Mon, 15 Apr 2019

Package Seurat updated to version 3.0.0 with previous version 2.3.4 dated 2018-07-17

Title: Tools for Single Cell Genomics
Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Butler A and Satija R (2017) <doi:10.1101/164889> for more details.
Author: Rahul Satija [aut] (<https://orcid.org/0000-0001-9448-8833>), Andrew Butler [aut] (<https://orcid.org/0000-0003-3608-0463>), Paul Hoffman [aut, cre] (<https://orcid.org/0000-0002-7693-8957>), Tim Stuart [aut] (<https://orcid.org/0000-0002-3044-0897>), Jeff Farrell [ctb], Shiwei Zheng [ctb] (<https://orcid.org/0000-0001-6682-6743>), Christoph Hafemeister [ctb] (<https://orcid.org/0000-0001-6365-8254>), Patrick Roelli [ctb]
Maintainer: Paul Hoffman <nygcSatijalab@nygenome.org>

Diff between Seurat versions 2.3.4 dated 2018-07-17 and 3.0.0 dated 2019-04-15

 Seurat-2.3.4/Seurat/R/alignment.R                                 |only
 Seurat-2.3.4/Seurat/R/as.R                                        |only
 Seurat-2.3.4/Seurat/R/cluster_determination.R                     |only
 Seurat-2.3.4/Seurat/R/cluster_determination_internal.R            |only
 Seurat-2.3.4/Seurat/R/cluster_validation.R                        |only
 Seurat-2.3.4/Seurat/R/conversion.R                                |only
 Seurat-2.3.4/Seurat/R/deprecated_functions.R                      |only
 Seurat-2.3.4/Seurat/R/differential_expression_internal.R          |only
 Seurat-2.3.4/Seurat/R/dimensional_reduction_internal.R            |only
 Seurat-2.3.4/Seurat/R/dimensional_reduction_utilities.R           |only
 Seurat-2.3.4/Seurat/R/interaction.R                               |only
 Seurat-2.3.4/Seurat/R/jackstraw.R                                 |only
 Seurat-2.3.4/Seurat/R/jackstraw_internal.R                        |only
 Seurat-2.3.4/Seurat/R/multi_modal.R                               |only
 Seurat-2.3.4/Seurat/R/not_used_yet.R                              |only
 Seurat-2.3.4/Seurat/R/plotting.R                                  |only
 Seurat-2.3.4/Seurat/R/plotting_internal.R                         |only
 Seurat-2.3.4/Seurat/R/plotting_utilities.R                        |only
 Seurat-2.3.4/Seurat/R/preprocessing_internal.R                    |only
 Seurat-2.3.4/Seurat/R/printing_utilities.R                        |only
 Seurat-2.3.4/Seurat/R/scoring.R                                   |only
 Seurat-2.3.4/Seurat/R/seurat.R                                    |only
 Seurat-2.3.4/Seurat/R/snn.R                                       |only
 Seurat-2.3.4/Seurat/R/spatial.R                                   |only
 Seurat-2.3.4/Seurat/R/spatial_internal.R                          |only
 Seurat-2.3.4/Seurat/R/tSNE_project.R                              |only
 Seurat-2.3.4/Seurat/R/utilities_internal.R                        |only
 Seurat-2.3.4/Seurat/man/AddImputedScore.Rd                        |only
 Seurat-2.3.4/Seurat/man/AddSamples.Rd                             |only
 Seurat-2.3.4/Seurat/man/AddSmoothedScore.Rd                       |only
 Seurat-2.3.4/Seurat/man/AlignSubspace.Rd                          |only
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 Seurat-2.3.4/Seurat/man/AverageDetectionRate.Rd                   |only
 Seurat-2.3.4/Seurat/man/AveragePCA.Rd                             |only
 Seurat-2.3.4/Seurat/man/BatchGene.Rd                              |only
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 Seurat-2.3.4/Seurat/man/BuildRFClassifier.Rd                      |only
 Seurat-2.3.4/Seurat/man/BuildSNN.Rd                               |only
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 Seurat-2.3.4/Seurat/man/CalcVarExpRatio.Rd                        |only
 Seurat-2.3.4/Seurat/man/CellPlot.Rd                               |only
 Seurat-2.3.4/Seurat/man/ClassifyCells.Rd                          |only
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 Seurat-2.3.4/Seurat/man/CombineIdent.Rd                           |only
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 Seurat-2.3.4/Seurat/man/DotPlotOld.Rd                             |only
 Seurat-2.3.4/Seurat/man/ExtractField.Rd                           |only
 Seurat-2.3.4/Seurat/man/FastWhichCells.Rd                         |only
 Seurat-2.3.4/Seurat/man/FeatureHeatmap.Rd                         |only
 Seurat-2.3.4/Seurat/man/FeatureLocator.Rd                         |only
 Seurat-2.3.4/Seurat/man/FilterCells.Rd                            |only
 Seurat-2.3.4/Seurat/man/FindAllMarkersNode.Rd                     |only
 Seurat-2.3.4/Seurat/man/FindGeneTerms.Rd                          |only
 Seurat-2.3.4/Seurat/man/FindMarkersNode.Rd                        |only
 Seurat-2.3.4/Seurat/man/FindVariableGenes.Rd                      |only
 Seurat-2.3.4/Seurat/man/FitGeneK.Rd                               |only
 Seurat-2.3.4/Seurat/man/GenePlot.Rd                               |only
 Seurat-2.3.4/Seurat/man/GenesInCluster.Rd                         |only
 Seurat-2.3.4/Seurat/man/GetCellEmbeddings.Rd                      |only
 Seurat-2.3.4/Seurat/man/GetCentroids.Rd                           |only
 Seurat-2.3.4/Seurat/man/GetClusters.Rd                            |only
 Seurat-2.3.4/Seurat/man/GetDimReduction.Rd                        |only
 Seurat-2.3.4/Seurat/man/GetGeneLoadings.Rd                        |only
 Seurat-2.3.4/Seurat/man/GetIdent.Rd                               |only
 Seurat-2.3.4/Seurat/man/ICAEmbed.Rd                               |only
 Seurat-2.3.4/Seurat/man/ICALoad.Rd                                |only
 Seurat-2.3.4/Seurat/man/ICAPlot.Rd                                |only
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 Seurat-2.3.4/Seurat/man/ICTopCells.Rd                             |only
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 Seurat-2.3.4/Seurat/man/InitialMapping.Rd                         |only
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 Seurat-2.3.4/Seurat/man/MakeSparse.Rd                             |only
 Seurat-2.3.4/Seurat/man/MarkerTest.Rd                             |only
 Seurat-2.3.4/Seurat/man/MatrixRowShuffle.Rd                       |only
 Seurat-2.3.4/Seurat/man/MergeNode.Rd                              |only
 Seurat-2.3.4/Seurat/man/MergeSeurat.Rd                            |only
 Seurat-2.3.4/Seurat/man/MetageneBicorPlot.Rd                      |only
 Seurat-2.3.4/Seurat/man/MultiModal_CCA.Rd                         |only
 Seurat-2.3.4/Seurat/man/MultiModal_CIA.Rd                         |only
 Seurat-2.3.4/Seurat/man/NegBinomDETest.Rd                         |only
 Seurat-2.3.4/Seurat/man/NegBinomRegDETest.Rd                      |only
 Seurat-2.3.4/Seurat/man/NumberClusters.Rd                         |only
 Seurat-2.3.4/Seurat/man/OldDoHeatmap.Rd                           |only
 Seurat-2.3.4/Seurat/man/PCAEmbed.Rd                               |only
 Seurat-2.3.4/Seurat/man/PCALoad.Rd                                |only
 Seurat-2.3.4/Seurat/man/PCAPlot.Rd                                |only
 Seurat-2.3.4/Seurat/man/PCElbowPlot.Rd                            |only
 Seurat-2.3.4/Seurat/man/PCHeatmap.Rd                              |only
 Seurat-2.3.4/Seurat/man/PCTopCells.Rd                             |only
 Seurat-2.3.4/Seurat/man/PCTopGenes.Rd                             |only
 Seurat-2.3.4/Seurat/man/PoissonDETest.Rd                          |only
 Seurat-2.3.4/Seurat/man/PrintAlignSubspaceParams.Rd               |only
 Seurat-2.3.4/Seurat/man/PrintCCAParams.Rd                         |only
 Seurat-2.3.4/Seurat/man/PrintCalcParams.Rd                        |only
 Seurat-2.3.4/Seurat/man/PrintCalcVarExpRatioParams.Rd             |only
 Seurat-2.3.4/Seurat/man/PrintDMParams.Rd                          |only
 Seurat-2.3.4/Seurat/man/PrintDim.Rd                               |only
 Seurat-2.3.4/Seurat/man/PrintFindClustersParams.Rd                |only
 Seurat-2.3.4/Seurat/man/PrintICA.Rd                               |only
 Seurat-2.3.4/Seurat/man/PrintICAParams.Rd                         |only
 Seurat-2.3.4/Seurat/man/PrintPCA.Rd                               |only
 Seurat-2.3.4/Seurat/man/PrintPCAParams.Rd                         |only
 Seurat-2.3.4/Seurat/man/PrintSNNParams.Rd                         |only
 Seurat-2.3.4/Seurat/man/PrintTSNEParams.Rd                        |only
 Seurat-2.3.4/Seurat/man/ProjectPCA.Rd                             |only
 Seurat-2.3.4/Seurat/man/PurpleAndYellow.Rd                        |only
 Seurat-2.3.4/Seurat/man/RefinedMapping.Rd                         |only
 Seurat-2.3.4/Seurat/man/RemoveFromTable.Rd                        |only
 Seurat-2.3.4/Seurat/man/RenameIdent.Rd                            |only
 Seurat-2.3.4/Seurat/man/ReorderIdent.Rd                           |only
 Seurat-2.3.4/Seurat/man/RunDiffusion.Rd                           |only
 Seurat-2.3.4/Seurat/man/RunMultiCCA.Rd                            |only
 Seurat-2.3.4/Seurat/man/RunPHATE.Rd                               |only
 Seurat-2.3.4/Seurat/man/SaveClusters.Rd                           |only
 Seurat-2.3.4/Seurat/man/ScaleDataR.Rd                             |only
 Seurat-2.3.4/Seurat/man/SetAllIdent.Rd                            |only
 Seurat-2.3.4/Seurat/man/SetClusters.Rd                            |only
 Seurat-2.3.4/Seurat/man/SetDimReduction.Rd                        |only
 Seurat-2.3.4/Seurat/man/SetIdent.Rd                               |only
 Seurat-2.3.4/Seurat/man/Seurat-deprecated.Rd                      |only
 Seurat-2.3.4/Seurat/man/Shuffle.Rd                                |only
 Seurat-2.3.4/Seurat/man/SplitDotPlotGG.Rd                         |only
 Seurat-2.3.4/Seurat/man/StashIdent.Rd                             |only
 Seurat-2.3.4/Seurat/man/SubsetByPredicate.Rd                      |only
 Seurat-2.3.4/Seurat/man/SubsetColumn.Rd                           |only
 Seurat-2.3.4/Seurat/man/SubsetRow.Rd                              |only
 Seurat-2.3.4/Seurat/man/TSNEPlot.Rd                               |only
 Seurat-2.3.4/Seurat/man/TobitTest.Rd                              |only
 Seurat-2.3.4/Seurat/man/TransferIdent.Rd                          |only
 Seurat-2.3.4/Seurat/man/ValidateClusters.Rd                       |only
 Seurat-2.3.4/Seurat/man/ValidateSpecificClusters.Rd               |only
 Seurat-2.3.4/Seurat/man/VariableGenePlot.Rd                       |only
 Seurat-2.3.4/Seurat/man/VizDimReduction.Rd                        |only
 Seurat-2.3.4/Seurat/man/VizICA.Rd                                 |only
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 Seurat-2.3.4/Seurat/tests/testthat/test_alignment.R               |only
 Seurat-2.3.4/Seurat/tests/testthat/test_cluster_determination.R   |only
 Seurat-2.3.4/Seurat/tests/testthat/test_differential_expression.R |only
 Seurat-2.3.4/Seurat/tests/testthat/test_interaction.R             |only
 Seurat-2.3.4/Seurat/tests/testthat/test_seurat_object.R           |only
 Seurat-2.3.4/Seurat/tests/testthat/test_snn.R                     |only
 Seurat-3.0.0/Seurat/DESCRIPTION                                   |   53 
 Seurat-3.0.0/Seurat/MD5                                           |  389 -
 Seurat-3.0.0/Seurat/NAMESPACE                                     |  619 +-
 Seurat-3.0.0/Seurat/NEWS.md                                       |   18 
 Seurat-3.0.0/Seurat/R/RcppExports.R                               |   40 
 Seurat-3.0.0/Seurat/R/clustering.R                                |only
 Seurat-3.0.0/Seurat/R/convenience.R                               |only
 Seurat-3.0.0/Seurat/R/data.R                                      |   24 
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 Seurat-3.0.0/Seurat/README.md                                     |   21 
 Seurat-3.0.0/Seurat/data/pbmc_small.rda                           |binary
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 Seurat-3.0.0/Seurat/man/AddMetaData.Rd                            |   48 
 Seurat-3.0.0/Seurat/man/AddModuleScore.Rd                         |   43 
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 Seurat-3.0.0/Seurat/man/AugmentPlot.Rd                            |   27 
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 Seurat-3.0.0/Seurat/man/CaseMatch.Rd                              |    2 
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 Seurat-3.0.0/Seurat/man/RunCCA.Rd                                 |   70 
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Package PwrGSD updated to version 2.3.1 with previous version 2.3 dated 2018-03-26

Title: Power in a Group Sequential Design
Description: Tools for the evaluation of interim analysis plans for sequentially monitored trials on a survival endpoint; tools to construct efficacy and futility boundaries, for deriving power of a sequential design at a specified alternative, template for evaluating the performance of candidate plans at a set of time varying alternatives. See Izmirlian, G. (2014) <doi:10.4310/SII.2014.v7.n1.a4>.
Author: Grant Izmirlian <izmirlig@mail.nih.gov>
Maintainer: Grant Izmirlian <izmirlig@mail.nih.gov>

Diff between PwrGSD versions 2.3 dated 2018-03-26 and 2.3.1 dated 2019-04-15

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More information about PwrGSD at CRAN
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Package island updated to version 0.2.4 with previous version 0.2.3 dated 2019-03-21

Title: Stochastic Island Biogeography Theory Made Easy
Description: Tools to develop stochastic models based on the Theory of Island Biogeography (TIB) of MacArthur and Wilson (1967) <DOI:10.1023/A:1016393430551> and extensions. The package implements methods to estimate colonization and extinction rates (including environmental variables) given presence-absence data, simulate community assembly, and perform model selection.
Author: Vicente Jimenez [aut, cre], David Alonso [aut]
Maintainer: Vicente Jimenez <vicente.jimenez.ontiveros@gmail.com>

Diff between island versions 0.2.3 dated 2019-03-21 and 0.2.4 dated 2019-04-15

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More information about island at CRAN
Permanent link

New package Irescale with initial version 0.2.6
Package: Irescale
Type: Package
Title: Calculate and Scale Moran's I
Version: 0.2.6
Author: Ivan Fuentes, Thomas DeWitt, Thomas Ioerger, Michael Bishop
Maintainer: Ivan Fuentes <jivfur@tamu.edu>
Description: Provides a scaling method to obtain a standardized Moran's I measure. Moran's I is a measure for the spatial autocorrelation of a data set, it gives a measure of similarity between data and its surrounding. The range of this value must be [-1,1], but this does not happen in practice. This package scale the Moran's I value and map it into the theoretical range of [-1,1]. Once the Moran's I value is rescaled, it facilitates the comparison between projects, for instance, a researcher can calculate Moran's I in a city in China, with a sample size of n1 and area of interest a1. Another researcher runs a similar experiment in a city in Mexico with different sample size, n2, and an area of interest a2. Due to the differences between the conditions, it is not possible to compare Moran's I in a straightforward way. In this version of the package, the spatial autocorrelation Moran's I is calculated as proposed in Chen(2009) <arXiv:1606.03658>.
License: GPL (>= 2)
URL: https://github.tamu.edu/jivfur/Irescale
Encoding: UTF-8
LazyData: true
Imports: Rcpp, ggplot2, sp, e1071, graphics, grDevices, stats, utils,Rdpack
RoxygenNote: 6.1.1
RdMacros: Rdpack
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-15 20:34:16 UTC; jivfur
Repository: CRAN
Date/Publication: 2019-04-15 21:22:56 UTC

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New package allelematch with initial version 2.5.1
Package: allelematch
Title: Identifying Unique Multilocus Genotypes where Genotyping Error and Missing Data may be Present
Version: 2.5.1
Authors@R: c( person("Paul", "Galpern", email = "pgalpern@gmail.com", role = "aut"), person("Todd", "Cross", email = "todd.cross@gmail.com", role = c("cre", "ctb")), person("Katie", "Zarn", email = "katie.zarn@gmail.com", role = "ctb") )
Maintainer: Todd Cross <todd.cross@gmail.com>
Description: Tools for the identification of unique of multilocus genotypes when both genotyping error and missing data may be present. The package is targeted at those working with large datasets and databases containing multiple samples of each individual, a situation that is common in conservation genetics, and particularly in non-invasive wildlife sampling applications. Functions explicitly incorporate missing data, and can tolerate allele mismatches created by genotyping error. If you use this tool, please cite the package using the journal article in Molecular Ecology Resources (Galpern et al., 2012). Please use citation('allelematch') to call the full citation. For users with access to the associated journal article, tutorial material is also available as supplementary material to the article describing this software, the citation for which can be called using citation('allelematch').
Depends: graphics, stats, utils
Imports: dynamicTreeCut
Suggests: R.rsp
VignetteBuilder: R.rsp
License: GPL-3
LazyLoad: yes
Packaged: 2019-04-15 16:01:22 UTC; tbcross
NeedsCompilation: no
Repository: CRAN
Author: Paul Galpern [aut], Todd Cross [cre, ctb], Katie Zarn [ctb]
Date/Publication: 2019-04-15 21:22:47 UTC

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Package lpdensity updated to version 0.2.3 with previous version 0.2.2 dated 2017-07-09

Title: Local Polynomial Density Estimation and Inference
Description: Without imposing stringent distributional assumptions or shape restrictions, nonparametric density estimation has been popular in economics and other social sciences for counterfactual analysis, program evaluation, and policy recommendations. This package implements a novel density estimator based on local polynomial regression, documented in Cattaneo, Jansson and Ma (2019) <arXiv:1811.11512>: lpdensity() to construct local polynomial based density (and derivatives) estimator; lpbwdensity() to perform data-driven bandwidth selection; and lpdensity.plot() for density plot with robust confidence interval.
Author: Matias D. Cattaneo, Michael Jansson, Xinwei Ma
Maintainer: Xinwei Ma <xinweima@umich.edu>

Diff between lpdensity versions 0.2.2 dated 2017-07-09 and 0.2.3 dated 2019-04-15

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Package projects updated to version 1.1.1 with previous version 1.1.0 dated 2019-04-15

Title: A Project Infrastructure for Researchers
Description: Provides a project infrastructure with a focus on manuscript creation. Creates a project folder with a single command, containing subdirectories for specific components, templates for manuscripts, and so on.
Author: Nik Krieger [aut, cre], Adam Perzynski [aut], Jarrod Dalton [aut]
Maintainer: Nik Krieger <nk@case.edu>

Diff between projects versions 1.1.0 dated 2019-04-15 and 1.1.1 dated 2019-04-15

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Package miceadds updated to version 3.2-48 with previous version 3.1-37 dated 2019-03-18

Title: Some Additional Multiple Imputation Functions, Especially for 'mice'
Description: Contains functions for multiple imputation which complements existing functionality in R. In particular, several imputation methods for the mice package (van Buuren & Groothuis-Oudshoorn, 2011, <doi:10.18637/jss.v045.i03>) are included. Main features of the miceadds package include plausible value imputation (Mislevy, 1991, <doi:10.1007/BF02294457>), multilevel imputation for variables at any level or with any number of hierarchical and non-hierarchical levels (Grund, Luedtke & Robitzsch, 2018, <doi:10.1177/1094428117703686>; van Buuren, 2018, Ch.7, <doi:10.1201/9780429492259>), imputation using partial least squares (PLS) for high dimensional predictors (Robitzsch, Pham & Yanagida, 2016), nested multiple imputation (Rubin, 2003, <doi:10.1111/1467-9574.00217>) and substantive model compatible imputation (Bartlett et al., 2015, <doi:10.1177/0962280214521348>).
Author: Alexander Robitzsch [aut, cre], Simon Grund [aut], Thorsten Henke [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between miceadds versions 3.1-37 dated 2019-03-18 and 3.2-48 dated 2019-04-15

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New package glcm with initial version 1.6.3
Package: glcm
Version: 1.6.3
Date: 2019-04-15
Title: Calculate Textures from Grey-Level Co-Occurrence Matrices (GLCMs)
Authors@R: person("Alex", "Zvoleff", email="azvoleff@conservation.org", role=c("aut", "cre"))
Maintainer: Alex Zvoleff <azvoleff@conservation.org>
Depends: R (>= 2.10.0)
Imports: Rcpp (>= 0.11.0)
Suggests: raster, testthat (>= 0.8.0)
LinkingTo: Rcpp, RcppArmadillo
Description: Enables calculation of image textures (Haralick 1973) <doi:10.1109/TSMC.1973.4309314> from grey-level co-occurrence matrices (GLCMs). Supports processing images that cannot fit in memory.
License: GPL (>= 3)
URL: http://www.azvoleff.com/glcm
BugReports: https://github.com/azvoleff/glcm/issues
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-04-15 15:40:58 UTC; azvol
Author: Alex Zvoleff [aut, cre]
Repository: CRAN
Date/Publication: 2019-04-15 18:12:44 UTC

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Package Brq updated to version 2.5 with previous version 2.4 dated 2019-04-08

Title: Bayesian Analysis of Quantile Regression Models
Description: Bayesian estimation and variable selection for quantile regression models.
Author: Rahim Alhamzawi
Maintainer: Rahim Alhamzawi (University of Al-Qadisiyah) <rahim.alhamzawi@qu.edu.iq>

Diff between Brq versions 2.4 dated 2019-04-08 and 2.5 dated 2019-04-15

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Package Ternary updated to version 1.1.0 with previous version 1.0.2 dated 2018-10-30

Title: An R Package for Creating Ternary Plots
Description: Plots ternary diagrams using the standard graphics functions. An alternative to 'ggtern', which uses the 'ggplot2' family of plotting functions.
Author: Martin R. Smith [aut, cre, cph] (<https://orcid.org/0000-0001-5660-1727>)
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

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Package robCompositions updated to version 2.1.0 with previous version 2.0.10 dated 2019-02-19

Title: Compositional Data Analysis
Description: Methods for analysis of compositional data including robust methods, imputation, methods to replace rounded zeros, (robust) outlier detection for compositional data, (robust) principal component analysis for compositional data, (robust) factor analysis for compositional data, (robust) discriminant analysis for compositional data (Fisher rule), robust regression with compositional predictors and (robust) Anderson-Darling normality tests for compositional data as well as popular log-ratio transformations (addLR, cenLR, isomLR, and their inverse transformations). In addition, visualisation and diagnostic tools are implemented as well as high and low-level plot functions for the ternary diagram.
Author: Matthias Templ [aut, cre], Karel Hron [aut], Peter Filzmoser [aut], Kamila Facevicova [ctb], Petra Kynclova [ctb], Jan Walach [ctb], Veronika Pintar [ctb], Jiajia Chen [ctb], Dominika Miksova [ctb]
Maintainer: Matthias Templ <matthias.templ@gmail.com>

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Package Irescale (with last version 0.1.4) was removed from CRAN

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

2019-04-12 0.1.4

Permanent link
Package Rserve updated to version 1.7-3.1 with previous version 1.7-3 dated 2013-08-21

Title: Binary R server
Description: Rserve acts as a socket server (TCP/IP or local sockets) which allows binary requests to be sent to R. Every connection has a separate workspace and working directory. Client-side implementations are available for popular languages such as C/C++ and Java, allowing any application to use facilities of R without the need of linking to R code. Rserve supports remote connection, user authentication and file transfer. A simple R client is included in this package as well.
Author: Simon Urbanek <Simon.Urbanek@r-project.org>
Maintainer: Simon Urbanek <Simon.Urbanek@r-project.org>

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Package JavaGD updated to version 0.6-1.1 with previous version 0.6-1 dated 2012-09-13

Title: Java Graphics Device
Description: Graphics device routing all graphics commands to a Java program. The actual functionality of the JavaGD depends on the Java-side implementation. Simple AWT and Swing implementations are included.
Author: Simon Urbanek <Simon.Urbanek@R-project.org>
Maintainer: Simon Urbanek <Simon.Urbanek@R-project.org>

Diff between JavaGD versions 0.6-1 dated 2012-09-13 and 0.6-1.1 dated 2019-04-15

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Package FastRWeb updated to version 1.1-1.1 with previous version 1.1-1 dated 2015-07-29

Title: Fast Interactive Framework for Web Scripting Using R
Description: Infrastrcture for creating rich, dynamic web content using R scripts while maintaining very fast response time.
Author: Simon Urbanek <Simon.Urbanek@r-project.org>, Jeffrey Horner <jeffrey.horner@gmail.com>
Maintainer: Simon Urbanek <Simon.Urbanek@r-project.org>

Diff between FastRWeb versions 1.1-1 dated 2015-07-29 and 1.1-1.1 dated 2019-04-15

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Package workflowr updated to version 1.3.0 with previous version 1.2.0 dated 2019-02-14

Title: A Framework for Reproducible and Collaborative Data Science
Description: Provides a workflow for your analysis projects by combining literate programming ('knitr' and 'rmarkdown') and version control ('Git', via 'git2r') to generate a website containing time-stamped, versioned, and documented results.
Author: John Blischak [aut, cre] (<https://orcid.org/0000-0003-2634-9879>), Peter Carbonetto [aut] (<https://orcid.org/0000-0003-1144-6780>), Matthew Stephens [aut] (<https://orcid.org/0000-0001-5397-9257>), Luke Zappia [ctb] (Instructions for hosting with GitLab), Pierre Formont [ctb] (Support for hosting with Shiny Server), Tim Trice [ctb] (Instructions for sharing common code), Jiaxiang Li [ctb] (Function wflow_toc() to create table of contents)
Maintainer: John Blischak <jdblischak@uchicago.edu>

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Package MFDFA updated to version 1.1 with previous version 1.0 dated 2018-04-18

Title: MultiFractal Detrended Fluctuation Analysis
Description: Contains the MultiFractal Detrended Fluctuation Analysis (MFDFA), MultiFractal Detrended Cross-Correlation Analysis (MFXDFA), and the Multiscale Multifractal Analysis (MMA). The MFDFA() function proposed in this package was used in Laib et al. (<doi:10.1016/j.chaos.2018.02.024> and <doi:10.1063/1.5022737>). See references for more information. Interested users can find a parallel version of the MFDFA() function on GitHub.
Author: Mohamed Laib [aut, cre], Luciano Telesca [aut], Mikhail Kanevski [aut]
Maintainer: Mohamed Laib <laib.med@gmail.com>

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Package coda.base updated to version 0.1.12 with previous version 0.1.11 dated 2019-01-15

Title: A Basic Set of Functions for Compositional Data Analysis
Description: A minimum set of functions to perform compositional data analysis using the log-ratio approach introduced by John Aitchison (1982) <http://www.jstor.org/stable/2345821>. Main functions have been implemented in c++ for better performance.
Author: Marc Comas-Cufí [aut, cre]
Maintainer: Marc Comas-Cufí <mcomas@imae.udg.edu>

Diff between coda.base versions 0.1.11 dated 2019-01-15 and 0.1.12 dated 2019-04-15

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Package clipr updated to version 0.6.0 with previous version 0.5.0 dated 2019-01-11

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

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Package BDgraph updated to version 2.58 with previous version 2.57 dated 2019-04-07

Title: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC
Description: Statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Letac et al. (2018) <arXiv:1706.04416>, Dobra and Mohammadi (2018) <doi:10.1214/18-AOAS1164>, Mohammadi et al. (2017) <doi:10.1111/rssc.12171>. To speed up the computations, the BDMCMC sampling algorithms are implemented in parallel using OpenMP in C++.
Author: Reza Mohammadi [aut, cre] <https://orcid.org/0000-0001-9538-0648>, Ernst Wit [aut] <https://orcid.org/0000-0002-3671-9610>, Adrian Dobra [ctb]
Maintainer: Reza Mohammadi <a.mohammadi@uva.nl>

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Package trip updated to version 1.6.0 with previous version 1.5.0 dated 2016-10-18

Title: Tools for the Analysis of Animal Track Data
Description: Functions for accessing and manipulating spatial data for animal tracking, with straightforward coercion from and to other formats. Filter for speed and create time spent maps from animal track data. There are coercion methods to convert between 'trip' and 'ltraj' from 'adehabitatLT', and between 'trip' and 'psp' and 'ppp' from 'spatstat'. Trip objects can be created from raw or grouped data frames, and from types in the 'sp', 'sf', 'amt', 'trackeR', 'mousetrap', and other packages.
Author: Michael D. Sumner [aut, cre], Sebastian Luque [ctb], Anthony Fischbach [ctb], Tomislav Hengl [ctb]
Maintainer: Michael D. Sumner <mdsumner@gmail.com>

Diff between trip versions 1.5.0 dated 2016-10-18 and 1.6.0 dated 2019-04-15

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Package NNS updated to version 0.3.9 with previous version 0.3.8.8 dated 2019-03-04

Title: Nonlinear Nonparametric Statistics
Description: Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization and Stochastic dominance. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).
Author: Fred Viole
Maintainer: Fred Viole <ovvo.financial.systems@gmail.com>

Diff between NNS versions 0.3.8.8 dated 2019-03-04 and 0.3.9 dated 2019-04-15

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Package upwaver updated to version 1.2.0 with previous version 1.1.0 dated 2018-04-24

Title: Access 'Upwave' API
Description: 'Upwave' <https://www.upwave.io/> is a task management app organising tasks on boards and cards. 'upwaver' is a wrapper around the 'Upwave' API <https://upwavehq.github.io/api/> that allows listing and updating those boards and cards.
Author: Adrian Staempfli, Christoph Strauss, Fabian Leuthold, Michael Schmid
Maintainer: Adrian Staempfli <adrian.staempfli@fhsg.ch>

Diff between upwaver versions 1.1.0 dated 2018-04-24 and 1.2.0 dated 2019-04-15

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Package funtimes updated to version 6.1 with previous version 6.0 dated 2019-02-17

Title: Functions for Time Series Analysis
Description: Includes non-parametric estimators and tests for time series analysis. The functions are to test for presence of possibly non-monotonic trends and for synchronism of trends in multiple time series, using modern bootstrap techniques and robust non-parametric difference-based estimators.
Author: Vyacheslav Lyubchich [aut, cre], Yulia R. Gel [aut], Calvin Chu [ctb], Xin Huang [ctb], Ethan D. Schaeffer [ctb], Srishti Vishwakarma [ctb], Xingyu Wang [ctb]
Maintainer: Vyacheslav Lyubchich <lyubchic@umces.edu>

Diff between funtimes versions 6.0 dated 2019-02-17 and 6.1 dated 2019-04-15

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Package BatchGetSymbols updated to version 2.5 with previous version 2.4 dated 2019-03-23

Title: Downloads and Organizes Financial Data for Multiple Tickers
Description: Makes it easy to download a large number of trade data from Yahoo Finance <https://finance.yahoo.com/>.
Author: Marcelo Perlin [aut, cre]
Maintainer: Marcelo Perlin <marceloperlin@gmail.com>

Diff between BatchGetSymbols versions 2.4 dated 2019-03-23 and 2.5 dated 2019-04-15

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Package projects updated to version 1.1.0 with previous version 0.1.0 dated 2018-12-30

Title: A Project Infrastructure for Researchers
Description: Provides a project infrastructure with a focus on manuscript creation. Creates a project folder with a single command, containing subdirectories for specific components, templates for manuscripts, and so on.
Author: Nik Krieger [aut, cre], Adam Perzynski [aut], Jarrod Dalton [aut]
Maintainer: Nik Krieger <nk@case.edu>

Diff between projects versions 0.1.0 dated 2018-12-30 and 1.1.0 dated 2019-04-15

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Package rnrfa updated to version 2.0 with previous version 1.5.0 dated 2018-11-20

Title: UK National River Flow Archive Data from R
Description: Utility functions to retrieve data from the UK National River Flow Archive (<http://nrfa.ceh.ac.uk/>). The package contains R wrappers to the UK NRFA data temporary-API. There are functions to retrieve stations falling in a bounding box, to generate a map and extracting time series and general information.
Author: Claudia Vitolo [aut, cre] (<https://orcid.org/0000-0002-4252-1176>), Matthew Fry [ctb] (Matthew supervised the unofficial API integration.), Wouter Buytaert [ctb] (This package is part of Claudia Vitolo's PhD work and Wouter is the supervisor.), Michael Spencer [ctb] (Michael updated the function osg_parse to work with grid references of different lengths.), Tobias Gauster [ctb] (Tobias improved the function osg_parse introducing vectorisation)
Maintainer: Claudia Vitolo <cvitolodev@gmail.com>

Diff between rnrfa versions 1.5.0 dated 2018-11-20 and 2.0 dated 2019-04-15

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New package DiSSMod with initial version 1.0.0
Package: DiSSMod
Type: Package
Title: Fitting Sample Selection Models for Discrete Response Variables
Version: 1.0.0
Date: 2019-04-15
Author: Sang Kyu Lee <lsk0816@gmail.com>, Adelchi Azzalini <adelchi.azzalini@unipd.it>, Hyoung-Moon Kim <hmk966a@gmail.com>
Maintainer: Sang Kyu Lee <lsk0816@gmail.com>
Description: Tools to fit sample selection models in case of discrete response variables, through a parametric formulation which represents a natural extension of the well-known Heckman selection model are provided in the package. The response variable can be of Bernoulli, Poisson or Negative Binomial type. The sample selection mechanism allows to choose among a Normal, Logistic or Gumbel distribution.
Depends: R (>= 2.10)
Imports: sfsmisc, matrixcalc, psych, MASS
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-15 10:14:28 UTC; user
Repository: CRAN
Date/Publication: 2019-04-15 10:42:40 UTC

More information about DiSSMod at CRAN
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Package word.alignment updated to version 1.1 with previous version 1.0.9 dated 2018-02-21

Title: Computing Word Alignment Using IBM Model 1 (and Symmetrization) for a Given Parallel Corpus and Its Evaluation
Description: For a given Sentence-Aligned Parallel Corpus, it aligns words for each sentence pair. It considers one-to-many and symmetrization alignments. Moreover, it evaluates the quality of word alignment based on this package and some other software. It also builds an automatic dictionary of two languages based on given parallel corpus.
Author: Neda Daneshagr and Majid Sarmad.
Maintainer: Neda Daneshgar<ne_da978@stu-mail.um.ac.ir>

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Package lsbclust updated to version 1.1 with previous version 1.0.5 dated 2018-04-19

Title: Least-Squares Bilinear Clustering for Three-Way Data
Description: Functions for performing least-squares bilinear clustering of three-way data. The method uses the bilinear decomposition (or bi-additive model) to model two-way matrix slices while clustering over the third way. Up to four different types of clusters are included, one for each term of the bilinear decomposition. In this way, matrices are clustered simultaneously on (a subset of) their overall means, row margins, column margins and row-column interactions. The orthogonality of the bilinear model results in separability of the joint clustering problem into four separate ones. Three of these sub-problems are specific k-means problems, while a special algorithm is implemented for the interactions. Plotting methods are provided, including biplots for the low-rank approximations of the interactions.
Author: Pieter Schoonees [aut, cre], Patrick Groenen [ctb]
Maintainer: Pieter Schoonees <schoonees@gmail.com>

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Package clustermq updated to version 0.8.7 with previous version 0.8.6 dated 2019-02-22

Title: Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque)
Description: Evaluate arbitrary function calls using workers on HPC schedulers in single line of code. All processing is done on the network without accessing the file system. Remote schedulers are supported via SSH.
Author: Michael Schubert <mschu.dev@gmail.com>
Maintainer: Michael Schubert <mschu.dev@gmail.com>

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New package TSSS with initial version 1.2.3
Package: TSSS
Version: 1.2.3
Title: Time Series Analysis with State Space Model
Author: The Institute of Statistical Mathematics, based on the program by Genshiro Kitagawa
Maintainer: Masami Saga <msaga@mtb.biglobe.ne.jp>
Depends: R (>= 3.4.0), datasets, stats
Suggests: utils
Imports: graphics
Description: Functions for statistical analysis, modeling and simulation of time series with state space model, based on the methodology in Kitagawa (1993, ISBN: 4-00-007703-1 and 2005, ISBN: 4-00-005455-4).
License: GPL (>= 2)
MailingList: Please send bug reports to ismrp@jasp.ism.ac.jp
NeedsCompilation: yes
Packaged: 2019-04-14 23:38:47 UTC; msaga
Repository: CRAN
Date/Publication: 2019-04-15 08:22:42 UTC

More information about TSSS at CRAN
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Package pts2polys updated to version 0.1.1 with previous version 0.1.0 dated 2019-04-14

Title: Construct Polygons Summarising the Location and Variability of Point Sets
Description: Various applications in invasive species biology, conservation biology, epidemiology and elsewhere involve sampling of sets of 2D points from a posterior distribution. The number of such point sets may be large, say 1000 or 10000. This package facilitates visualisation of such output by constructing seven nested polygons representing the location and variability of the point sets. This can be used, for example, to visualise the range boundary of a species, and uncertainty in the location of that boundary.
Author: Jonathan Keith [aut, cre], Ken Clarkson [aut], Eric Hufschmid [ctb], AT&T [cph]
Maintainer: Jonathan Keith <jonathan.keith@monash.edu>

Diff between pts2polys versions 0.1.0 dated 2019-04-14 and 0.1.1 dated 2019-04-15

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New package JamendoR with initial version 0.1.0
Package: JamendoR
Type: Package
Title: Access to 'Jamendo' API
Version: 0.1.0
Authors@R: c(person("Maximilian", "Greil", role = c("aut", "cre"), email = "maximilian_greil@web.de"), person("Benedikt", "Greil", role = "aut", email = "grbene99@web.de"))
Maintainer: Maximilian Greil <maximilian_greil@web.de>
Description: Provides an interface to 'Jamendo' API <https://developer.jamendo.com/v3.0>. Pull audio, features and other information for a given 'Jamendo' user (including yourself!) or enter an artist's -, album's -, or track's name and retrieve the available information in seconds.
Depends: R (>= 3.3.0)
Imports: httr,dplyr,jsonlite,stats
Suggests: knitr
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 6.1.1
URL: http://github.com/MaxGreil/JamendoR
BugReports: http://github.com/MaxGreil/JamendoR/issues
NeedsCompilation: no
Packaged: 2019-04-14 19:40:14 UTC; Maximilian
Author: Maximilian Greil [aut, cre], Benedikt Greil [aut]
Repository: CRAN
Date/Publication: 2019-04-15 08:12:39 UTC

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Permanent link

Package mpath updated to version 0.3-12 with previous version 0.3-7 dated 2019-02-27

Title: Regularized Linear Models
Description: Algorithms for fitting model-based penalized coefficient paths. Currently the models include penalized Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial regression models. The penalties include least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP), and each possibly combining with L_2 penalty. See Wang et al. (2014) <doi:10.1002/sim.6314>, Wang et al. (2015) <doi:10.1002/bimj.201400143>, Wang et al. (2016) <doi:10.1177/0962280214530608>.
Author: Zhu Wang, with contributions from Achim Zeileis, Simon Jackman, Brian Ripley, Trevor Hastie, Rob Tibshirani, Balasubramanian Narasimhan, Gil Chu and Patrick Breheny
Maintainer: Zhu Wang <wangz1@uthscsa.edu>

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Package POD updated to version 1.1.0 with previous version 0.99.0 dated 2019-02-06

Title: Probability of Detection for Qualitative PCR Methods
Description: This tool computes the probability of detection (POD) curve and the limit of detection (LOD), i.e. the number of copies of the target DNA sequence required to ensure a 95 % probability of detection (LOD95). Other quantiles of the LOD can be specified. This is a reimplementation of the mathematical-statistical modelling of the validation of qualitative polymerase chain reaction (PCR) methods within a single laboratory as provided by the commercial tool 'PROLab' <http://quodata.de/>. The modelling itself has been described by Uhlig et al. (2015) <doi:10.1007/s00769-015-1112-9>.
Author: Markus Boenn (State Office for Consumer Protection Saxony-Anhalt, Germany)
Maintainer: Markus Boenn <markus.boenn.sf@gmail.com>

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Package BayesSenMC updated to version 0.1.1 with previous version 0.1.0 dated 2019-04-08

Title: Different Models of Posterior Distributions of Adjusted Odds Ratio
Description: Generates different posterior distributions of adjusted odds ratio under different priors of sensitivity and specificity, and plots the models for comparison. It also provides estimations for the specifications of the models using diagnostics of exposure status with a non-linear mixed effects model. It implements the methods that are first proposed by Chu et al. (2006) <doi:10.1016/j.annepidem.2006.04.001> and Chu et al. (2010) <doi:10.1177/0272989X09353452>.
Author: Jinhui Yang, Haitao Chu, and Lifeng Lin
Maintainer: Jinhui Yang <yangj2@carleton.edu>

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Package AeRobiology updated to version 2.0 with previous version 1.0.3 dated 2019-03-05

Title: A Computational Tool for Aerobiological Data
Description: Different tools for managing databases of airborne particles, elaborating the main calculations and visualization of results. In a first step, data are checked using tools for quality control and all missing gaps are completed. Then, the main parameters of the pollen season are calculated and represented graphically. Multiple graphical tools are available: pollen calendars, phenological plots, time series, tendencies, interactive plots, abundance plots...
Author: Jesus Rojo <Jesus.Rojo@uclm.es>, Antonio Picornell <picornell@uma.es>, Jose Oteros <OterosJose@gmail.com>
Maintainer: "Jose Oteros" <OterosJose@gmail.com>

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Package expss updated to version 0.8.11 with previous version 0.8.10 dated 2018-12-11

Title: Tables, Labels and Some Useful Functions from Spreadsheets and 'SPSS' Statistics
Description: Package computes and displays tables with support for 'SPSS'-style labels, multiple and nested banners, weights, multiple-response variables and significance testing. There are facilities for nice output of tables in 'knitr', 'Shiny', '*.xlsx' files, R and 'Jupyter' notebooks. Methods for labelled variables add value labels support to base R functions and to some functions from other packages. Additionally, the package brings popular data transformation functions from 'SPSS' Statistics and 'Excel': 'RECODE', 'COUNT', 'COMPUTE', 'DO IF', 'COUNTIF', 'VLOOKUP' and etc. These functions are very useful for data processing in marketing research surveys. Package intended to help people to move data processing from 'Excel' and 'SPSS' to R.
Author: Gregory Demin [aut, cre]
Maintainer: Gregory Demin <gdemin@gmail.com>

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 182 files changed, 24705 insertions(+), 20679 deletions(-)

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