: Functions for working with (grouped) multivariate normal variance mixture distributions (evaluation of distribution functions and densities, random number generation and parameter estimation), including Student's t distribution for non-integer degrees-of-freedom as well as the grouped t distribution and copula with multiple degrees-of-freedom parameters. See Hintz, Hofert, Lemieux (2019) <arXiv:1911.03017> for more details.
Author: Marius Hofert [aut, cre], Erik Hintz [aut], Christiane Lemieux [aut]
Maintainer: Marius Hofert <marius.hofert@uwaterloo.ca>

Diff between nvmix versions 0.0-4 dated 2020-06-12 and 0.0-5 dated 2020-09-21

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Package FLSSS updated to version 8.6.6 with previous version 8.5.6 dated 2019-10-28

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

Diff between FLSSS versions 8.5.6 dated 2019-10-28 and 8.6.6 dated 2020-09-21

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Package AGHmatrix updated to version 2.0.0 with previous version 1.0.2 dated 2019-07-30

Title: Relationship Matrices for Diploid and Autopolyploid Species
Description: Computation of A (pedigree), G (genomic-base), and H (A corrected by G) relationship matrices for diploid and autopolyploid species. Several methods are implemented considering additive and non-additive models.
Author: Rodrigo Amadeu [aut, cre], Catherine Cellon [ctb], Leticia Lara [ctb], Marcio Resende [ctb], Ivone Oliveira [ctb], Luis Ferrao [ctb], Patricio Munoz [ctb], Augusto Garcia [ctb]
Maintainer: Rodrigo Amadeu <rramadeu@ufl.edu>

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Package ProcMod updated to version 1.0.6 with previous version 1.0.3 dated 2019-11-25

Title: Informative Procrustean Matrix Correlation
Description: Estimates corrected Procrustean correlation between matrices for removing overfitting effect. Coissac Eric and Gonindard-Melodelima Christelle (2019) <bioarXiv:10.1101/842070>.
Author: Eric Coissac, Christelle Gonindard-Melodelima
Maintainer: Eric Coissac <eric.coissac@metabarcoding.org>

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Package rmdcev (with last version 1.2.2) was removed from CRAN

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

2020-09-18 1.2.2

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Package ImportExport updated to version 1.3 with previous version 1.1 dated 2015-09-19

Title: Import and Export Data
Description: Import and export data from the most common statistical formats by using R functions that guarantee the least loss of the data information, giving special attention to the date variables and the labelled ones.
Author: Roger Pros, Isaac Subirana, Joan Vila.
Maintainer: Isaac Subirana <isubirana@imim.es>

Diff between ImportExport versions 1.1 dated 2015-09-19 and 1.3 dated 2020-09-21

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Package HSAUR2 updated to version 1.1-18 with previous version 1.1-17 dated 2017-08-20

Title: A Handbook of Statistical Analyses Using R (2nd Edition)
Description: Functions, data sets, analyses and examples from the second edition of the book ''A Handbook of Statistical Analyses Using R'' (Brian S. Everitt and Torsten Hothorn, Chapman & Hall/CRC, 2008). The first chapter of the book, which is entitled ''An Introduction to R'', is completely included in this package, for all other chapters, a vignette containing all data analyses is available. In addition, the package contains Sweave code for producing slides for selected chapters (see HSAUR2/inst/slides).
Author: Brian S. Everitt and Torsten Hothorn
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between HSAUR2 versions 1.1-17 dated 2017-08-20 and 1.1-18 dated 2020-09-21

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New package retroharmonize with initial version 0.1.13
Package: retroharmonize
Type: Package
Title: Ex Post Survey Data Harmonization
Version: 0.1.13
Authors@R: c(person(given = "Daniel", family = "Antal", role = c("aut", "cre"), email = "daniel.antal@ceemid.eu", comment = c(ORCID = "0000-0001-7513-6760")), person(given = "Marta", family = "Kolczynska", role = c("ctb"), email = "mkolczynska@gmail.com", comment = c(ORCID = "0000-0003-4981-0437")) )
Maintainer: Daniel Antal <daniel.antal@ceemid.eu>
Description: Assist in reproducible retrospective (ex-post) harmonization of data, particularly individual level survey data, by providing tools for organizing metadata, standardizing the coding of variables, and variable names and value labels, including missing values, and documenting the data transformations, with the help of comprehensive s3 classes.
License: GPL-3
Encoding: UTF-8
Language: en-US
URL: https://retroharmonize.dataobservatory.eu/
BugReports: https://github.com/antaldaniel/retroharmonize/issues
LazyData: true
Imports: vctrs, haven, dplyr (>= 1.0.0), magrittr, stats, tibble, labelled, methods, rlang, fs, assertthat, tidyselect, pillar, snakecase, purrr, tidyr, here
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown, covr, testthat, png
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-11 21:54:27 UTC; Daniel Antal
Author: Daniel Antal [aut, cre] (<https://orcid.org/0000-0001-7513-6760>), Marta Kolczynska [ctb] (<https://orcid.org/0000-0003-4981-0437>)
Repository: CRAN
Date/Publication: 2020-09-21 09:10:02 UTC

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New package mobr with initial version 2.0.0
Package: mobr
Title: Measurement of Biodiversity
Version: 2.0.0
Authors@R: c(person("Daniel", "McGlinn", email = "danmcglinn@gmail.com", role = c("aut", "cre")), person("Xiao", "Xiao", email = "xiao@weecology.org", role = "aut"), person("Brian", "McGill", email = "brimcgill@gmail.com", role = "aut"), person("Felix", "May", email = "felix.may@idiv.de", role = "aut"), person("Thore", "Engel", email = "thore.engel@idiv.de", role = "aut"), person("Caroline", "Oliver", email = "olivercs@g.cofc.edu", role = "aut"), person("Shane", "Blowes", email = "shane.blowes@idiv.de", role = "aut"), person("Tiffany", "Knight", email = "tiffany.knight@idiv.de", role = 'aut'), person("Oliver", "Purschke", email = "oliverpurschke@web.de", role = 'aut'), person("Nicholas", "Gotelli", email = "Nicholas.Gotelli@uvm.edu", role = "aut"), person("Jon", "Chase", email = "jonathan.chase@idiv.de", role = "aut"))
Date: 2020-08-15
Description: Functions for calculating metrics for the measurement biodiversity and its changes across scales, treatments, and gradients. The methods implemented in this package are described in: Chase, J.M., et al. (2018) <doi:10.1111/ele.13151>, McGlinn, D.J., et al. (2019) <doi:10.1111/2041-210X.13102>, and McGlinn, D.J., et al. (2020) <doi:10.1101/851717>.
Depends: R (>= 3.5.0)
Imports: plotrix, scales, dplyr, purrr, tidyr, pbapply, ggplot2, egg, tibble, vctrs, rlang, geosphere
Suggests: knitr, rmarkdown, testthat
License: MIT + file LICENSE
LazyData: true
RoxygenNote: 7.1.1
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-12 16:55:33 UTC; mcglinndj
Author: Daniel McGlinn [aut, cre], Xiao Xiao [aut], Brian McGill [aut], Felix May [aut], Thore Engel [aut], Caroline Oliver [aut], Shane Blowes [aut], Tiffany Knight [aut], Oliver Purschke [aut], Nicholas Gotelli [aut], Jon Chase [aut]
Maintainer: Daniel McGlinn <danmcglinn@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-21 09:30:03 UTC

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New package wayback with initial version 0.2.4
Package: wayback
Type: Package
Title: Rock Solid Package Installation for Legacy R Versions
Version: 0.2.4
Date: 2020-09-11
Authors@R: c( person( given = "Peter", family = "Meissner", email = "retep.meissner@gmail.com", role = c("aut", "cre") ), person( family = "virtual7", email = "info@virtual7.de", role = c("cph") ) )
Maintainer: Peter Meissner <retep.meissner@gmail.com>
Description: Make sure packages are available at runtime without any setup. Package installation, reproducibility and exchanging code can be frustrating especially if code is used on older R versions. Often it is hard to puzzle out which package versions are able to work together after some years have passed and packages evolved further and further. The 'wayback' package aims to make this process as painless and robust as possible by using 'MRAN's 'CRAN' snapshots to build local package libraries from way back.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: checkpoint
NeedsCompilation: no
Packaged: 2020-09-11 20:02:05 UTC; peter
Author: Peter Meissner [aut, cre], virtual7 [cph]
Repository: CRAN
Date/Publication: 2020-09-21 09:00:02 UTC

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New package splmm with initial version 1.0
Package: splmm
Type: Package
Title: Simultaneous Penalized Linear Mixed Effects Models
Version: 1.0
Date: 2020-08-12
Author: Luoying Yang, Tong Tong Wu
Maintainer: Luoying Yang <lyang19@u.rochester.edu>
Description: Contains functions that fit linear mixed-effects models for high-dimensional data (p>>n) with penalty for both the fixed effects and random effects for variable selection. The details of the algorithm can be found in Luoying Yang PhD thesis (available soon). The algorithm implementation is based on the R package 'lmmlasso'.
License: GPL-3
Imports: Rcpp (>= 1.0.1), emulator, miscTools, penalized, ggplot2, gridExtra, plot3D, MASS
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2020-09-11 15:10:22 UTC; lyang19
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2020-09-21 08:40:03 UTC

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New package SlidingWindows with initial version 0.1.4
Package: SlidingWindows
Type: Package
Title: Methods for Time Series Analysis
Description: A collection of functions to perform Detrended Fluctuation Analysis (DFA exponent), GUEDES et al. (2019) <doi:10.1016/j.physa.2019.04.132> , Detrended cross-correlation coefficient (RHODCCA), GUEDES & ZEBENDE (2019) <doi:10.1016/j.physa.2019.121286>, and Detrended Multiple cross-correlation coefficient (DMC), ZEBENDE & SILVA-FILHO (2018) <doi:10.1016/j.physa.2018.06.119>, both with sliding windows approach.
Version: 0.1.4
Date: 2020-09-11
Authors@R: c(person("Everaldo Freitas","Guedes", email = "efgestatistico@gmail.com", role = c("aut","cre"), comment = c(ORCID="0000-0002-2986-7367")), person("Ivan Costa da Cunha","Lima", email = "ivandacunhalima@gmail.com", role = c("aut"), comment = c(ORCID="0000-0002-4525-2346")), person("Gilney Figueira","Zebende", email = "gfzebende@hotmail", role = c("aut"), comment = c(ORCID="0000-0003-2420-9805")), person("Aloísio Machado","Silva-Filho", email = "aloisioestatistico@uefs.br", role = c("aut"), comment = c(ORCID="0000-0001-8250-1527")))
Maintainer: Everaldo Freitas Guedes <efgestatistico@gmail.com>
License: GPL-3
URL: https://github.com/efguedes/SlidingWindows
BugReports: https://github.com/efguedes/SlidingWindows
NeedsCompilation: no
Encoding: UTF-8
LazyData: true
Imports: stats, DCCA, PerformanceAnalytics, nonlinearTseries
Suggests: xts, zoo, quantmod
RoxygenNote: 7.1.1
Packaged: 2020-09-11 14:46:25 UTC; Everaldo Guedes
Author: Everaldo Freitas Guedes [aut, cre] (<https://orcid.org/0000-0002-2986-7367>), Ivan Costa da Cunha Lima [aut] (<https://orcid.org/0000-0002-4525-2346>), Gilney Figueira Zebende [aut] (<https://orcid.org/0000-0003-2420-9805>), Aloísio Machado Silva-Filho [aut] (<https://orcid.org/0000-0001-8250-1527>)
Repository: CRAN
Date/Publication: 2020-09-21 08:30:03 UTC

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New package ScriptMapR with initial version 0.0.2
Package: ScriptMapR
Type: Package
Title: R Script Visualization in Cytoscape
Version: 0.0.2
Author: Raphael Bonnet [aut, cre], Marion Guernoté [ctb], Terry Gouin [ctb], Maxime Laurens [ctb], Thibault Meekel [ctb], Jean-François Peyron[aut,ths]
Maintainer: Raphaël Bonnet <raphael.bonnet@univ-cotedazur.fr>
Description: Displays the content of a R script into the 'Cytoscape' network-visualization app <https://cytoscape.org/>.
BugReports: https://github.com/peyronlab/ScriptMapR/issues
Imports: RCy3, formatR, dplyr, stringr, utils, grDevices
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-11 15:54:30 UTC; raphael
Repository: CRAN
Date/Publication: 2020-09-21 08:50:02 UTC

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New package Neighboot with initial version 1.0.0
Package: Neighboot
Title: Neighborhood Bootstrap Method for RDS
Version: 1.0.0
Date: 2020-09-09
Author: Mamadou Yauck [aut, cre], Erica E. M. Moodie [aut]
Maintainer: Mamadou Yauck <mamadou.yauck@mcgill.ca>
Description: A bootstrap method for Respondent-Driven Sampling (RDS) that relies on the underlying structure of the RDS network to estimate uncertainty.
License: GPL-3
LazyData: true
RoxygenNote: 7.1.1
Imports: magrittr, RDStreeboot, igraph, RDS, dplyr
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-09-11 14:41:36 UTC; Utilisateur
Repository: CRAN
Date/Publication: 2020-09-21 08:30:07 UTC

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New package lightgbm with initial version 3.0.0
Package: lightgbm
Type: Package
Title: Light Gradient Boosting Machine
Version: 3.0.0
Date: 2020-09-11
Authors@R: c( person("Guolin", "Ke", email = "guolin.ke@microsoft.com", role = c("aut", "cre")), person("Damien", "Soukhavong", email = "damien.soukhavong@skema.edu", role = c("aut")), person("Yachen", "Yan", role = c("ctb")), person("James", "Lamb", email="jaylamb20@gmail.com", role = c("aut")), person("Qi", "Meng", role = c("aut")), person("Thomas", "Finley", role = c("aut")), person("Taifeng", "Wang", role = c("aut")), person("Wei", "Chen", role = c("aut")), person("Weidong", "Ma", role = c("aut")), person("Qiwei", "Ye", role = c("aut")), person("Tie-Yan", "Liu", role = c("aut")), person("Microsoft Corporation", role = c("cph")), person("Dropbox, Inc.", role = c("cph")) )
Description: Tree based algorithms can be improved by introducing boosting frameworks. 'LightGBM' is one such framework, based on Ke, Guolin et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>. This package offers an R interface to work with it. It is designed to be distributed and efficient with the following advantages: 1. Faster training speed and higher efficiency. 2. Lower memory usage. 3. Better accuracy. 4. Parallel learning supported. 5. Capable of handling large-scale data. In recognition of these advantages, 'LightGBM' has been widely-used in many winning solutions of machine learning competitions. Comparison experiments on public datasets suggest that 'LightGBM' can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, 'LightGBM' can achieve a linear speed-up in training time by using multiple machines.
Encoding: UTF-8
License: MIT + file LICENSE
URL: https://github.com/Microsoft/LightGBM
BugReports: https://github.com/Microsoft/LightGBM/issues
NeedsCompilation: yes
Biarch: true
Suggests: testthat
Depends: R (>= 3.5), R6 (>= 2.0)
Imports: data.table (>= 1.9.6), graphics, jsonlite (>= 1.0), Matrix (>= 1.1-0), methods, utils
SystemRequirements: C++11
RoxygenNote: 7.1.1
Packaged: 2020-09-11 15:05:31 UTC; jlamb
Author: Guolin Ke [aut, cre], Damien Soukhavong [aut], Yachen Yan [ctb], James Lamb [aut], Qi Meng [aut], Thomas Finley [aut], Taifeng Wang [aut], Wei Chen [aut], Weidong Ma [aut], Qiwei Ye [aut], Tie-Yan Liu [aut], Microsoft Corporation [cph], Dropbox, Inc. [cph]
Maintainer: Guolin Ke <guolin.ke@microsoft.com>
Repository: CRAN
Date/Publication: 2020-09-21 08:40:06 UTC

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New package GHap with initial version 2.0.0
Package: GHap
Type: Package
Title: Genome-Wide Haplotyping
Version: 2.0.0
Date: 2020-08-12
Author: Yuri Tani Utsunomiya, Marco Milanesi, Mario Barbato
Maintainer: Yuri Tani Utsunomiya <ytutsunomiya@gmail.com>
Description: Haplotype calling from phased marker data. Given user-defined haplotype blocks (HapBlock), the package identifies the different haplotype alleles (HapAllele) present in the data and scores sample haplotype allele genotypes (HapGenotype) based on HapAllele dose (i.e. 0, 1 or 2 copies). The output is not only useful for analyses that can handle multi-allelic markers, but is also conveniently formatted for existing pipelines intended for bi-allelic markers. The package was first described in Bioinformatics by Utsunomiya et al. (2016, <doi:10.1093/bioinformatics/btw356>). Since the v2 release, the package provides functions for unsupervised and supervised detection of ancestry tracks. The methods implemented in these functions were described in an article published in Methods in Ecology and Evolution by Utsunomiya et al. (2020, <doi:10.1111/2041-210X.13467>).
License: GPL (>= 2)
Imports: parallel (>= 3.4.4), Matrix (>= 1.2-16), methods (>= 3.4.4), lme4 (>= 1.1-21), e1071 (>= 1.7-0.1), class (>= 7.3-15), data.table (>= 1.12.6)
VignetteBuilder: R.rsp
Suggests: R.rsp
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-09-11 18:05:25 UTC; yuri
Repository: CRAN
Date/Publication: 2020-09-21 08:50:08 UTC

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Package vcd updated to version 1.4-8 with previous version 1.4-7 dated 2020-04-02

Title: Visualizing Categorical Data
Description: Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).
Author: David Meyer [aut, cre], Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Kurt Hornik [aut], Florian Gerber [ctb], Michael Friendly [ctb]
Maintainer: David Meyer <David.Meyer@R-project.org>

Diff between vcd versions 1.4-7 dated 2020-04-02 and 1.4-8 dated 2020-09-21

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Package TestDesign updated to version 1.1.2 with previous version 1.0.2 dated 2020-02-05

Title: Optimal Test Design Approach to Fixed and Adaptive Test Construction
Description: Use the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) <doi:10.1201/9781315117430> in constructing fixed and adaptive tests. Supports the following mixed-integer programming (MIP) solver packages: 'lpsymphony', 'Rsymphony', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see <https://www.gurobi.com/downloads/>. See vignette for installing 'Rsymphony' package on Mac systems.
Author: Seung W. Choi [aut, cre] (<https://orcid.org/0000-0003-4777-5420>), Sangdon Lim [aut] (<https://orcid.org/0000-0002-2988-014X>)
Maintainer: Seung W. Choi <schoi@austin.utexas.edu>

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Package DODR (with last version 0.99.2) was removed from CRAN

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Package precautionary updated to version 0.1-4 with previous version 0.1-3 dated 2020-09-13

Title: Safety Diagnostics for Dose-Escalation Trial Designs
Description: Enhances various R packages that support the design and simulation of phase 1 dose-escalation trials, adding diagnostics to examine the safety characteristics of these designs in light of expected inter-individual variation in pharmacokinetics and pharmacodynamics. See Norris (2020), "Retrospective analysis of a fatal dose-finding trial" <arXiv:2004.12755>.
Author: David C. Norris [aut, cre, cph] (<https://orcid.org/0000-0001-9593-6343>)
Maintainer: David C. Norris <david@precisionmethods.guru>

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Package pathfindR.data updated to version 1.1.0 with previous version 1.0.0 dated 2020-06-04

Title: Data Package for 'pathfindR'
Description: This is a data-only package, containing data needed to run the CRAN package 'pathfindR', a package for enrichment analysis utilizing active subnetworks. This package contains protein-protein interaction network data, data related to gene sets and example input/output data.
Author: Ege Ulgen [cre, cph] (<https://orcid.org/0000-0003-2090-3621>), Ozan Ozisik [aut] (<https://orcid.org/0000-0001-5980-8002>)
Maintainer: Ege Ulgen <egeulgen@gmail.com>

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Package nightmares updated to version 0.0.2 with previous version 0.0.1 dated 2020-09-09

Title: Common Analysis with Remote Sensing Data
Description: A collection of functions used in remote sensing analysis (e.g., conversion from digital numbers to radiance, reflectance, and temperature). It includes several algorithms to calculate the albedo: Liang (2000) <doi:10.1016/S0034-4257(00)00205-4>, Silva et al. (2016) <doi:10.32614/RJ-2016-051>, Tasumi et al. (2008) <doi:10.1061/(ASCE)1084-0699(2008)13:2(51)>, among others; and include functions to derive several spectral indices. Although the current version implements basic functions, it will be expandable to a more robust tool for water cycle modeling (e.g., to include surface runoff and evapotranspiration calculations) in the near future. This package is under development at the Institute about Natural Resources Research (INIRENA) from the Universidad Michoacana de San Nicolas de Hidalgo.
Author: Rafael Hernandez-Guzman [aut, cre] (<https://orcid.org/0000-0002-2711-9015>)
Maintainer: Rafael Hernandez-Guzman <rhernandez.g@gmail.com>

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Package RUVIIIC (with last version 1.0.17) was removed from CRAN

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2020-09-08 1.0.17
2020-09-04 1.0.16

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Package sdwd (with last version 1.0.4) was removed from CRAN

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2020-09-03 1.0.4

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Package bnlearn updated to version 4.6.1 with previous version 4.6 dated 2020-09-15

Title: Bayesian Network Structure Learning, Parameter Learning and Inference
Description: Bayesian network structure learning, parameter learning and inference. This package implements constraint-based (PC, GS, IAMB, Inter-IAMB, Fast-IAMB, MMPC, Hiton-PC, HPC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing and Tabu Search) and hybrid (MMHC, RSMAX2, H2PC) structure learning algorithms for discrete, Gaussian and conditional Gaussian networks, along with many score functions and conditional independence tests. The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented. Some utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple and advanced plots) are included, as well as support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries, cross-validation, bootstrap and model averaging. Development snapshots with the latest bugfixes are available from <https://www.bnlearn.com/>.
Author: Marco Scutari [aut, cre], Robert Ness [ctb]
Maintainer: Marco Scutari <marco.scutari@gmail.com>

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Sun, 20 Sep 2020

New package plfMA with initial version 1.0.5
Package: plfMA
Type: Package
Title: A GUI to View, Design and Export Various Graphs of Data
Version: 1.0.5
Date: 2020-09-19
Author: Dhammapal Bharne, Vaibhav Vindal
Maintainer: Dhammapal Bharne <dhammapalb@uohyd.ac.in>
Imports: limma, tcltk, RGtk2, gWidgets2, gWidgets2RGtk2, cairoDevice, grDevices, graphics, stats
Description: Provides a graphical user interface for viewing and designing various types of graphs of the data. The graphs can be saved in different formats of an image.
Depends: R (>= 3.1.1)
License: GPL-2
LazyLoad: yes
NeedsCompilation: no
Packaged: 2020-09-20 03:58:45 UTC; dhamma
Repository: CRAN
Date/Publication: 2020-09-20 22:20:03 UTC

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Package LTRCforests updated to version 0.5.1 with previous version 0.5.0 dated 2020-07-03

Title: Ensemble Methods for Survival Data with Time-Varying Covariates
Description: Implements the conditional inference forest and random survival forest algorithm to modeling left-truncated right-censored data with time-invariant covariates, and (left-truncated) right-censored survival data with time-varying covariates. It also provides functions to tune the parameters and evaluate the model fit. See Yao et al. (2020) <arXiv:2006.00567>.
Author: Weichi Yao [aut, cre], Halina Frydman [aut], Denis Larocque [aut], Jeffrey S. Simonoff [aut]
Maintainer: Weichi Yao <wy635@stern.nyu.edu>

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Package diveMove updated to version 1.5.2 with previous version 1.5.1 dated 2020-09-12

Title: Dive Analysis and Calibration
Description: Utilities to represent, visualize, filter, analyse, and summarize time-depth recorder (TDR) data. Miscellaneous functions for handling location data are also provided.
Author: Sebastian P. Luque <spluque@gmail.com>
Maintainer: Sebastian P. Luque <spluque@gmail.com>

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Package bayesdfa updated to version 0.1.6 with previous version 0.1.5 dated 2020-09-02

Title: Bayesian Dynamic Factor Analysis (DFA) with 'Stan'
Description: Implements Bayesian dynamic factor analysis with 'Stan'. Dynamic factor analysis is a dimension reduction tool for multivariate time series. 'bayesdfa' extends conventional dynamic factor models in several ways. First, extreme events may be estimated in the latent trend by modeling process error with a student-t distribution. Second, autoregressive and moving average components can be optionally included. Third, the estimated dynamic factors can be analyzed with hidden Markov models to evaluate support for latent regimes.
Author: Eric J. Ward [aut, cre], Sean C. Anderson [aut], Luis A. Damiano [aut], Mary E. Hunsicker, [ctb], Mike A. Litzow [ctb], Trustees of Columbia University [cph]
Maintainer: Eric J. Ward <eric.ward@noaa.gov>

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Package insight updated to version 0.9.6 with previous version 0.9.5 dated 2020-09-07

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>), Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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