Fri, 17 May 2019

Package onewaytests updated to version 2.3 with previous version 2.2 dated 2019-04-26

Title: One-Way Tests in Independent Groups Designs
Description: Performs one-way tests in independent groups designs; one-way analysis of variance (ANOVA), Welch's heteroscedastic F test, Welch's heteroscedastic F test with trimmed means and Winsorized variances, Brown-Forsythe test, Alexander-Govern test, James second order test, Kruskal-Wallis test, Scott-Smith test, Box F test and Johansen F test. The package performs pairwise comparisons and graphical approaches. Also, the package includes Student's t test, Welch's t test and Mann-Whitney U test for two samples. Moreover, it assesses variance homogeneity and normality of data in each group via tests and plots (Dag et al., 2018, <https://journal.r-project.org/archive/2018/RJ-2018-022/RJ-2018-022.pdf>).
Author: Osman Dag [aut, cre], Anil Dolgun [aut], N. Meric Konar [aut]
Maintainer: Osman Dag <osman.dag@outlook.com>

Diff between onewaytests versions 2.2 dated 2019-04-26 and 2.3 dated 2019-05-17

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Package grex updated to version 1.9 with previous version 1.8 dated 2018-04-23

Title: Gene ID Mapping for Genotype-Tissue Expression (GTEx) Data
Description: Convert 'Ensembl' gene identifiers from Genotype-Tissue Expression (GTEx) data to identifiers in other annotation systems, including 'Entrez', 'HGNC', and 'UniProt'.
Author: Nan Xiao [aut, cre] (<https://orcid.org/0000-0002-0250-5673>), Gao Wang [aut], Lei Sun [aut]
Maintainer: Nan Xiao <me@nanx.me>

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Package sparklyr updated to version 1.0.1 with previous version 1.0.0 dated 2019-02-25

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

Diff between sparklyr versions 1.0.0 dated 2019-02-25 and 1.0.1 dated 2019-05-17

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Package DALEX updated to version 0.4 with previous version 0.3.0 dated 2019-03-25

Title: Descriptive mAchine Learning EXplanations
Description: Machine Learning (ML) models are widely used and have various applications in classification or regression. Models created with boosting, bagging, stacking or similar techniques are often used due to their high performance, but such black-box models usually lack of interpretability. DALEX package contains various explainers that help to understand the link between input variables and model output. The single_variable() explainer extracts conditional response of a model as a function of a single selected variable. It is a wrapper over packages 'pdp' (Greenwell 2017) <doi:10.32614/RJ-2017-016>, 'ALEPlot' (Apley 2018) <arXiv:1612.08468> and 'factorMerger' (Sitko and Biecek 2017) <arXiv:1709.04412>. The single_prediction() explainer attributes parts of a model prediction to particular variables used in the model. It is a wrapper over 'breakDown' package (Staniak and Biecek 2018) <doi:10.32614/RJ-2018-072>. The variable_dropout() explainer calculates variable importance scores based on variable shuffling (Fisher at al. 2018) <arXiv:1801.01489>. All these explainers can be plotted with generic plot() function and compared across different models. 'DALEX' is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.
Author: Przemyslaw Biecek [aut, cre] (<https://orcid.org/0000-0001-8423-1823>)
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>

Diff between DALEX versions 0.3.0 dated 2019-03-25 and 0.4 dated 2019-05-17

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More information about DALEX at CRAN
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Package Boom updated to version 0.9 with previous version 0.8 dated 2018-04-29

Title: Bayesian Object Oriented Modeling
Description: A C++ library for Bayesian modeling, with an emphasis on Markov chain Monte Carlo. Although boom contains a few R utilities (mainly plotting functions), its primary purpose is to install the BOOM C++ library on your system so that other packages can link against it.
Author: Steven L. Scott is the sole author and creator of the BOOM project. Some code in the BOOM libraries has been modified from other open source projects. These include Cephes (obtained from Netlib, written by Stephen L. Moshier), NEWUOA (M.J.D Powell, obtained from Powell's web site), and a modified version of the R math libraries (R core development team). Original copyright notices have been maintained in all source files. In these cases, copyright claimed by Steven L. Scott is limited to modifications made to the original code. Google claims copyright for code written while Steven L. Scott was employed at Google from 2008 - 2018, but BOOM is not an officially supported Google project.
Maintainer: Steven L. Scott <steve.the.bayesian@gmail.com>

Diff between Boom versions 0.8 dated 2018-04-29 and 0.9 dated 2019-05-17

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 Boom-0.8/Boom/inst/include/cpputil/str2d.hpp                                                                       |only
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 Boom-0.8/Boom/src/LinAlg/Kronecker.cpp                                                                             |only
 Boom-0.8/Boom/src/LinAlg/LinAlgExceptions.cpp                                                                      |only
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 Boom-0.8/Boom/src/Models/Glm/CumulativeProbitModel.cpp                                                             |only
 Boom-0.8/Boom/src/Models/Glm/MvReg2.cpp                                                                            |only
 Boom-0.8/Boom/src/Models/Glm/MvnGivenXandSigma.cpp                                                                 |only
 Boom-0.8/Boom/src/Models/Glm/PosteriorSamplers/CumulativeLogitSampler.cpp                                          |only
 Boom-0.8/Boom/src/Models/Glm/PosteriorSamplers/CumulativeProbitSampler.cpp                                         |only
 Boom-0.8/Boom/src/Models/Glm/PosteriorSamplers/MvRegSampler.cpp                                                    |only
 Boom-0.8/Boom/src/Models/Hierarchical/PosteriorSamplers/HierarchicalGaussianRegressionAsisSampler.cpp              |only
 Boom-0.8/Boom/src/Models/PointProcess/PosteriorSamplers/HomogeneousPoissonProcessPosteriorSampler.cpp              |only
 Boom-0.8/Boom/src/Models/PointProcess/PosteriorSamplers/MarkovModulatedPoissonProcessPosteriorSampler.cpp          |only
 Boom-0.8/Boom/src/cpputil/cat_string.cpp                                                                           |only
 Boom-0.8/Boom/src/cpputil/str2d.cpp                                                                                |only
 Boom-0.8/Boom/src/create_state_model.cpp                                                                           |only
 Boom-0.9/Boom/DESCRIPTION                                                                                          |   11 
 Boom-0.9/Boom/MD5                                                                                                  | 1265 ++++++----
 Boom-0.9/Boom/NAMESPACE                                                                                            |   80 
 Boom-0.9/Boom/R/boxplot.true.R                                                                                     |   13 
 Boom-0.9/Boom/R/check.data.R                                                                                       |   25 
 Boom-0.9/Boom/R/check.mcmc.matrix.R                                                                                |   43 
 Boom-0.9/Boom/R/circle.R                                                                                           |only
 Boom-0.9/Boom/R/compare.den.R                                                                                      |    2 
 Boom-0.9/Boom/R/compare.many.ts.R                                                                                  |    2 
 Boom-0.9/Boom/R/compare.vector.distribution.R                                                                      |    3 
 Boom-0.9/Boom/R/function.R                                                                                         |only
 Boom-0.9/Boom/R/log.integrated.gaussian.likelihood.R                                                               |only
 Boom-0.9/Boom/R/plot.dynamic.distribution.R                                                                        |    6 
 Boom-0.9/Boom/R/plot.many.ts.R                                                                                     |   11 
 Boom-0.9/Boom/R/prior_specification.R                                                                              |   42 
 Boom-0.9/Boom/R/sufstats.R                                                                                         |   12 
 Boom-0.9/Boom/inst/include/Bmath/Bmath.hpp                                                                         |    9 
 Boom-0.9/Boom/inst/include/Bmath/nmath.hpp                                                                         |   10 
 Boom-0.9/Boom/inst/include/Eigen                                                                                   |only
 Boom-0.9/Boom/inst/include/LinAlg/Array.hpp                                                                        |   71 
 Boom-0.9/Boom/inst/include/LinAlg/Cholesky.hpp                                                                     |   18 
 Boom-0.9/Boom/inst/include/LinAlg/DiagonalMatrix.hpp                                                               |   33 
 Boom-0.9/Boom/inst/include/LinAlg/LU.hpp                                                                           |only
 Boom-0.9/Boom/inst/include/LinAlg/Matrix.hpp                                                                       |  147 -
 Boom-0.9/Boom/inst/include/LinAlg/QR.hpp                                                                           |   21 
 Boom-0.9/Boom/inst/include/LinAlg/SWEEP.hpp                                                                        |    2 
 Boom-0.9/Boom/inst/include/LinAlg/Selector.hpp                                                                     |  267 +-
 Boom-0.9/Boom/inst/include/LinAlg/SpdMatrix.hpp                                                                    |   31 
 Boom-0.9/Boom/inst/include/LinAlg/SubMatrix.hpp                                                                    |   75 
 Boom-0.9/Boom/inst/include/LinAlg/Vector.hpp                                                                       |   70 
 Boom-0.9/Boom/inst/include/LinAlg/VectorView.hpp                                                                   |  118 
 Boom-0.9/Boom/inst/include/Models/Bart/Bart.hpp                                                                    |    8 
 Boom-0.9/Boom/inst/include/Models/BetaModel.hpp                                                                    |    2 
 Boom-0.9/Boom/inst/include/Models/BinomialModel.hpp                                                                |    4 
 Boom-0.9/Boom/inst/include/Models/CategoricalData.hpp                                                              |   16 
 Boom-0.9/Boom/inst/include/Models/CompositeData.hpp                                                                |    2 
 Boom-0.9/Boom/inst/include/Models/DataPair.hpp                                                                     |    2 
 Boom-0.9/Boom/inst/include/Models/DataTypes.hpp                                                                    |   70 
 Boom-0.9/Boom/inst/include/Models/DirichletModel.hpp                                                               |    2 
 Boom-0.9/Boom/inst/include/Models/ExponentialIncrementModel.hpp                                                    |only
 Boom-0.9/Boom/inst/include/Models/ExponentialModel.hpp                                                             |    6 
 Boom-0.9/Boom/inst/include/Models/GammaModel.hpp                                                                   |    4 
 Boom-0.9/Boom/inst/include/Models/GaussianModel.hpp                                                                |    4 
 Boom-0.9/Boom/inst/include/Models/GaussianModelBase.hpp                                                            |   54 
 Boom-0.9/Boom/inst/include/Models/GaussianModelGivenSigma.hpp                                                      |    3 
 Boom-0.9/Boom/inst/include/Models/Glm/AggregatedRegressionModel.hpp                                                |   27 
 Boom-0.9/Boom/inst/include/Models/Glm/BinomialLogitModel.hpp                                                       |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/BinomialProbitModel.hpp                                                      |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/BinomialRegressionData.hpp                                                   |    4 
 Boom-0.9/Boom/inst/include/Models/Glm/ChoiceData.hpp                                                               |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/GammaRegressionModel.hpp                                                     |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/Glm.hpp                                                                      |   20 
 Boom-0.9/Boom/inst/include/Models/Glm/GlmCoefs.hpp                                                                 |   62 
 Boom-0.9/Boom/inst/include/Models/Glm/IndependentRegressionModels.hpp                                              |only
 Boom-0.9/Boom/inst/include/Models/Glm/LogisticRegressionModel.hpp                                                  |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/ModelSelectionConcepts.hpp                                                   |   26 
 Boom-0.9/Boom/inst/include/Models/Glm/MultinomialLogitModel.hpp                                                    |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/MultinomialProbitModel.hpp                                                   |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/MultivariateRegression.hpp                                                   |only
 Boom-0.9/Boom/inst/include/Models/Glm/MvnGivenX.hpp                                                                |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/MvtRegModel.hpp                                                              |   13 
 Boom-0.9/Boom/inst/include/Models/Glm/OrdinalCutpointModel.hpp                                                     |  217 +
 Boom-0.9/Boom/inst/include/Models/Glm/PoissonRegressionData.hpp                                                    |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/AdaptiveSpikeSlabRegressionSampler.hpp                     |only
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/BinomialLogitCompositeSpikeSlabSampler.hpp                 |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/BinomialLogitDataImputer.hpp                               |    4 
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/BinomialLogitSamplerTim.hpp                                |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/BinomialProbitDataImputer.hpp                              |    6 
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/BregVsSampler.hpp                                          |  115 
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/CorrelationMap.hpp                                         |only
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/IndependentRegressionModelsPosteriorSampler.hpp            |only
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/MultivariateRegressionSampler.hpp                          |only
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/MultivariateRegressionSpikeSlabSampler.hpp                 |only
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/MvtRegSampler.hpp                                          |   10 
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/NormalMixtureApproximation.hpp                             |  101 
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/OrdinalLogitImputer.hpp                                    |only
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/OrdinalLogitPosteriorSampler.hpp                           |only
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/RegressionConjSampler.hpp                                  |   22 
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/SpikeSlabSampler.hpp                                       |   18 
 Boom-0.9/Boom/inst/include/Models/Glm/PosteriorSamplers/VsPriorSampler.hpp                                         |   17 
 Boom-0.9/Boom/inst/include/Models/Glm/ProbitRegression.hpp                                                         |    2 
 Boom-0.9/Boom/inst/include/Models/Glm/RegressionModel.hpp                                                          |   73 
 Boom-0.9/Boom/inst/include/Models/Glm/VariableSelectionPrior.hpp                                                   |  181 +
 Boom-0.9/Boom/inst/include/Models/Glm/WeightedRegressionModel.hpp                                                  |    4 
 Boom-0.9/Boom/inst/include/Models/Glm/ZeroInflatedGammaRegression.hpp                                              |    2 
 Boom-0.9/Boom/inst/include/Models/HMM/Clickstream/NestedHmm.hpp                                                    |   12 
 Boom-0.9/Boom/inst/include/Models/HMM/Clickstream/Stream.hpp                                                       |    2 
 Boom-0.9/Boom/inst/include/Models/HMM/HMM2.hpp                                                                     |    2 
 Boom-0.9/Boom/inst/include/Models/HMM/HealthStateModel.hpp                                                         |    8 
 Boom-0.9/Boom/inst/include/Models/HMM/HmmFilter.hpp                                                                |    2 
 Boom-0.9/Boom/inst/include/Models/Hierarchical/HierarchicalDirichletModel.hpp                                      |    2 
 Boom-0.9/Boom/inst/include/Models/Hierarchical/HierarchicalGammaModel.hpp                                          |    2 
 Boom-0.9/Boom/inst/include/Models/Hierarchical/HierarchicalPoissonModel.hpp                                        |    2 
 Boom-0.9/Boom/inst/include/Models/Hierarchical/HierarchicalZeroInflatedGammaModel.hpp                              |    2 
 Boom-0.9/Boom/inst/include/Models/Hierarchical/HierarchicalZeroInflatedPoissonModel.hpp                            |    2 
 Boom-0.9/Boom/inst/include/Models/Hierarchical/PosteriorSamplers/HierGaussianRegressionAsisSampler.hpp             |only
 Boom-0.9/Boom/inst/include/Models/IRT/DafePcrRwm.hpp                                                               |    3 
 Boom-0.9/Boom/inst/include/Models/IRT/IRT.hpp                                                                      |    2 
 Boom-0.9/Boom/inst/include/Models/IRT/IrtModel.hpp                                                                 |   19 
 Boom-0.9/Boom/inst/include/Models/IRT/Item.hpp                                                                     |   32 
 Boom-0.9/Boom/inst/include/Models/IRT/PartialCreditModel.hpp                                                       |   10 
 Boom-0.9/Boom/inst/include/Models/IRT/Subject.hpp                                                                  |   18 
 Boom-0.9/Boom/inst/include/Models/IRT/multisubscale_logit_cutpoint_model.hpp                                       |    2 
 Boom-0.9/Boom/inst/include/Models/IndependentMvnModel.hpp                                                          |   31 
 Boom-0.9/Boom/inst/include/Models/IndependentMvnModelGivenScalarSigma.hpp                                          |    2 
 Boom-0.9/Boom/inst/include/Models/MarkovModel.hpp                                                                  |   24 
 Boom-0.9/Boom/inst/include/Models/MatrixNormalModel.hpp                                                            |only
 Boom-0.9/Boom/inst/include/Models/Mixtures/ConditionalFiniteMixtureModel.hpp                                       |    2 
 Boom-0.9/Boom/inst/include/Models/Mixtures/MvnMetaAnalysisDPMPriorModel.hpp                                        |    2 
 Boom-0.9/Boom/inst/include/Models/ModelTypes.hpp                                                                   |   15 
 Boom-0.9/Boom/inst/include/Models/MultinomialModel.hpp                                                             |    4 
 Boom-0.9/Boom/inst/include/Models/MvnBase.hpp                                                                      |    6 
 Boom-0.9/Boom/inst/include/Models/MvnGivenScalarSigma.hpp                                                          |    3 
 Boom-0.9/Boom/inst/include/Models/Nnet                                                                             |only
 Boom-0.9/Boom/inst/include/Models/ParamTypes.hpp                                                                   |   43 
 Boom-0.9/Boom/inst/include/Models/PointProcess/HomogeneousPoissonProcess.hpp                                       |    2 
 Boom-0.9/Boom/inst/include/Models/PointProcess/MarkovModulatedPoissonProcess.hpp                                   |    8 
 Boom-0.9/Boom/inst/include/Models/PointProcess/PointProcess.hpp                                                    |   21 
 Boom-0.9/Boom/inst/include/Models/PointProcess/PoissonClusterProcess.hpp                                           |   10 
 Boom-0.9/Boom/inst/include/Models/PointProcess/PosteriorSamplers/HomogPoissonProcessPosteriorSampler.hpp           |only
 Boom-0.9/Boom/inst/include/Models/PointProcess/PosteriorSamplers/MmppPosteriorSampler.hpp                          |only
 Boom-0.9/Boom/inst/include/Models/PointProcess/WeeklyCyclePoissonProcess.hpp                                       |    2 
 Boom-0.9/Boom/inst/include/Models/PoissonGammaModel.hpp                                                            |    2 
 Boom-0.9/Boom/inst/include/Models/PoissonModel.hpp                                                                 |    2 
 Boom-0.9/Boom/inst/include/Models/Policies/CompositeParamPolicy.hpp                                                |    3 
 Boom-0.9/Boom/inst/include/Models/Policies/IID_DataPolicy.hpp                                                      |    3 
 Boom-0.9/Boom/inst/include/Models/Policies/ParamPolicy_2.hpp                                                       |   69 
 Boom-0.9/Boom/inst/include/Models/Policies/PriorPolicy.hpp                                                         |    1 
 Boom-0.9/Boom/inst/include/Models/Policies/SufstatDataPolicy.hpp                                                   |    1 
 Boom-0.9/Boom/inst/include/Models/PosteriorSamplers/GenericGaussianVarianceSampler.hpp                             |    2 
 Boom-0.9/Boom/inst/include/Models/PosteriorSamplers/IndependentMvnVarSampler.hpp                                   |    3 
 Boom-0.9/Boom/inst/include/Models/PosteriorSamplers/MvnConjSampler.hpp                                             |   51 
 Boom-0.9/Boom/inst/include/Models/PosteriorSamplers/MvnVarSampler.hpp                                              |   57 
 Boom-0.9/Boom/inst/include/Models/PosteriorSamplers/PosteriorSampler.hpp                                           |    3 
 Boom-0.9/Boom/inst/include/Models/ProductDirichletModel.hpp                                                        |    2 
 Boom-0.9/Boom/inst/include/Models/ScaledChisqModel.hpp                                                             |    2 
 Boom-0.9/Boom/inst/include/Models/SpdData.hpp                                                                      |   49 
 Boom-0.9/Boom/inst/include/Models/StateSpace/AggregatedStateSpaceRegression.hpp                                    |   45 
 Boom-0.9/Boom/inst/include/Models/StateSpace/DynamicInterceptRegression.hpp                                        |  213 +
 Boom-0.9/Boom/inst/include/Models/StateSpace/Filters/ConditionalIidKalmanFilter.hpp                                |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/Filters/ConditionallyIndependentKalmanFilter.hpp                      |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/Filters/KalmanFilterBase.hpp                                          |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/Filters/MultivariateKalmanFilterBase.hpp                              |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/Filters/ScalarKalmanFilter.hpp                                        |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/Filters/SparseKalmanTools.hpp                                         |   56 
 Boom-0.9/Boom/inst/include/Models/StateSpace/Filters/SparseMatrix.hpp                                              |  592 +++-
 Boom-0.9/Boom/inst/include/Models/StateSpace/Filters/SparseVector.hpp                                              |    3 
 Boom-0.9/Boom/inst/include/Models/StateSpace/MultivariateStateSpaceModel.hpp                                       |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/MultivariateStateSpaceModelBase.hpp                                   |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/MultivariateStateSpaceRegressionModel.hpp                             |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/PosteriorSamplers/DynamicInterceptRegressionPosteriorSampler.hpp      |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/PosteriorSamplers/MultivariateStateSpaceModelSampler.hpp              |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/PosteriorSamplers/MvStateSpaceRegressionPosteriorSampler.hpp          |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/PosteriorSamplers/SharedLocalLevelPosteriorSampler.hpp                |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/PosteriorSamplers/StateSpacePosteriorSampler.hpp                      |    4 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModelVector.hpp                                                  |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/ArStateModel.hpp                                          |   17 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/DynamicRegressionArStateModel.hpp                         |   37 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/DynamicRegressionStateModel.hpp                           |   31 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/GeneralSeasonalStateModel.hpp                             |   15 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/HierarchicalRegressionHolidayStateModel.hpp               |   79 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/Holiday.hpp                                               |    4 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/LocalLevelStateModel.hpp                                  |  213 +
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/LocalLinearTrend.hpp                                      |   29 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/RandomWalkHolidayStateModel.hpp                           |   63 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/RegressionHolidayStateModel.hpp                           |   90 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/RegressionStateModel.hpp                                  |   37 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/SeasonalStateModel.hpp                                    |   20 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/SemilocalLinearTrend.hpp                                  |   25 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/StateModel.hpp                                            |  118 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/StaticInterceptStateModel.hpp                             |   16 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/StudentLocalLinearTrend.hpp                               |   23 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/TrigStateModel.hpp                                        |  200 -
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateModels/test_utils                                                |only
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateSpaceLogitModel.hpp                                              |    5 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateSpaceModel.hpp                                                   |   34 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateSpaceModelBase.hpp                                               |  939 ++-----
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateSpaceRegressionModel.hpp                                         |    4 
 Boom-0.9/Boom/inst/include/Models/StateSpace/StateSpaceStudentRegressionModel.hpp                                  |    3 
 Boom-0.9/Boom/inst/include/Models/StateSpace/tests                                                                 |only
 Boom-0.9/Boom/inst/include/Models/TimeSeries/ArModel.hpp                                                           |    2 
 Boom-0.9/Boom/inst/include/Models/TimeSeries/ArmaModel.hpp                                                         |   18 
 Boom-0.9/Boom/inst/include/Models/TimeSeries/AugmentedTimeSeries.hpp                                               |    4 
 Boom-0.9/Boom/inst/include/Models/TimeSeries/NonzeroMeanAr1Model.hpp                                               |    4 
 Boom-0.9/Boom/inst/include/Models/TimeSeries/TimeSeries.hpp                                                        |   18 
 Boom-0.9/Boom/inst/include/Models/UniformModel.hpp                                                                 |    2 
 Boom-0.9/Boom/inst/include/Models/WeightedData.hpp                                                                 |    4 
 Boom-0.9/Boom/inst/include/Models/WeightedGaussianSuf.hpp                                                          |    2 
 Boom-0.9/Boom/inst/include/Models/WeightedMvnModel.hpp                                                             |    2 
 Boom-0.9/Boom/inst/include/Models/WishartModel.hpp                                                                 |    2 
 Boom-0.9/Boom/inst/include/Models/ZeroInflatedPoissonModel.hpp                                                     |    2 
 Boom-0.9/Boom/inst/include/Samplers/UnivariateSliceSampler.hpp                                                     |    6 
 Boom-0.9/Boom/inst/include/TargetFun/LogPost.hpp                                                                   |    2 
 Boom-0.9/Boom/inst/include/cpputil/Constants.hpp                                                                   |    1 
 Boom-0.9/Boom/inst/include/cpputil/Date.hpp                                                                        |   16 
 Boom-0.9/Boom/inst/include/cpputil/DateTime.hpp                                                                    |   27 
 Boom-0.9/Boom/inst/include/cpputil/DefaultVnames.hpp                                                               |    4 
 Boom-0.9/Boom/inst/include/cpputil/OutputTable.hpp                                                                 |    4 
 Boom-0.9/Boom/inst/include/cpputil/ParamHolder.hpp                                                                 |   35 
 Boom-0.9/Boom/inst/include/cpputil/ProgressTracker.hpp                                                             |    2 
 Boom-0.9/Boom/inst/include/cpputil/Redirector.hpp                                                                  |   11 
 Boom-0.9/Boom/inst/include/cpputil/Split.hpp                                                                       |   12 
 Boom-0.9/Boom/inst/include/cpputil/ThreadTools.hpp                                                                 |    6 
 Boom-0.9/Boom/inst/include/cpputil/file_utils.hpp                                                                  |    2 
 Boom-0.9/Boom/inst/include/cpputil/portable_math.hpp                                                               |    6 
 Boom-0.9/Boom/inst/include/cpputil/string_utils.hpp                                                                |   83 
 Boom-0.9/Boom/inst/include/cpputil/timer.hpp                                                                       |only
 Boom-0.9/Boom/inst/include/distributions.hpp                                                                       |  158 +
 Boom-0.9/Boom/inst/include/distributions/rng.hpp                                                                   |   31 
 Boom-0.9/Boom/inst/include/numopt.hpp                                                                              |    6 
 Boom-0.9/Boom/inst/include/r_interface/boom_r_tools.hpp                                                            |   73 
 Boom-0.9/Boom/inst/include/r_interface/create_mixture_component.hpp                                                |    4 
 Boom-0.9/Boom/inst/include/r_interface/create_point_process.hpp                                                    |    2 
 Boom-0.9/Boom/inst/include/r_interface/create_poisson_cluster_components.hpp                                       |    2 
 Boom-0.9/Boom/inst/include/r_interface/create_poisson_process.hpp                                                  |    2 
 Boom-0.9/Boom/inst/include/r_interface/determine_nthreads.hpp                                                      |    2 
 Boom-0.9/Boom/inst/include/r_interface/list_io.hpp                                                                 |  944 ++++---
 Boom-0.9/Boom/inst/include/r_interface/parse_model_formula.hpp                                                     |    2 
 Boom-0.9/Boom/inst/include/r_interface/prior_specification.hpp                                                     |   30 
 Boom-0.9/Boom/inst/include/r_interface/seed_rng_from_R.hpp                                                         |   12 
 Boom-0.9/Boom/inst/include/r_interface/sufstats.hpp                                                                |    4 
 Boom-0.9/Boom/inst/include/stats/AsciiDistributionCompare.hpp                                                      |   18 
 Boom-0.9/Boom/inst/include/stats/DataTable.hpp                                                                     |   25 
 Boom-0.9/Boom/inst/include/stats/Design.hpp                                                                        |    2 
 Boom-0.9/Boom/inst/include/stats/FreqDist.hpp                                                                      |    8 
 Boom-0.9/Boom/inst/include/stats/NaturalSpline.hpp                                                                 |    1 
 Boom-0.9/Boom/inst/include/stats/Resampler.hpp                                                                     |    2 
 Boom-0.9/Boom/inst/include/stats/simple_random_sample.hpp                                                          |    2 
 Boom-0.9/Boom/inst/include/stats/summary.hpp                                                                       |only
 Boom-0.9/Boom/inst/include/uint.hpp                                                                                |    6 
 Boom-0.9/Boom/man/ToString.Rd                                                                                      |    2 
 Boom-0.9/Boom/man/ar1.coefficient.prior.Rd                                                                         |    4 
 Boom-0.9/Boom/man/beta.prior.Rd                                                                                    |    4 
 Boom-0.9/Boom/man/boxplot.true.Rd                                                                                  |   30 
 Boom-0.9/Boom/man/check.Rd                                                                                         |   25 
 Boom-0.9/Boom/man/check.data.Rd                                                                                    |    4 
 Boom-0.9/Boom/man/circles.Rd                                                                                       |only
 Boom-0.9/Boom/man/compare.vector.distributions.Rd                                                                  |    2 
 Boom-0.9/Boom/man/dirichlet-distribution.Rd                                                                        |    2 
 Boom-0.9/Boom/man/dirichlet.prior.Rd                                                                               |    4 
 Boom-0.9/Boom/man/discrete-uniform-prior.Rd                                                                        |    2 
 Boom-0.9/Boom/man/dmvn.Rd                                                                                          |    4 
 Boom-0.9/Boom/man/double.model.Rd                                                                                  |    4 
 Boom-0.9/Boom/man/gamma.prior.Rd                                                                                   |    4 
 Boom-0.9/Boom/man/generate_factor_data.Rd                                                                          |    2 
 Boom-0.9/Boom/man/inverse-wishart.Rd                                                                               |    2 
 Boom-0.9/Boom/man/invgamma.Rd                                                                                      |    2 
 Boom-0.9/Boom/man/lmgamma.Rd                                                                                       |    2 
 Boom-0.9/Boom/man/log.integrated.gaussian.likelihood.Rd                                                            |only
 Boom-0.9/Boom/man/lognormal.prior.Rd                                                                               |    4 
 Boom-0.9/Boom/man/markov.prior.Rd                                                                                  |    4 
 Boom-0.9/Boom/man/match_data_frame.Rd                                                                              |    2 
 Boom-0.9/Boom/man/mscan.Rd                                                                                         |    2 
 Boom-0.9/Boom/man/mvn.diagonal.prior.Rd                                                                            |    4 
 Boom-0.9/Boom/man/mvn.independent.sigma.prior.Rd                                                                   |    2 
 Boom-0.9/Boom/man/mvn.prior.Rd                                                                                     |    4 
 Boom-0.9/Boom/man/normal.inverse.gamma.prior.Rd                                                                    |    4 
 Boom-0.9/Boom/man/normal.inverse.wishart.prior.Rd                                                                  |    4 
 Boom-0.9/Boom/man/normal.prior.Rd                                                                                  |    2 
 Boom-0.9/Boom/man/plot.dynamic.distribution.Rd                                                                     |    2 
 Boom-0.9/Boom/man/regression.coefficient.conjugate.prior.Rd                                                        |    2 
 Boom-0.9/Boom/man/rmvn.Rd                                                                                          |    4 
 Boom-0.9/Boom/man/rvectorfunction.Rd                                                                               |only
 Boom-0.9/Boom/man/scaled.matrix.normal.prior.Rd                                                                    |only
 Boom-0.9/Boom/man/sd.prior.Rd                                                                                      |    4 
 Boom-0.9/Boom/man/sufstat.Rd                                                                                       |    9 
 Boom-0.9/Boom/man/suggest.burn.log.likelihood.Rd                                                                   |    2 
 Boom-0.9/Boom/man/thin.matrix.Rd                                                                                   |    2 
 Boom-0.9/Boom/man/timeseries.boxplot.Rd                                                                            |    2 
 Boom-0.9/Boom/man/traceproduct.Rd                                                                                  |    2 
 Boom-0.9/Boom/man/uniform.prior.Rd                                                                                 |    2 
 Boom-0.9/Boom/man/wishart.Rd                                                                                       |    2 
 Boom-0.9/Boom/src/Bmath/Bmath.hpp                                                                                  |    9 
 Boom-0.9/Boom/src/Bmath/dlogis.cpp                                                                                 |   16 
 Boom-0.9/Boom/src/Bmath/gammalims.cpp                                                                              |   55 
 Boom-0.9/Boom/src/Bmath/mathlib_error.cpp                                                                          |   12 
 Boom-0.9/Boom/src/Bmath/mlutils.cpp                                                                                |    9 
 Boom-0.9/Boom/src/Bmath/nmath.hpp                                                                                  |   10 
 Boom-0.9/Boom/src/Bmath/pbeta.cpp                                                                                  |    2 
 Boom-0.9/Boom/src/Bmath/pgamma.cpp                                                                                 |    2 
 Boom-0.9/Boom/src/Bmath/plogis.cpp                                                                                 |   19 
 Boom-0.9/Boom/src/Bmath/pnchisq.cpp                                                                                |   13 
 Boom-0.9/Boom/src/Bmath/qchisq.cpp                                                                                 |    8 
 Boom-0.9/Boom/src/Bmath/qgamma.cpp                                                                                 |   28 
 Boom-0.9/Boom/src/Bmath/rbinom.cpp                                                                                 |    2 
 Boom-0.9/Boom/src/Bmath/rpois.cpp                                                                                  |    6 
 Boom-0.9/Boom/src/LinAlg/Array.cpp                                                                                 |   72 
 Boom-0.9/Boom/src/LinAlg/Cholesky.cpp                                                                              |   55 
 Boom-0.9/Boom/src/LinAlg/CorrelationMatrix.cpp                                                                     |    1 
 Boom-0.9/Boom/src/LinAlg/DiagonalMatrix.cpp                                                                        |   61 
 Boom-0.9/Boom/src/LinAlg/Eigen.cpp                                                                                 |    2 
 Boom-0.9/Boom/src/LinAlg/LU.cpp                                                                                    |only
 Boom-0.9/Boom/src/LinAlg/Matrix.cpp                                                                                |  166 -
 Boom-0.9/Boom/src/LinAlg/QR.cpp                                                                                    |   79 
 Boom-0.9/Boom/src/LinAlg/SVD.cpp                                                                                   |    2 
 Boom-0.9/Boom/src/LinAlg/Selector.cpp                                                                              |  704 +++--
 Boom-0.9/Boom/src/LinAlg/SpdMatrix.cpp                                                                             |   72 
 Boom-0.9/Boom/src/LinAlg/SubMatrix.cpp                                                                             |  217 +
 Boom-0.9/Boom/src/LinAlg/Vector.cpp                                                                                |  230 +
 Boom-0.9/Boom/src/LinAlg/VectorView.cpp                                                                            |   14 
 Boom-0.9/Boom/src/Makevars                                                                                         |   17 
 Boom-0.9/Boom/src/Models/Bart/Bart.cpp                                                                             |    4 
 Boom-0.9/Boom/src/Models/BetaModel.cpp                                                                             |    2 
 Boom-0.9/Boom/src/Models/BinomialModel.cpp                                                                         |    6 
 Boom-0.9/Boom/src/Models/CategoricalData.cpp                                                                       |   16 
 Boom-0.9/Boom/src/Models/CompositeData.cpp                                                                         |    2 
 Boom-0.9/Boom/src/Models/DataTypes.cpp                                                                             |   43 
 Boom-0.9/Boom/src/Models/DirichletModel.cpp                                                                        |    2 
 Boom-0.9/Boom/src/Models/ExponentialIncrementModel.cpp                                                             |only
 Boom-0.9/Boom/src/Models/ExponentialModel.cpp                                                                      |   16 
 Boom-0.9/Boom/src/Models/GammaModel.cpp                                                                            |    4 
 Boom-0.9/Boom/src/Models/GaussianModel.cpp                                                                         |   21 
 Boom-0.9/Boom/src/Models/GaussianModelBase.cpp                                                                     |   53 
 Boom-0.9/Boom/src/Models/Glm/AggregatedRegressionModel.cpp                                                         |   18 
 Boom-0.9/Boom/src/Models/Glm/BinomialRegressionData.cpp                                                            |   14 
 Boom-0.9/Boom/src/Models/Glm/ChoiceData.cpp                                                                        |    2 
 Boom-0.9/Boom/src/Models/Glm/GlmCoefs.cpp                                                                          |   53 
 Boom-0.9/Boom/src/Models/Glm/IndependentRegressionModels.cpp                                                       |only
 Boom-0.9/Boom/src/Models/Glm/MultinomialLogitModel.cpp                                                             |    2 
 Boom-0.9/Boom/src/Models/Glm/MultinomialProbitModel.cpp                                                            |    4 
 Boom-0.9/Boom/src/Models/Glm/MultivariateRegression.cpp                                                            |only
 Boom-0.9/Boom/src/Models/Glm/MvnGivenX.cpp                                                                         |    3 
 Boom-0.9/Boom/src/Models/Glm/MvtRegModel.cpp                                                                       |   16 
 Boom-0.9/Boom/src/Models/Glm/OrdinalCutpointModel.cpp                                                              |  494 ++-
 Boom-0.9/Boom/src/Models/Glm/PoissonRegressionData.cpp                                                             |    2 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/AdaptiveSpikeSlabRegressionSampler.cpp                              |only
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/BinomialLogitCompositeSpikeSlabSampler.cpp                          |    4 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/BinomialLogitDataImputer.cpp                                        |   19 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/BinomialLogitSpikeSlabSampler.cpp                                   |    2 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/BinomialProbitTimSampler.cpp                                        |    3 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/BregVsSampler.cpp                                                   |   99 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/CorrelationMap.cpp                                                  |only
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/MLVS_data_imputer.cpp                                               |    9 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/MultivariateRegressionSampler.cpp                                   |only
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/MultivariateRegressionSpikeSlabSampler.cpp                          |only
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/MvtRegSampler.cpp                                                   |    8 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/NormalMixtureApproximation.cpp                                      |   13 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/OrdinalLogitImputer.cpp                                             |only
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/OrdinalLogitPosteriorSampler.cpp                                    |only
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/RegressionCoefficientSampler.cpp                                    |    4 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/RegressionConjSampler.cpp                                           |   58 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/RegressionShrinkageSampler.cpp                                      |    2 
 Boom-0.9/Boom/src/Models/Glm/PosteriorSamplers/VsPriorSampler.cpp                                                  |   18 
 Boom-0.9/Boom/src/Models/Glm/RegressionModel.cpp                                                                   |  109 
 Boom-0.9/Boom/src/Models/Glm/VariableSelectionPrior.cpp                                                            |  253 +-
 Boom-0.9/Boom/src/Models/Glm/WeightedRegressionModel.cpp                                                           |    2 
 Boom-0.9/Boom/src/Models/HMM/Clickstream/NestedHmm.cpp                                                             |   10 
 Boom-0.9/Boom/src/Models/HMM/GeneralHmmStateSpaceWrapper.cpp                                                       |    2 
 Boom-0.9/Boom/src/Models/HMM/HealthStateModel.cpp                                                                  |    2 
 Boom-0.9/Boom/src/Models/HMM/HmmFilter.cpp                                                                         |    4 
 Boom-0.9/Boom/src/Models/HMM/PosteriorSamplers/LiuWestParticleFilter.cpp                                           |    2 
 Boom-0.9/Boom/src/Models/Hierarchical/HierarchicalDirichletModel.cpp                                               |    2 
 Boom-0.9/Boom/src/Models/Hierarchical/HierarchicalPoissonModel.cpp                                                 |    2 
 Boom-0.9/Boom/src/Models/Hierarchical/HierarchicalZeroInflatedGammaModel.cpp                                       |    2 
 Boom-0.9/Boom/src/Models/Hierarchical/HierarchicalZeroInflatedPoissonModel.cpp                                     |    2 
 Boom-0.9/Boom/src/Models/Hierarchical/PosteriorSamplers/HierGaussianRegressionAsisSampler.cpp                      |only
 Boom-0.9/Boom/src/Models/IRT/IrtModel.cpp                                                                          |   57 
 Boom-0.9/Boom/src/Models/IRT/Item.cpp                                                                              |   34 
 Boom-0.9/Boom/src/Models/IRT/PartialCreditModel.cpp                                                                |   10 
 Boom-0.9/Boom/src/Models/IRT/Subject.cpp                                                                           |   16 
 Boom-0.9/Boom/src/Models/IndependentMvnModel.cpp                                                                   |  106 
 Boom-0.9/Boom/src/Models/IndependentMvnModelGivenScalarSigma.cpp                                                   |    6 
 Boom-0.9/Boom/src/Models/MarkovModel.cpp                                                                           |   22 
 Boom-0.9/Boom/src/Models/MatrixNormalModel.cpp                                                                     |only
 Boom-0.9/Boom/src/Models/Mixtures/ConditionalFiniteMixtureModel.cpp                                                |    2 
 Boom-0.9/Boom/src/Models/Mixtures/MvnMetaAnalysisDPMPriorModel.cpp                                                 |    2 
 Boom-0.9/Boom/src/Models/ModelTypes.cpp                                                                            |   22 
 Boom-0.9/Boom/src/Models/MultinomialModel.cpp                                                                      |   10 
 Boom-0.9/Boom/src/Models/MvnBase.cpp                                                                               |    5 
 Boom-0.9/Boom/src/Models/Nnet                                                                                      |only
 Boom-0.9/Boom/src/Models/ParamTypes.cpp                                                                            |    6 
 Boom-0.9/Boom/src/Models/PointProcess/HomogeneousPoissonProcess.cpp                                                |    2 
 Boom-0.9/Boom/src/Models/PointProcess/MarkovModulatedPoissonProcess.cpp                                            |    4 
 Boom-0.9/Boom/src/Models/PointProcess/PointProcess.cpp                                                             |    4 
 Boom-0.9/Boom/src/Models/PointProcess/PoissonClusterProcess.cpp                                                    |  175 -
 Boom-0.9/Boom/src/Models/PointProcess/PosteriorSamplers/HomogPoissonProcessPosteriorSampler.cpp                    |only
 Boom-0.9/Boom/src/Models/PointProcess/PosteriorSamplers/MmppPosteriorSampler.cpp                                   |only
 Boom-0.9/Boom/src/Models/PointProcess/WeeklyCyclePoissonProcess.cpp                                                |    2 
 Boom-0.9/Boom/src/Models/PoissonGammaModel.cpp                                                                     |    2 
 Boom-0.9/Boom/src/Models/PoissonModel.cpp                                                                          |    2 
 Boom-0.9/Boom/src/Models/PosteriorSamplers/BetaPosteriorSampler.cpp                                                |    7 
 Boom-0.9/Boom/src/Models/PosteriorSamplers/CorrelationSampler.cpp                                                  |    2 
 Boom-0.9/Boom/src/Models/PosteriorSamplers/DirichletPosteriorSampler.cpp                                           |    2 
 Boom-0.9/Boom/src/Models/PosteriorSamplers/IndependentMvnVarSampler.cpp                                            |   15 
 Boom-0.9/Boom/src/Models/PosteriorSamplers/MvnConjSampler.cpp                                                      |   39 
 Boom-0.9/Boom/src/Models/PosteriorSamplers/SepStratSampler.cpp                                                     |    4 
 Boom-0.9/Boom/src/Models/ProductDirichletModel.cpp                                                                 |    4 
 Boom-0.9/Boom/src/Models/SpdData.cpp                                                                               |   68 
 Boom-0.9/Boom/src/Models/StateSpace/AggregatedStateSpaceRegression.cpp                                             |   25 
 Boom-0.9/Boom/src/Models/StateSpace/DynamicInterceptRegression.cpp                                                 |  258 +-
 Boom-0.9/Boom/src/Models/StateSpace/Filters/ConditionalIidKalmanFilter.cpp                                         |only
 Boom-0.9/Boom/src/Models/StateSpace/Filters/ConditionallyIndependentKalmanFilter.cpp                               |only
 Boom-0.9/Boom/src/Models/StateSpace/Filters/KalmanFilterBase.cpp                                                   |only
 Boom-0.9/Boom/src/Models/StateSpace/Filters/KalmanTools.cpp                                                        |    4 
 Boom-0.9/Boom/src/Models/StateSpace/Filters/MultivariateKalmanFilterBase.cpp                                       |only
 Boom-0.9/Boom/src/Models/StateSpace/Filters/ScalarKalmanFilter.cpp                                                 |only
 Boom-0.9/Boom/src/Models/StateSpace/Filters/SparseKalmanTools.cpp                                                  |  136 +
 Boom-0.9/Boom/src/Models/StateSpace/Filters/SparseMatrix.cpp                                                       |  502 +++
 Boom-0.9/Boom/src/Models/StateSpace/Filters/SparseVector.cpp                                                       |    2 
 Boom-0.9/Boom/src/Models/StateSpace/MultivariateStateSpaceModel.cpp                                                |only
 Boom-0.9/Boom/src/Models/StateSpace/MultivariateStateSpaceModelBase.cpp                                            |only
 Boom-0.9/Boom/src/Models/StateSpace/MultivariateStateSpaceRegressionModel.cpp                                      |only
 Boom-0.9/Boom/src/Models/StateSpace/PosteriorSamplers/AggregatedStateSpacePosteriorSampler.cpp                     |    4 
 Boom-0.9/Boom/src/Models/StateSpace/PosteriorSamplers/MultivariateStateSpaceModelSampler.cpp                       |only
 Boom-0.9/Boom/src/Models/StateSpace/PosteriorSamplers/MvStateSpaceRegressionPosteriorSampler.cpp                   |only
 Boom-0.9/Boom/src/Models/StateSpace/PosteriorSamplers/SharedLocalLevelPosteriorSampler.cpp                         |only
 Boom-0.9/Boom/src/Models/StateSpace/PosteriorSamplers/StateSpacePosteriorSampler.cpp                               |   23 
 Boom-0.9/Boom/src/Models/StateSpace/PosteriorSamplers/StudentLocalLinearTrendPosteriorSampler.cpp                  |   55 
 Boom-0.9/Boom/src/Models/StateSpace/StateModelVector.cpp                                                           |only
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/ArStateModel.cpp                                                   |   12 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/DynamicRegressionArStateModel.cpp                                  |   10 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/DynamicRegressionStateModel.cpp                                    |   42 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/HierarchicalRegressionHolidayStateModel.cpp                        |   78 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/Holiday.cpp                                                        |    3 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/LocalLevelStateModel.cpp                                           |  272 ++
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/LocalLinearTrend.cpp                                               |   21 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/RandomWalkHolidayStateModel.cpp                                    |   17 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/RegressionHolidayStateModel.cpp                                    |  141 -
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/RegressionStateModel.cpp                                           |   29 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/SeasonalStateModel.cpp                                             |    3 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/SemilocalLinearTrend.cpp                                           |   28 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/StateModel.cpp                                                     |   15 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/StaticInterceptStateModel.cpp                                      |    6 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/StudentLocalLinearTrend.cpp                                        |    9 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/TrigStateModel.cpp                                                 |   66 
 Boom-0.9/Boom/src/Models/StateSpace/StateModels/test_utils                                                         |only
 Boom-0.9/Boom/src/Models/StateSpace/StateSpaceLogitModel.cpp                                                       |   59 
 Boom-0.9/Boom/src/Models/StateSpace/StateSpaceModel.cpp                                                            |   76 
 Boom-0.9/Boom/src/Models/StateSpace/StateSpaceModelBase.cpp                                                        |  827 +-----
 Boom-0.9/Boom/src/Models/StateSpace/StateSpacePoissonModel.cpp                                                     |   16 
 Boom-0.9/Boom/src/Models/StateSpace/StateSpaceRegressionModel.cpp                                                  |   52 
 Boom-0.9/Boom/src/Models/StateSpace/StateSpaceStudentRegressionModel.cpp                                           |   47 
 Boom-0.9/Boom/src/Models/StateSpace/tests                                                                          |only
 Boom-0.9/Boom/src/Models/TimeSeries/ArModel.cpp                                                                    |    2 
 Boom-0.9/Boom/src/Models/TimeSeries/ArmaModel.cpp                                                                  |   58 
 Boom-0.9/Boom/src/Models/TimeSeries/NonzeroMeanAr1Model.cpp                                                        |    2 
 Boom-0.9/Boom/src/Models/UniformModel.cpp                                                                          |    4 
 Boom-0.9/Boom/src/Models/WeightedGaussianSuf.cpp                                                                   |    2 
 Boom-0.9/Boom/src/Models/WeightedMvnModel.cpp                                                                      |    2 
 Boom-0.9/Boom/src/Models/WishartModel.cpp                                                                          |    4 
 Boom-0.9/Boom/src/Models/ZeroInflatedPoissonModel.cpp                                                              |    2 
 Boom-0.9/Boom/src/Samplers/MH_Proposals.cpp                                                                        |    6 
 Boom-0.9/Boom/src/Samplers/ScalarSliceSampler.cpp                                                                  |   26 
 Boom-0.9/Boom/src/Samplers/TIM.cpp                                                                                 |    2 
 Boom-0.9/Boom/src/TargetFun/Transformation.cpp                                                                     |    2 
 Boom-0.9/Boom/src/boom_r_tools.cpp                                                                                 |  137 -
 Boom-0.9/Boom/src/cpputil/Date.cpp                                                                                 |   54 
 Boom-0.9/Boom/src/cpputil/DateTime.cpp                                                                             |    8 
 Boom-0.9/Boom/src/cpputil/DefaultVnames.cpp                                                                        |    6 
 Boom-0.9/Boom/src/cpputil/OutputTable.cpp                                                                          |    4 
 Boom-0.9/Boom/src/cpputil/ParamHolder.cpp                                                                          |   13 
 Boom-0.9/Boom/src/cpputil/gll.cpp                                                                                  |   11 
 Boom-0.9/Boom/src/cpputil/is_all_white.cpp                                                                         |    7 
 Boom-0.9/Boom/src/cpputil/is_numeric.cpp                                                                           |    4 
 Boom-0.9/Boom/src/cpputil/parse_range.cpp                                                                          |   31 
 Boom-0.9/Boom/src/cpputil/print_columns.cpp                                                                        |   11 
 Boom-0.9/Boom/src/cpputil/read_file.cpp                                                                            |   13 
 Boom-0.9/Boom/src/cpputil/split.cpp                                                                                |   33 
 Boom-0.9/Boom/src/cpputil/split_delimited.cpp                                                                      |    9 
 Boom-0.9/Boom/src/cpputil/split_string.cpp                                                                         |   20 
 Boom-0.9/Boom/src/create_mixture_component.cpp                                                                     |    6 
 Boom-0.9/Boom/src/create_point_process.cpp                                                                         |    2 
 Boom-0.9/Boom/src/create_poisson_cluster_components.cpp                                                            |    4 
 Boom-0.9/Boom/src/create_poisson_process.cpp                                                                       |   10 
 Boom-0.9/Boom/src/determine_nthreads.cpp                                                                           |    2 
 Boom-0.9/Boom/src/distributions/Markov.cpp                                                                         |    2 
 Boom-0.9/Boom/src/distributions/matrix_normal.cpp                                                                  |   38 
 Boom-0.9/Boom/src/distributions/mvn.cpp                                                                            |   54 
 Boom-0.9/Boom/src/distributions/rmulti.cpp                                                                         |    1 
 Boom-0.9/Boom/src/distributions/rng.cpp                                                                            |   17 
 Boom-0.9/Boom/src/distributions/trun_norm.cpp                                                                      |    3 
 Boom-0.9/Boom/src/distributions/usp.cpp                                                                            |    2 
 Boom-0.9/Boom/src/extract_mixture_data.cpp                                                                         |    4 
 Boom-0.9/Boom/src/list_io.cpp                                                                                      |  916 +++----
 Boom-0.9/Boom/src/numopt/NelderMead.cpp                                                                            |    1 
 Boom-0.9/Boom/src/numopt/NumericalDerivatives.cpp                                                                  |    4 
 Boom-0.9/Boom/src/numopt/bfgs.cpp                                                                                  |    5 
 Boom-0.9/Boom/src/numopt/max_nd.cpp                                                                                |    6 
 Boom-0.9/Boom/src/numopt/newton.cpp                                                                                |    5 
 Boom-0.9/Boom/src/parse_model_formula.cpp                                                                          |    4 
 Boom-0.9/Boom/src/prior_specification.cpp                                                                          |  103 
 Boom-0.9/Boom/src/seed_rng_from_R.cpp                                                                              |   10 
 Boom-0.9/Boom/src/spike_slab_prior.cpp                                                                             |    8 
 Boom-0.9/Boom/src/stats/AsciiDistributionCompare.cpp                                                               |   36 
 Boom-0.9/Boom/src/stats/DataTable.cpp                                                                              |   65 
 Boom-0.9/Boom/src/stats/Design.cpp                                                                                 |    2 
 Boom-0.9/Boom/src/stats/FreqDist.cpp                                                                               |    2 
 Boom-0.9/Boom/src/stats/NaturalSpline.cpp                                                                          |    6 
 Boom-0.9/Boom/src/stats/Spline.cpp                                                                                 |    2 
 Boom-0.9/Boom/src/stats/summary.cpp                                                                                |only
 Boom-0.9/Boom/src/sufstats.cpp                                                                                     |    4 
 521 files changed, 10999 insertions(+), 6306 deletions(-)

More information about Boom at CRAN
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Package SNPknock updated to version 0.8.2 with previous version 0.7.1 dated 2018-05-30

Title: Knockoffs for Hidden Markov Models and Genetic Data
Description: Generate knockoffs for genetic data and hidden Markov models. For more information, see the website below and the accompanying papers: "Gene hunting with hidden Markov model knockoffs", Sesia et al., Biometrika, 2019, (<doi:10.1093/biomet/asy033>). "Multi-resolution localization of causal variants across the genome", Sesia et al., bioRxiv, 2019, (<doi:10.1101/631390>).
Author: Matteo Sesia [aut, cre]
Maintainer: Matteo Sesia <msesia@stanford.edu>

Diff between SNPknock versions 0.7.1 dated 2018-05-30 and 0.8.2 dated 2019-05-17

 SNPknock-0.7.1/SNPknock/man/GenotypeModel_wrapper.Rd         |only
 SNPknock-0.7.1/SNPknock/man/HaplotypeModel_wrapper.Rd        |only
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Package RECA updated to version 1.7 with previous version 1.6 dated 2018-05-16

Title: Relevant Component Analysis for Supervised Distance Metric Learning
Description: Relevant Component Analysis (RCA) tries to find a linear transformation of the feature space such that the effect of irrelevant variability is reduced in the transformed space.
Author: Nan Xiao [aut, cre] (<https://orcid.org/0000-0002-0250-5673>)
Maintainer: Nan Xiao <me@nanx.me>

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Package Delaporte updated to version 7.0.2 with previous version 7.0.1 dated 2019-04-05

Title: Statistical Functions for the Delaporte Distribution
Description: Provides probability mass, distribution, quantile, random-variate generation, and method-of-moments parameter-estimation functions for the Delaporte distribution. The Delaporte is a discrete probability distribution which can be considered the convolution of a negative binomial distribution with a Poisson distribution. Alternatively, it can be considered a counting distribution with both Poisson and negative binomial components. It has been studied in actuarial science as a frequency distribution which has more variability than the Poisson, but less than the negative binomial.
Author: Avraham Adler [aut, cph, cre] (<https://orcid.org/0000-0002-3039-0703>)
Maintainer: Avraham Adler <Avraham.Adler@gmail.com>

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Package msaenet updated to version 3.1 with previous version 3.0 dated 2018-12-14

Title: Multi-Step Adaptive Estimation Methods for Sparse Regressions
Description: Multi-step adaptive elastic-net (MSAENet) algorithm for feature selection in high-dimensional regressions proposed in Xiao and Xu (2015) <DOI:10.1080/00949655.2015.1016944>, with support for multi-step adaptive MCP-net (MSAMNet) and multi-step adaptive SCAD-net (MSASNet) methods.
Author: Nan Xiao [aut, cre] (<https://orcid.org/0000-0002-0250-5673>), Qing-Song Xu [aut]
Maintainer: Nan Xiao <me@nanx.me>

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Package CorrToolBox updated to version 1.6.1 with previous version 1.6 dated 2019-03-03

Title: Modeling Correlational Magnitude Transformations in Discretization Contexts
Description: Modeling the correlation transitions under specified distributional assumptions within the realm of discretization in the context of the latency and threshold concepts. The details of the method are explained in Demirtas, H. and Vardar-Acar, C. (2017) <DOI:10.1007/978-981-10-3307-0_4>.
Author: Rawan Allozi, Hakan Demirtas, Ran Gao
Maintainer: Ran Gao <rgao8@uic.edu>

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Package qs updated to version 0.16.1 with previous version 0.15.1 dated 2019-04-07

Title: Quick Serialization of R Objects
Description: Provides functions for quickly writing and reading any R object to and from disk.
Author: Travers Ching [aut, cre, cph], Yann Collet [ctb, cph] (Yann Collet is the author of the bundled zstd and lz4 code), Facebook, Inc. [cph] (Facebook is the copyright holder of the bundled zstd code), Reichardt Tino [ctb, cph] (Contributor/copyright holder of zstd bundled code), Skibinski Przemyslaw [ctb, cph] (Contributor/copyright holder of zstd bundled code), Mori Yuta [ctb, cph] (Contributor/copyright holder of zstd bundled code), Romain Francois [ctb, cph] (Derived example/tutorials for Alt-Rep structures), Francesc Alted [ctb, cph] (Shuffling routines derived from Blosc library)
Maintainer: Travers Ching <traversc@gmail.com>

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Package svglite updated to version 1.2.2 with previous version 1.2.1 dated 2017-09-11

Title: An 'SVG' Graphics Device
Description: A graphics device for R that produces 'Scalable Vector Graphics'. 'svglite' is a fork of the older 'RSvgDevice' package.
Author: Hadley Wickham [aut], Lionel Henry [aut, cre], T Jake Luciani [aut], Matthieu Decorde [aut], Vaudor Lise [aut], Tony Plate [ctb] (Early line dashing code), David Gohel [ctb] (Line dashing code and raster code), Yixuan Qiu [ctb] (Improved styles; polypath implementation), Håkon Malmedal [ctb] (Opacity code), RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>

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Package SPOT updated to version 2.0.4 with previous version 2.0.3 dated 2018-05-14

Title: Sequential Parameter Optimization Toolbox
Description: A set of tools for model based optimization and tuning of algorithms. It includes surrogate models, optimizers and design of experiment approaches. The main interface is spot, which uses sequentially updated surrogate models for the purpose of efficient optimization. The main goal is to ease the burden of objective function evaluations, when a single evaluation requires a significant amount of resources.
Author: Thomas Bartz-Beielstein [aut], Joerg Stork [aut], Martin Zaefferer [aut, cre], Margarita Rebolledo [ctb], Christian Lasarczyk [ctb], Joerg Ziegenhirt [ctb], Wolfgang Konen [ctb], Oliver Flasch [ctb], Patrick Koch [ctb], Martina Friese [ctb], Lorenzo Gentile [ctb], Frederik Rehbach [ctb]
Maintainer: Martin Zaefferer <martin.zaefferer@gmx.de>

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Package CrossVA updated to version 0.9.8 with previous version 0.9.7 dated 2019-04-21

Title: Verbal Autopsy Data Transformation for InSilicoVA and InterVA5 Algorithms
Description: Enables transformation of Verbal Autopsy data collected with the WHO 2016 questionnaire (versions 1.4.1 & 1.5.1) or the WHO 2014 questionnaire for automated coding of Cause of Death using the InSilicoVA (data.type = "WHO2016") and InterVA5 algorithms. Previous versions of this package supported user-supplied mappings (via the map_records function), but this functionality has been removed. This package is made available by WHO and the Bloomberg Data for Health Initiative.
Author: Peter Byass [aut], Eungang Choi [aut], Sam Clark [aut], Zehang Li [aut], Nicolas Maire [aut], Tyler McCormick [aut], Jason Thomas [aut, cre]
Maintainer: Jason Thomas <jarathomas@gmail.com>

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New package tokenbrowser with initial version 0.1.0
Package: tokenbrowser
Type: Package
Title: Create Full Text Browsers from Annotated Token Lists
Version: 0.1.0
Author: Kasper Welbers and Wouter van Atteveldt
Maintainer: Kasper Welbers <kasperwelbers@gmail.com>
License: GPL-3
Depends: R (>= 2.10)
Imports: methods, Rcpp, stringi
Suggests: testthat
LinkingTo: Rcpp
LazyData: true
Description: Create browsers for reading full texts from a token list format. Information obtained from text analyses (e.g., topic modeling, word scaling) can be used to annotate the texts.
SystemRequirements: C++11
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-05-17 14:35:54 UTC; kasper
Repository: CRAN
Date/Publication: 2019-05-17 16:20:04 UTC

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New package AFheritability with initial version 0.1.0
Package: AFheritability
Type: Package
Title: The Attributable Fraction (AF) Described as a Function of Disease Heritability, Prevalence and Intervention Specific Factors
Version: 0.1.0
Author: Elisabeth Dahlqwist
Maintainer: Elisabeth Dahlqwist <elisabeth.dahlqwist88@gmail.com>
Description: The AFfunction() is a function which returns an estimate of the Attributable Fraction (AF) and a plot of the AF as a function of heritability, disease prevalence, size of target group and intervention effect. Since the AF is a function of several factors, a shiny app is used to better illustrate how the relationship between the AF and heritability depends on several other factors. The app is ran by the function runShinyApp(). For more information see Dahlqwist E et al. (2019) <doi:10.1007/s00439-019-02006-8>.
License: GPL-2 | GPL-3
Depends: reshape2, mvtnorm, ggplot2, shiny
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-17 16:18:29 UTC; elidah
Repository: CRAN
Date/Publication: 2019-05-17 16:40:03 UTC

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New package ADAPTS with initial version 0.9.14
Package: ADAPTS
Type: Package
Title: Automated Deconvolution Augmentation of Profiles for Tissue Specific Cells
Version: 0.9.14
Author: Samuel A Danziger
Maintainer: Samuel A Danziger <sam.danziger@gmail.com>
Copyright: Celgene Corporation
Description: Augments existing or de-novo cell-type signature matrices to deconvolve bulk gene expression data. This package expands on the techniques outlined in Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, Hoang CD, Diehn M, Alizadeh, AA (2015) <doi:10.1038/nmeth.3337>'s Nature Methods paper: 'Robust enumeration of cell subsets from tissue expression profiles' to allow a user to easily add their own cell types (e.g. a tumor specific cell type) to Newman's LM22 or other signature matrix.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.3.0)
biocViews:
Imports: missForest, e1071, WGCNA, ComICS, pheatmap, doParallel, quantmod, preprocessCore, pcaMethods, foreach, DeconRNASeq
Suggests: R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2019-05-17 01:18:32 UTC; sdanziger
Repository: CRAN
Date/Publication: 2019-05-17 16:00:03 UTC

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New package PLNmodels with initial version 0.9.2
Package: PLNmodels
Title: Poisson Lognormal Models
Version: 0.9.2
Authors@R: c( person("Julien", "Chiquet", role = c("aut", "cre"), email = "julien.chiquet@inra.fr", comment = c(ORCID = "0000-0002-3629-3429")), person("Mahendra", "Mariadassou", role = "aut", email = "mahendra.mariadassou@inra.fr", comment = c(ORCID = "0000-0003-2986-354X")), person("Stéphane", "Robin", role ="ctb", email = "stephane.robin@inra.fr") )
Description: The Poisson-lognormal model and variants can be used for a variety of multivariate problems when count data are at play, including principal component analysis for count data (Chiquet, Mariadassou and Robin, 2018 <doi:10.1214/18-AOAS1177>), discriminant analysis and network inference (Chiquet, Mariadassou and Robin, 2018 <arXiv:1806.03120>). Implements variational algorithms to fit such models accompanied with a set of functions for visualization and diagnostic.
URL: https://jchiquet.github.io/PLNmodels/
BugReports: https://github.com/jchiquet/PLNmodels/issues
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 6.1.1
Depends: R (>= 3.4)
biocViews:
Imports: methods, stats, MASS, parallel, R6, glassoFast, Matrix, Rcpp, nloptr (>= 1.2.0), igraph, grid, gridExtra, dplyr, tidyr, ggplot2, corrplot, magrittr, biomformat, phyloseq
Suggests: knitr, rmarkdown, GGally, testthat, covr, pkgdown
LinkingTo: Rcpp, RcppArmadillo, nloptr (>= 1.2.0)
VignetteBuilder: knitr
Collate: 'PLNfit-class.R' 'PLN.R' 'PLNLDA.R' 'PLNLDAfit-S3methods.R' 'PLNLDAfit-class.R' 'PLNPCA.R' 'PLNPCAfamily-S3methods.R' 'PLNfamily-class.R' 'PLNPCAfamily-class.R' 'PLNPCAfit-S3methods.R' 'PLNPCAfit-class.R' 'PLNfamily-S3methods.R' 'PLNfit-S3methods.R' 'PLNmodels-package.R' 'PLNnetwork.R' 'PLNnetworkfamily-S3methods.R' 'PLNnetworkfamily-class.R' 'PLNnetworkfit-S3methods.R' 'PLNnetworkfit-class.R' 'RcppExports.R' 'deprecated.R' 'import_utils.R' 'mollusk.R' 'plot_utils.R' 'trichoptera.R' 'utils-pipe.R' 'utils.R'
NeedsCompilation: yes
Packaged: 2019-05-16 20:14:19 UTC; jchiquet
Author: Julien Chiquet [aut, cre] (<https://orcid.org/0000-0002-3629-3429>), Mahendra Mariadassou [aut] (<https://orcid.org/0000-0003-2986-354X>), Stéphane Robin [ctb]
Maintainer: Julien Chiquet <julien.chiquet@inra.fr>
Repository: CRAN
Date/Publication: 2019-05-17 15:20:03 UTC

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New package oceanis with initial version 0.8.4
Package: oceanis
Type: Package
Title: Cartography for Statistical Analysis
Version: 0.8.4
Date: 2019-05-17
Author: Sébastien CALVET [cre, aut], Sophie AUDRIC [aut]
Maintainer: Sébastien CALVET <sebastien.calvet@insee.fr>
Description: Creating maps for statistical analysis such as proportional circles, chroropleth, typology and flows. Some functions use 'shiny' or 'leaflet' technologies for dynamism and interactivity. The great features are : - Create maps in a web environment where the parameters are modifiable on the fly ('shiny' and 'leaflet' technology). - Create interactive maps through zoom and pop-up ('leaflet' technology). - Create frozen maps with the possibility to add labels.
License: GPL (>= 2.0)
LazyLoad: yes
Depends: R (>= 3.3.0),shiny (>= 1.0.5),shinyBS (>= 0.61)
Imports: utils (>= 3.3.3),shinyjs (>= 1.0),shinythemes (>= 1.1.1),DT (>= 0.2),foreign (>= 0.8.67),sf (>= 0.6.3),sfc (>= 0.1.0),stringr (>= 1.2.0),leaflet (>= 2.0.2),leaflet.extras (>= 1.0.0),classInt(>= 0.2.3),units (>= 0.6.0),grDevices (>= 3.3.3),readODS (>= 1.6.7),xlsx (>= 0.5.7),ggplot2 (>= 2.2.1),dplyr (>= 0.7.2),graphics (>= 3.3.3),mapview (>= 2.5.0),tidyr (>= 0.7.1),munsell (>= 0.5.0),lwgeom (>= 0.1.4)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-05-17 07:43:22 UTC; zz0srj
Repository: CRAN
Date/Publication: 2019-05-17 15:30:03 UTC

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Package dqrng updated to version 0.2.1 with previous version 0.2.0 dated 2019-04-22

Title: Fast Pseudo Random Number Generators
Description: Several fast random number generators are provided as C++ header only libraries: The PCG family by O'Neill (2014 <https://www.cs.hmc.edu/tr/hmc-cs-2014-0905.pdf>) as well as Xoroshiro128+ and Xoshiro256+ by Blackman and Vigna (2018 <arXiv:1805.01407>). In addition fast functions for generating random numbers according to a uniform, normal and exponential distribution are included. The latter two use the Ziggurat algorithm originally proposed by Marsaglia and Tsang (2000, <doi:10.18637/jss.v005.i08>). These functions are exported to R and as a C++ interface and are enabled for use with the default 64 bit generator from the PCG family, Xoroshiro128+ and Xoshiro256+ as well as the 64 bit version of the 20 rounds Threefry engine (Salmon et al., 2011 <doi:10.1145/2063384.2063405>) as provided by the package 'sitmo'.
Author: Ralf Stubner [aut, cre], daqana GmbH [cph], David Blackman [ctb], Melissa O'Neill [ctb], Sebastiano Vigna [ctb], Aaron Lun [ctb]
Maintainer: Ralf Stubner <ralf.stubner@gmail.com>

Diff between dqrng versions 0.2.0 dated 2019-04-22 and 0.2.1 dated 2019-05-17

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New package CodataGS with initial version 1.43
Package: CodataGS
Type: Package
Title: Genomic Prediction Using SNP Codata
Version: 1.43
Date: 2019-05-17
Author: Lars Ronnegard
Maintainer: Lars Ronnegard <lrn@du.se>
Description: Computes genomic breeding values using external information on the markers. The package fits a linear mixed model with heteroscedastic random effects, where the random effect variance is fitted using a linear predictor and a log link. The method is described in Mouresan, Selle and Ronnegard (2019) <doi:10.1101/636746>.
License: GPL
Depends: Matrix
NeedsCompilation: no
Packaged: 2019-05-17 12:09:05 UTC; lrn
Repository: CRAN
Date/Publication: 2019-05-17 15:40:07 UTC

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New package prettyB with initial version 0.2.1
Package: prettyB
Type: Package
Title: Pretty Base Graphics
Version: 0.2.1
Authors@R: person(given="Colin", family="Gillespie", email="csgillespie@gmail.com", role = c("aut", "cre"))
Maintainer: Colin Gillespie <csgillespie@gmail.com>
Description: Drop-in replacements for standard base graphics functions. The replacements are prettier versions of the originals.
URL: https://github.com/jumpingrivers/prettyB/
BugReports: https://github.com/jumpingrivers/prettyB//issues
License: GPL-2 | GPL-3
Imports: grDevices, stats, graphics
Suggests: testthat, vdiffr, covr, lintr, knitr
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-17 07:35:20 UTC; ncsg3
Author: Colin Gillespie [aut, cre]
Repository: CRAN
Date/Publication: 2019-05-17 14:20:04 UTC

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New package plotdap with initial version 0.0.2
Package: plotdap
Title: Easily Visualize Data from 'ERDDAP' Servers via the 'rerddap' Package
Version: 0.0.2
Date: 2019-04-29
Authors@R: c( person("Carson", "Sievert", role = "aut"), person("Roy", "Mendelssohn", role = c("aut", "ctb", "cre"), email = "roy.mendelssohn@noaa.gov"))
Description: Easily visualize and animate 'tabledap' and 'griddap' objects obtained via the 'rerddap' package in a simple one-line command, using either base graphics or 'ggplot2' graphics. 'plotdap' handles extracting and reshaping the data, map projections and continental outlines. Optionally the data can be animated through time using the 'gganmiate' package.
License: MIT + file LICENSE
URL: https://github.com/ropensci/plotdap
BugReports: https://github.com/ropensci/plotdap/issues
Depends: R (>= 3.5.0), rerddap
Imports: dplyr, gganimate, ggplot2 (>= 3.1.0), lazyeval, lubridate, magrittr, mapdata, maps (>= 3.2.0), maptools, plot3D, rgdal, rgeos, raster, scales, sf, tidyr
Suggests: testthat, Cairo, knitr, rmarkdown
RoxygenNote: 6.1.1
LazyData: true
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-03 01:01:13 UTC; rmendels
Author: Carson Sievert [aut], Roy Mendelssohn [aut, ctb, cre]
Maintainer: Roy Mendelssohn <roy.mendelssohn@noaa.gov>
Repository: CRAN
Date/Publication: 2019-05-17 15:00:03 UTC

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Package partykit updated to version 1.2-4 with previous version 1.2-3 dated 2019-01-31

Title: A Toolkit for Recursive Partytioning
Description: A toolkit with infrastructure for representing, summarizing, and visualizing tree-structured regression and classification models. This unified infrastructure can be used for reading/coercing tree models from different sources ('rpart', 'RWeka', 'PMML') yielding objects that share functionality for print()/plot()/predict() methods. Furthermore, new and improved reimplementations of conditional inference trees (ctree()) and model-based recursive partitioning (mob()) from the 'party' package are provided based on the new infrastructure. A description of this package was published by Hothorn and Zeileis (2015) <http://jmlr.org/papers/v16/hothorn15a.html>.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>), Heidi Seibold [ctb] (<https://orcid.org/0000-0002-8960-9642>), Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between partykit versions 1.2-3 dated 2019-01-31 and 1.2-4 dated 2019-05-17

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Package dslabs updated to version 0.6.0 with previous version 0.5.2 dated 2018-12-19

Title: Data Science Labs
Description: Datasets and functions that can be used for data analysis practice, homework and projects in data science courses and workshops.
Author: Rafael A. Irizarry, Amy Gill
Maintainer: Rafael A. Irizarry <rafa@jimmy.harvard.edu>

Diff between dslabs versions 0.5.2 dated 2018-12-19 and 0.6.0 dated 2019-05-17

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Package MBESS updated to version 4.5.1 with previous version 4.5.0 dated 2019-05-14

Title: The MBESS R Package
Description: Implements methods that useful in designing research studies and analyzing data, with particular emphasis on methods that are developed for or used within the behavioral, educational, and social sciences (broadly defined). That being said, many of the methods implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a suite of functions for a variety of related topics, such as effect sizes, confidence intervals for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and minimum-risk point estimation perspectives), mediation analysis, various properties of distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but at this point MBESS contains methods applicable and used in a wide variety of fields and is an orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has greatly benefited from others, see <http://nd.edu/~kkelley/site/MBESS.html> for a detailed list of those that have contributed and other details.
Author: Ken Kelley [aut, cre]
Maintainer: Ken Kelley <kkelley@nd.edu>

Diff between MBESS versions 4.5.0 dated 2019-05-14 and 4.5.1 dated 2019-05-17

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Package ggPMX updated to version 0.9.2 with previous version 0.9.1 dated 2019-05-16

Title: 'ggplot2' Based Tool to Facilitate Diagnostic Plots for NLME Models
Description: At Novartis, we aimed at standardizing the set of diagnostic plots used for modeling activities in order to reduce the overall effort required for generating such plots. For this, we developed a guidance that proposes an adequate set of diagnostics and a toolbox, called 'ggPMX' to execute them. 'ggPMX' is a toolbox that can generate all diagnostic plots at a quality sufficient for publication and submissions using few lines of code.
Author: Amine Gassem [cre, aut], Bruno Bieth [aut], Irina Baltcheva [aut], Thomas Dumortier [aut], Christian Bartels [aut], Souvik Bhattacharya [aut], Inga Ludwig [aut], Ines Paule [aut], Didier Renard [aut], Qing Xi Ooi [ctr], Novartis Pharma AG [cph]
Maintainer: Amine Gassem <contact@ag-study.com>

Diff between ggPMX versions 0.9.1 dated 2019-05-16 and 0.9.2 dated 2019-05-17

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Package egoTERGM updated to version 2.1.1 with previous version 2.1.0 dated 2019-02-05

Title: Estimation of Ego-Temporal Exponential Random Graph Models via Expectation Maximization (EM)
Description: Estimation of ego-temporal exponential random graph models with two-stage estimation including initialization through k-means clustering on temporal exponential random graph model parameters and EM as per Campbell (2018) <doi:10.7910/DVN/TWHEZ9>.
Author: Benjamin W. Campbell [aut, cre], Michael Salter-Townshend [ctb], Thomas Brendan Murphy [ctb]
Maintainer: Benjamin W. Campbell <campbell.1721@osu.edu>

Diff between egoTERGM versions 2.1.0 dated 2019-02-05 and 2.1.1 dated 2019-05-17

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New package statsguRu with initial version 0.1.0
Type: Package
Package: statsguRu
Version: 0.1.0
Title: Extract, Visualize and Analyze Cricket Statistics from ESPNCricinfo's Statsguru
Description: Use this package to scrap Test Matches, One Day Internationals, Twenty-20 Internationals data of a player from ESPNCricinfo's Statsguru (<http://stats.espncricinfo.com/ci/engine/stats/index.html>) and then visualize their batting, bowling and fielding performances in the form of charts and graphs.
Author: Pranav Nagarajan
Maintainer: Pranav Nagarajan <npranav10@gmail.com>
URL: https://github.com/npranav10/statsguRu
BugReports: https://github.com/npranav10/statsguRu/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: htmltab,plotrix,devtools,grDevices,graphics,utils
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-17 08:54:51 UTC; Pranav N
Repository: CRAN
Date/Publication: 2019-05-17 11:50:41 UTC

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Package rspa updated to version 0.2.4 with previous version 0.2.3 dated 2018-07-30

Title: Adapt Numerical Records to Fit (in)Equality Restrictions
Description: Minimally adjust the values of numerical records in a data.frame, such that each record satisfies a predefined set of equality and/or inequality constraints. The constraints can be defined using the 'validate' package. The core algorithms have recently been moved to the 'lintools' package, refer to 'lintools' for a more basic interface and access to a version of the algorithm that works with sparse matrices.
Author: Mark van der Loo
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>

Diff between rspa versions 0.2.3 dated 2018-07-30 and 0.2.4 dated 2019-05-17

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Package parallelMap updated to version 1.4 with previous version 1.3 dated 2015-06-09

Title: Unified Interface to Parallelization Back-Ends
Description: Unified parallelization framework for multiple back-end, designed for internal package and interactive usage. The main operation is parallel mapping over lists. Supports 'local', 'multicore', 'mpi' and 'BatchJobs' mode. Allows tagging of the parallel operation with a level name that can be later selected by the user to switch on parallel execution for exactly this operation.
Author: Bernd Bischl [cre, aut], Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>)
Maintainer: Bernd Bischl <bernd_bischl@gmx.net>

Diff between parallelMap versions 1.3 dated 2015-06-09 and 1.4 dated 2019-05-17

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 parallelMap-1.4/parallelMap/tests/testthat/test_batchtools.R   |only
 parallelMap-1.4/parallelMap/tests/testthat/test_local.R        |    2 
 parallelMap-1.4/parallelMap/tests/testthat/test_mpi.R          |    6 
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 34 files changed, 296 insertions(+), 140 deletions(-)

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Package coloc updated to version 3.2-1 with previous version 3.1 dated 2018-02-24

Title: Colocalisation Tests of Two Genetic Traits
Description: Performs the colocalisation tests described in Plagnol et al (2009) <doi:10.1093/biostatistics/kxn039>, Wallace et al (2013) <doi:10.1002/gepi.21765> and Giambartolomei et al (2013) <doi:10.1371/journal.pgen.1004383>.
Author: Chris Wallace [aut, cre], Claudia Giambartolomei [aut], Vincent Plagnol [ctb]
Maintainer: Chris Wallace <cew54@cam.ac.uk>

Diff between coloc versions 3.1 dated 2018-02-24 and 3.2-1 dated 2019-05-17

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New package pulseTD with initial version 0.1.0
Package: pulseTD
Type: Package
Title: Identification of Transcriptional Dynamics using Pulse Models via 4su-Seq Data and RNA-Seq Data
Version: 0.1.0
Date: 2019-5-5
Author: XinWang
Maintainer: XinWang <xindd_2014@163.com>
Description: A tool for analyzing the transcription, processing and degradation rates of genes by 4sU-seq (the Metabolic Label 4-thiouridine) data and RNA-seq (RNA sequencing) data. It can not only recognize the transcriptional dynamic rates at the measurement time points, but also obtain continuous changes in transcriptional dynamics. More importantly, it is able to predict the trend of mRNA (Mature RNA) transcription and expression changes in the future.
License: GPL-2
Encoding: UTF-8
Depends: R (>= 3.4.0)
biocViews:
Imports: AnnotationDbi, SummarizedExperiment, Rsamtools, Biobase, S4Vectors, methods, parallel, GenomicFeatures, ggplot2, grid, GenomicAlignments
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, TxDb.Hsapiens.UCSC.hg19.knownGene
URL: https://github.com/bioWzz/pulseTD_0.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-17 01:32:57 UTC; Administrator
Repository: CRAN
Date/Publication: 2019-05-17 09:20:03 UTC

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New package CGE with initial version 0.1.8
Package: CGE
Type: Package
Title: Computing General Equilibrium
Version: 0.1.8
Author: LI Wu <liwu@staff.shu.edu.cn>
Maintainer: LI Wu <liwu@staff.shu.edu.cn>
Description: Developing general equilibrium models, computing general equilibrium and simulating economic dynamics with structural dynamic models in LI (2019, ISBN: 9787521804225) "General Equilibrium and Structural Dynamics: Perspectives of New Structural Economics. Beijing: Economic Science Press".
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-17 01:12:11 UTC; Administrator
Repository: CRAN
Date/Publication: 2019-05-17 09:20:17 UTC

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New package sparseMatEst with initial version 1.0.0
Package: sparseMatEst
Type: Package
Title: Sparse Matrix Estimation and Inference
Version: 1.0.0
Authors@R: c( person(given="Adam B", family="Kashlak", email = "kashlak@ualberta.ca", role = c("aut", "cre")), person(given="Xinyu", family="Zhang", role = c("ctb")) )
Author: Adam B Kashlak [aut, cre], Xinyu Zhang [ctb]
Maintainer: Adam B Kashlak <kashlak@ualberta.ca>
Description: The 'sparseMatEst' package provides functions for estimating sparse covariance and precision matrices with error control. A false positive rate is fixed corresponding to the probability of falsely including a matrix entry in the support of the estimator. It uses the binary search method outlined in Kashlak and Kong (2019) <arXiv:1705.02679> and in Kashlak (2019) <arXiv:1903.10988>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: stats, glasso
NeedsCompilation: no
Packaged: 2019-05-17 03:30:20 UTC; AdKas
Repository: CRAN
Date/Publication: 2019-05-17 08:20:05 UTC

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Package rlmDataDriven updated to version 0.3.0 with previous version 0.2.1 dated 2019-03-12

Title: Robust Regression with Data Driven Tuning Parameter
Description: Data driven approach for robust regression estimation in homoscedastic and heteroscedastic context. See Wang et al. (2007), <doi:10.1198/106186007X180156> regarding homoscedastic framework.
Author: You-Gan Wang
Maintainer: You-Gan Wang <you-gan.wang@qut.edu.au>

Diff between rlmDataDriven versions 0.2.1 dated 2019-03-12 and 0.3.0 dated 2019-05-17

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New package matahari with initial version 0.1.0
Package: matahari
Type: Package
Title: Spy on Your R Session
Version: 0.1.0
Authors@R: c( person("Sean", "Kross", email = "sean@seankross.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5215-0316")), person("Lucy", "D'Agostino McGowan", email = "lucydagostino@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-7297-9359")), person("Jeff", "Leek", email = "jtleek@gmail.com", role = "ldr", comment = c(ORCID = "0000-0002-2873-2671")) )
Description: Conveniently log everything you type into the R console. Logs are are stored as tidy data frames which can then be analyzed using 'tidyverse' style tools.
Depends: R (>= 3.5.0)
Imports: rstudioapi, tibble, readr, jsonlite, clipr, purrr, rlang
Suggests: testthat, knitr, rmarkdown
License: MIT + file LICENSE
URL: https://github.com/jhudsl/matahari
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
BugReports: https://github.com/jhudsl/matahari/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-17 02:20:00 UTC; sean
Author: Sean Kross [aut, cre] (<https://orcid.org/0000-0001-5215-0316>), Lucy D'Agostino McGowan [aut] (<https://orcid.org/0000-0001-7297-9359>), Jeff Leek [ldr] (<https://orcid.org/0000-0002-2873-2671>)
Maintainer: Sean Kross <sean@seankross.com>
Repository: CRAN
Date/Publication: 2019-05-17 08:20:12 UTC

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Package jskm updated to version 0.3.5 with previous version 0.3.1 dated 2019-03-12

Title: Kaplan-Meier Plot with 'ggplot2'
Description: The function 'jskm()' creates publication quality Kaplan-Meier plot with at risk tables below. 'svyjskm()' provides plot for weighted Kaplan-Meier estimator.
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>), Zarathu [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

Diff between jskm versions 0.3.1 dated 2019-03-12 and 0.3.5 dated 2019-05-17

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Package JMcmprsk updated to version 0.9.4 with previous version 0.9.3 dated 2017-12-10

Title: Joint Models for Longitudinal Measurements and Competing Risks Failure Time Data
Description: Fit joint models of continuous or ordinal longitudinal data and time-to-event data with competing risks. For a detailed information, see Robert Elashoff, Gang li and Ning Li (2016, ISBN:9781439807828) ; Robert M. Elashoff,Gang Li and Ning Li (2008) <doi:10.1111/j.1541-0420.2007.00952.x> ; Ning Li, Robert Elashoff, Gang Li and Jeffrey Saver (2010) <doi:10.1002/sim.3798> .
Author: Hong Wang<wh@csu.edu.cn>, Ning Li<nli@biomath.ucla.edu> and Gang Li<vli@ucla.edu>
Maintainer: Hong Wang <wh@csu.edu.cn>

Diff between JMcmprsk versions 0.9.3 dated 2017-12-10 and 0.9.4 dated 2019-05-17

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Package fclust updated to version 2.1 with previous version 2.0.1 dated 2018-10-22

Title: Fuzzy Clustering
Description: Algorithms for fuzzy clustering, cluster validity indices and plots for cluster validity and visualizing fuzzy clustering results.
Author: Paolo Giordani, Maria Brigida Ferraro, Alessio Serafini
Maintainer: Paolo Giordani <paolo.giordani@uniroma1.it>

Diff between fclust versions 2.0.1 dated 2018-10-22 and 2.1 dated 2019-05-17

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Package AnalyzeFMRI updated to version 1.1-18 with previous version 1.1-17 dated 2018-05-14

Title: Functions for Analysis of fMRI Datasets Stored in the ANALYZE or NIFTI Format
Description: Functions for I/O, visualisation and analysis of functional Magnetic Resonance Imaging (fMRI) datasets stored in the ANALYZE or NIFTI format. Note that the latest version of XQuartz seems to be necessary under MacOS.
Author: Pierre Lafaye De Micheaux [aut, cre], Jonathan L Marchini [aut]
Maintainer: Pierre Lafaye De Micheaux <lafaye@unsw.edu.au>

Diff between AnalyzeFMRI versions 1.1-17 dated 2018-05-14 and 1.1-18 dated 2019-05-17

 DESCRIPTION                      |   19 ++-
 MD5                              |   12 +-
 inst/HISTORY                     |   11 ++
 src/Makevars.in                  |    2 
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 src/spatial.filters.non.linear.c |    3 
 7 files changed, 193 insertions(+), 161 deletions(-)

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New package yarr with initial version 0.1.1
Package: yarr
Type: Package
Title: Yet Another 'ARFF' Reader
Version: 0.1.1
Authors@R: c(person("David", "Charte", email = "fdavidcl@ugr.es", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4830-9512")), person("Francisco", "Charte", email = "francisco@fcharte.com", role = "aut", comment = c(ORCID = "0000-0002-3083-8942")))
Description: A parser and a writer for 'WEKA' Attribute-Relation File Format <https://waikato.github.io/weka-wiki/arff_stable/> in pure R, with no dependencies. As opposed to other R implementations, this package can read standard (dense) as well as sparse files, i.e. those where each row does only contain nonzero components. Unlike 'RWeka', 'yarr' does not require any 'Java' installation nor is dependent on external software. This implementation is generalized from those in packages 'mldr' and 'mldr.datasets'.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
URL: https://github.com/fdavidcl/yarr
BugReports: https://github.com/fdavidcl/yarr/issues
Depends: R (>= 3.6)
Suggests: testthat (>= 2.1.0)
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-16 18:18:28 UTC; fdavidcl
Author: David Charte [aut, cre] (<https://orcid.org/0000-0002-4830-9512>), Francisco Charte [aut] (<https://orcid.org/0000-0002-3083-8942>)
Maintainer: David Charte <fdavidcl@ugr.es>
Repository: CRAN
Date/Publication: 2019-05-17 07:20:04 UTC

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New package SMARTp with initial version 0.1.1
Package: SMARTp
Type: Package
Title: Sample Size for SMART Designs in Non-Surgical Periodontal Trials
Version: 0.1.1
Author: Jing Xu, Dipankar Bandyopadhyay, Douglas Azevedo, Bibhas Chakraborty
Maintainer: Dipankar Bandyopadhyay <bandyopd@gmail.com>
Description: Sample size calculation to detect dynamic treatment regime (DTR) effects based on change in clinical attachment level (CAL) outcomes from a non-surgical chronic periodontitis treatments study. The experiment is performed under a Sequential Multiple Assignment Randomized Trial (SMART) design. The clustered tooth (sub-unit) level CAL outcomes are skewed, spatially-referenced, and non-randomly missing. The implemented algorithm is available in Xu et al. (2019+) <arXiv:1902.09386>.
Depends: R (>= 3.5)
Imports: covr, sn (>= 1.5), mvtnorm (>= 1.0), stats, methods
URL: https://github.com/bandyopd/SMARTp
License: LGPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-16 16:32:55 UTC; douglas
Repository: CRAN
Date/Publication: 2019-05-17 07:10:04 UTC

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New package Rbeast with initial version 0.1
Package: Rbeast
Type: Package
Version: 0.1
Date: 2019-05-08
Title: Bayesian Change-Point Detection and Time Series Decomposition
Authors@R: c(person(given = "Kaiguang", family = "Zhao", role = c("aut", "cre"), email = "lidar.rs@gmail.com"), person(given = "Tongxi", family = "Hu", role = "aut", email = "hu.1555@osu.edu"), person(given = "Yang", family = "Li", role = "aut", email = "li.10015@osu.edu") )
Author: Kaiguang Zhao [aut, cre], Tongxi Hu [aut], Yang Li [aut]
Maintainer: Kaiguang Zhao <lidar.rs@gmail.com>
Depends: R (>= 2.10.0),methods, utils
Description: Interpretation of time series data is affected by model choices. Different models can give different or even contradicting estimates of patterns, trends, and mechanisms for the same data--a limitation alleviated by the Bayesian estimator of abrupt change,seasonality, and trend (BEAST) of this package. BEAST seeks to improve time series decomposition by forgoing the "single-best-model" concept and embracing all competing models into the inference via a Bayesian model averaging scheme. It is a flexible tool to uncover abrupt changes (i.e., change-points), cyclic variations (e.g., seasonality), and nonlinear trends in time-series observations. BEAST not just tells when changes occur but also quantifies how likely the detected changes are true. It detects not just piecewise linear trends but also arbitrary nonlinear trends. BEAST is applicable to real-valued time series data of all kinds, be it for remote sensing, economics, climate sciences, ecology, and hydrology. Example applications include its use to identify regime shifts in ecological data, map forest disturbance and land degradation from satellite imagery, detect market trends in economic data, pinpoint anomaly and extreme events in climate data, and unravel system dynamics in biological data. Details on BEAST are reported in Zhao et al. (2019).
LazyData: true
License: GPL (>= 2)
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2019-05-16 15:09:51 UTC; zhaokg
Repository: CRAN
Date/Publication: 2019-05-17 07:00:35 UTC

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Package radarBoxplot updated to version 1.0.0 with previous version 0.2.6 dated 2019-05-13

Title: Implementation of the Radar-Boxplot
Description: Creates the radar-boxplot, a plot that was created by the author during his doctoring in forest resources. The radar-boxplot is a visualization feature suited for multivariate classification/clustering. It provides an intuitive deep understanding of the data.
Author: Caio Hamamura [aut, cre]
Maintainer: Caio Hamamura <caiohamamura@gmail.com>

Diff between radarBoxplot versions 0.2.6 dated 2019-05-13 and 1.0.0 dated 2019-05-17

 DESCRIPTION             |   12 -
 MD5                     |   14 -
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 R/utils.R               |  105 +++++++++
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 man/figures/Example.png |binary
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 8 files changed, 523 insertions(+), 238 deletions(-)

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New package partition with initial version 0.1.0
Package: partition
Type: Package
Title: Agglomerative Partitioning Framework for Dimension Reduction
Version: 0.1.0
Authors@R: c( person( "Joshua", "Millstein", role = "aut", email = "joshua.millstein@usc.edu"), person( "Malcolm", "Barrett", role = c("aut", "cre"), email = "malcolmbarrett@gmail.com", comment = c(ORCID = "0000-0003-0299-5825")))
Maintainer: Malcolm Barrett <malcolmbarrett@gmail.com>
Description: A fast and flexible framework for agglomerative partitioning. 'partition' uses an approach called Direct-Measure-Reduce to create new variables that maintain the user-specified minimum level of information. Each reduced variable is also interpretable: the original variables map to one and only one variable in the reduced data set. 'partition' is flexible, as well: how variables are selected to reduce, how information loss is measured, and the way data is reduced can all be customized.
Depends: R (>= 3.3.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, rlang, purrr, tibble, dplyr (>= 0.8.0), tidyr, ggplot2 (>= 3.0.0), stringr, magrittr, crayon, pillar, infotheo, MASS, forcats
Suggests: covr, spelling, testthat, knitr, rmarkdown
RoxygenNote: 6.1.1
URL: https://uscbiostats.github.io/partition/, https://github.com/USCbiostats/partition
BugReports: https://github.com/USCbiostats/partition/issues
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-05-16 16:08:33 UTC; malcolmbarrett
Author: Joshua Millstein [aut], Malcolm Barrett [aut, cre] (<https://orcid.org/0000-0003-0299-5825>)
Repository: CRAN
Date/Publication: 2019-05-17 07:00:04 UTC

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New package memoria with initial version 1.0.0
Package: memoria
Type: Package
Title: Quantifying Ecological Memory in Palaeoecological Datasets and Other Long Time-Series
Version: 1.0.0
Author: Blas M. Benito
Maintainer: Blas M. Benito <blasbenito@gmail.com>
Description: Tools to quantify ecological memory in long time-series with Random Forest models (Breiman 2001 <doi:10.1023/A:1010933404324>) fitted with the 'ranger' library (Wright and Ziegler 2017 <doi:10.18637/jss.v077.i01>). Particularly oriented to palaeoecological datasets and simulated pollen curves produced by the 'virtualPollen' package, but also applicable to other long time-series involving a set of environmental drivers and a biotic response.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Depends: R (>= 2.10)
Imports: ggplot2, ranger, cowplot, viridis, viridisLite, zoo, stringr, HH, tidyr
Suggests: devtools, formatR, kableExtra, magrittr, knitr, rmarkdown, rpart, rpart.plot, randomForest, virtualPollen
NeedsCompilation: no
Packaged: 2019-05-16 21:43:51 UTC; blas
Repository: CRAN
Date/Publication: 2019-05-17 08:00:02 UTC

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New package expstudies with initial version 0.0.1
Package: expstudies
Title: Calculate Exposures, Assign Records to Intervals
Version: 0.0.1
Authors@R: person(given = "Matthew", family = "Caseres", email = "matthewcaseres@outlook.com", role = c("aut", "cre"))
Description: Creation of an exposure table with rows for policy-intervals from a table with a unique policy number key and beginning and ending dates for each policy. Methods for assigning supplemental data containing dates and policy numbers to the corresponding interval from the created exposures table.
Depends: R (>= 3.1.0)
Imports: magrittr, dplyr, lubridate, Rcpp
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp
Suggests: pander, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-05-16 21:18:43 UTC; matcaseres
Author: Matthew Caseres [aut, cre]
Maintainer: Matthew Caseres <matthewcaseres@outlook.com>
Repository: CRAN
Date/Publication: 2019-05-17 08:00:08 UTC

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Package EMMAgeo updated to version 0.9.6 with previous version 0.9.4 dated 2016-03-19

Title: End-Member Modelling of Grain-Size Data
Description: End-member modelling analysis of grain-size data is an approach to unmix a data set's underyling distributions and their contribution to the data set. EMMAgeo provides deterministic and robust protocols for that purpose.
Author: Michael Dietze, Elisabeth Dietze
Maintainer: Michael Dietze <mdietze@gfz-potsdam.de>

Diff between EMMAgeo versions 0.9.4 dated 2016-03-19 and 0.9.6 dated 2019-05-17

 EMMAgeo-0.9.4/EMMAgeo/R/Mqs.uncertainty.R        |only
 EMMAgeo-0.9.4/EMMAgeo/R/define.limits.R          |only
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 EMMAgeo-0.9.6/EMMAgeo/DESCRIPTION                |   25 
 EMMAgeo-0.9.6/EMMAgeo/MD5                        |  113 +--
 EMMAgeo-0.9.6/EMMAgeo/NAMESPACE                  |   20 
 EMMAgeo-0.9.6/EMMAgeo/NEWS                       |    8 
 EMMAgeo-0.9.6/EMMAgeo/R/EMMA.R                   |  205 +++---
 EMMAgeo-0.9.6/EMMAgeo/R/EMMAgeo-package.R        |   46 -
 EMMAgeo-0.9.6/EMMAgeo/R/GUI.R                    |   14 
 EMMAgeo-0.9.6/EMMAgeo/R/check.data.R             |   96 --
 EMMAgeo-0.9.6/EMMAgeo/R/click.limits.R           |only
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 EMMAgeo-0.9.6/EMMAgeo/R/robust.EM.R              |  779 ++++++++++++-----------
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 EMMAgeo-0.9.6/EMMAgeo/man/test.robustness.Rd     |   72 +-
 70 files changed, 1730 insertions(+), 1421 deletions(-)

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Package Eagle updated to version 1.5.0 with previous version 1.4.0 dated 2019-04-23

Title: Multiple Locus Association Mapping on a Genome-Wide Scale
Description: An implementation of multiple-locus association mapping on a genome-wide scale. 'Eagle' can handle inbred and outbred study populations, populations of arbitrary unknown complexity, and data larger than the memory capacity of the computer. Since 'Eagle' is based on linear mixed models, it is best suited to the analysis of data on continuous traits. However, it can tolerate non-normal data. 'Eagle' reports, as its findings, the best set of snp in strongest association with a trait. For users unfamiliar with R, to perform an analysis, run 'OpenGUI()'. This opens a web browser to the menu-driven user interface for the input of data, and for performing genome-wide analysis.
Author: Andrew George [aut, cre], Joshua Bowden [ctb], Ryan Stephenson [ctb], Hyun Kang [ctb], Noah Zaitlen [ctb], Claire Wade [ctb], Andrew Kirby [ctb], David Heckerman [ctb], Mark Daly [ctb], Eleazar Eskin [ctb]
Maintainer: Andrew George <andrew.george@csiro.au>

Diff between Eagle versions 1.4.0 dated 2019-04-23 and 1.5.0 dated 2019-05-17

 DESCRIPTION                               |   10 
 MD5                                       |   29 -
 R/AM.R                                    |   20 -
 R/FPR4AM.R                                |    2 
 R/OpenGUI.R                               |    5 
 R/ReadMap.R                               |    6 
 R/ReadPheno.R                             |    4 
 R/check_inputs_mlam.R                     |    6 
 R/find_qtl.R                              |   26 -
 R/form_results.R                          |    8 
 R/onAttach.R                              |    2 
 R/summary_am.R                            |   14 
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 man/OpenGUI.Rd                            |    5 
 man/SummaryAM.Rd                          |    2 
 16 files changed, 566 insertions(+), 113 deletions(-)

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New package bundesbank with initial version 0.1-9
Package: bundesbank
Type: Package
Title: Download Data from Bundesbank
Version: 0.1-9
Date: 2019-05-16
Maintainer: Enrico Schumann <es@enricoschumann.net>
Authors@R: person(given = "Enrico", family = "Schumann", role = c("aut", "cre"), email = "es@enricoschumann.net", comment = c(ORCID = "0000-0001-7601-6576"))
Description: Download data from the time-series databases of the Bundesbank, the German central bank. See the overview at the Bundesbank website (<https://www.bundesbank.de/en/statistics/time-series-databases>) for available series. The package provides only a single function, getSeries(), which supports both traditional and real-time datasets; it will also download meta data if available. Downloaded data can automatically be arranged in various formats, such as data frames or 'zoo' series. The data may optionally be cached, so as to avoid repeated downloads of the same series.
License: GPL-3
URL: http://enricoschumann.net/R/packages/bundesbank/index.htm, https://github.com/enricoschumann/bundesbank
Suggests: zoo
NeedsCompilation: no
Packaged: 2019-05-16 19:05:13 UTC; es19
Author: Enrico Schumann [aut, cre] (<https://orcid.org/0000-0001-7601-6576>)
Repository: CRAN
Date/Publication: 2019-05-17 07:40:07 UTC

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New package bmass with initial version 1.0.3
Encoding: UTF-8
Type: Package
Package: bmass
Version: 1.0.3
Date: 2019-05-15
Title: Bayesian Multivariate Analysis of Summary Statistics
Authors@R: c(person("Michael","Turchin",email = "mturchin20@uchicago.edu", role=c("aut","cre")), person("Matthew","Stephens",email = "mstephens@uchicago.edu", role = "aut"), person("Peter","Carbonetto",role="ctb"))
Description: Multivariate tool for analyzing genome-wide association study results in the form of univariate summary statistics. The goal of 'bmass' is to comprehensively test all possible multivariate models given the phenotypes and datasets provided. Multivariate models are determined by assigning each phenotype to being either Unassociated (U), Directly associated (D) or Indirectly associated (I) with the genetic variant of interest. Test results for each model are presented in the form of Bayes factors, thereby allowing direct comparisons between models. The underlying framework implemented here is based on the modeling developed in "A Unified Framework for Association Analysis with Multiple Related Phenotypes", M. Stephens (2013) <doi:10.1371/journal.pone.0065245>.
License: GPL (>= 3)
URL: https://github.com/mturchin20/bmass
BugReports: https://github.com/mturchin20/bmass/issues
Depends: R (>= 3.3.0)
Imports: utils, stats
Suggests: testthat, knitr, rmarkdown
LazyData: true
NeedsCompilation: no
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Packaged: 2019-05-16 16:23:07 UTC; mturchin20
Author: Michael Turchin [aut, cre], Matthew Stephens [aut], Peter Carbonetto [ctb]
Maintainer: Michael Turchin <mturchin20@uchicago.edu>
Repository: CRAN
Date/Publication: 2019-05-17 07:20:12 UTC

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

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

2019-05-03 0.1.0

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