Fri, 07 Apr 2017

Package netmeta updated to version 0.9-4 with previous version 0.9-3 dated 2017-03-12

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

Diff between netmeta versions 0.9-3 dated 2017-03-12 and 0.9-4 dated 2017-04-07

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New package easyNCDF with initial version 0.0.1
Package: easyNCDF
Title: Tools to Easily Read/Write NetCDF Files into/from Multidimensional R Arrays
Version: 0.0.1
Authors@R: c( person("BSC-CNS", role = c("aut", "cph")), person("Nicolau", "Manubens", , "nicolau.manubens@bsc.es", role = c("aut", "cre")))
Description: Set of wrappers for the 'ncdf4' package to simplify and extend its reading/writing capabilities into/from multidimensional R arrays.
Depends: R (>= 2.14.1)
Imports: ncdf4, abind
License: LGPL-3
URL: https://earth.bsc.es/gitlab/es/easyNCDF/wikis/home
BugReports: https://earth.bsc.es/gitlab/es/easyNCDF/issues
LazyData: true
SystemRequirements: netcdf development libraries
NeedsCompilation: no
Packaged: 2017-04-07 23:07:32 UTC; nmanubens
Author: BSC-CNS [aut, cph], Nicolau Manubens [aut, cre]
Maintainer: Nicolau Manubens <nicolau.manubens@bsc.es>
Repository: CRAN
Date/Publication: 2017-04-07 23:22:53 UTC

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Package validate updated to version 0.1.7 with previous version 0.1.5 dated 2016-06-24

Title: Data Validation Infrastructure
Description: Declare data validation rules and data quality indicators; confront data with them and analyze or visualize the results. The package supports rules that are per-field, in-record, cross-record or cross-dataset. Rules can be automatically analyzed for rule type and connectivity.
Author: Mark van der Loo [cre, aut], Edwin de Jonge [aut], Paul Hsieh [ctb]
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>

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Package sunburstR updated to version 0.6.4 with previous version 0.6.3 dated 2016-10-15

Title: 'Htmlwidget' for 'Kerry Rodden' 'd3.js' Sequence Sunburst
Description: Make interactive 'd3.js' sequence sunburst diagrams in R with the convenience and infrastructure of an 'htmlwidget'.
Author: Mike Bostock [aut, cph] (d3.js library, http://d3js.org), Kerry Rodden [aut, cph] (sequences library in htmlwidgets/lib, https://gist.github.com/kerryrodden/7090426), Kent Russell [aut, cre] (R interface), Florian Breitwieser [ctb] (R interface)
Maintainer: Kent Russell <kent.russell@timelyportfolio.com>

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Package rsoi updated to version 0.2.1 with previous version 0.1.0 dated 2017-04-04

Title: El Nino/Southern Oscillation (ENSO) Index
Description: Downloads Southern Oscillation Index from <https://www.ncdc.noaa.gov/teleconnections/enso/indicators/soi/> and Oceanic Nino Index data from <http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/detrend.nino34.ascii.txt>.
Author: Sam Albers [aut, cre]
Maintainer: Sam Albers <sam.albers@gmail.com>

Diff between rsoi versions 0.1.0 dated 2017-04-04 and 0.2.1 dated 2017-04-07

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Package rosm updated to version 0.2.2 with previous version 0.2.1 dated 2017-04-01

Title: Plot Raster Map Tiles from Open Street Map and Other Sources
Description: Download and plot Open Street Map <http://www.openstreetmap.org/>, Bing Maps <http://www.bing.com/maps> and other tiled map sources in a way that works seamlessly with plotting from the 'sp' package. Use to create high-resolution basemaps and add hillshade to vector-based maps.
Author: Dewey Dunnington [aut, cre], Timothée Giraud [ctb]
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

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New package reghelper with initial version 0.3.3
Package: reghelper
Type: Package
Title: Helper Functions for Regression Analysis
Version: 0.3.3
Date: 2017-04-07
Authors@R: person("Jeffrey", "Hughes", email="jeff.hughes@gmail.com", role=c("aut", "cre"))
Description: A set of functions used to automate commonly used methods in regression analysis. This includes plotting interactions, calculating simple slopes, calculating standardized coefficients, etc. See the reghelper documentation for more information, documentation, and examples.
License: GPL-3
URL:
Depends: R (>= 3.1.0)
LazyData: true
Imports: ggplot2 (>= 1.0.0), stats, nlme, lme4, utils
Suggests: testthat (>= 0.8.1)
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-04-07 21:19:06 UTC; jeffh
Author: Jeffrey Hughes [aut, cre]
Maintainer: Jeffrey Hughes <jeff.hughes@gmail.com>
Repository: CRAN
Date/Publication: 2017-04-07 22:53:04 UTC

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Package prettymapr updated to version 0.2.1 with previous version 0.2 dated 2017-04-01

Title: Scale Bar, North Arrow, and Pretty Margins in R
Description: Automates the process of creating a scale bar and north arrow in any package that uses base graphics to plot in R. Bounding box tools help find and manipulate extents. Finally, there is a function to automate the process of setting margins, plotting the map, scale bar, and north arrow, and resetting graphic parameters upon completion.
Author: Dewey Dunnington <dewey@fishandwhistle.net>
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

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Package IRTShiny updated to version 1.2 with previous version 1.1 dated 2015-09-20

Title: Item Response Theory via Shiny
Description: Interactive shiny application for running Item Response Theory analysis. Provides graphics for characteristic and information curves.
Author: W. Kyle Hamilton <kyle.hamilton@gmail.com>, Atsushi Mizumoto <atsushi@mizumot.com>
Maintainer: W. Kyle Hamilton <kyle.hamilton@gmail.com>

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Package datapack updated to version 1.2.0 with previous version 1.0.1 dated 2016-05-20

Title: A Flexible Container to Transport and Manipulate Data and Associated Resources
Description: Provides a flexible container to transport and manipulate complex sets of data. These data may consist of multiple data files and associated meta data and ancillary files. Individual data objects have associated system level meta data, and data files are linked together using the OAI-ORE standard resource map which describes the relationships between the files. The OAI-ORE standard is described at <https://www.openarchives.org/ore>. Data packages can be serialized and transported as structured files that have been created following the BagIt specification. The BagIt specification is described at <https://tools.ietf.org/html/draft-kunze-bagit-08>.
Author: Matthew B. Jones [aut, cre], Peter Slaughter [aut], Regents of the University of California [cph]
Maintainer: Matthew B. Jones <jones@nceas.ucsb.edu>

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Package Boom updated to version 0.6 with previous version 0.5 dated 2016-08-18

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.
Maintainer: Steve Scott <stevescott@google.com>

Diff between Boom versions 0.5 dated 2016-08-18 and 0.6 dated 2017-04-07

 Boom-0.5/Boom/inst/include/Models/CompositeVectorModel.hpp                                                |only
 Boom-0.5/Boom/inst/include/Models/ProductModel.hpp                                                        |only
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 Boom-0.5/Boom/inst/include/distributions/ks.hpp                                                           |only
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 Boom-0.6/Boom/DESCRIPTION                                                                                 |    8 
 Boom-0.6/Boom/MD5                                                                                         |  721 ++--
 Boom-0.6/Boom/NAMESPACE                                                                                   |    8 
 Boom-0.6/Boom/R/compare.vector.distribution.R                                                             |    5 
 Boom-0.6/Boom/R/dirichlet.R                                                                               |only
 Boom-0.6/Boom/R/dmvn.R                                                                                    |only
 Boom-0.6/Boom/R/format.R                                                                                  |only
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 Boom-0.6/Boom/R/lmgamma.R                                                                                 |only
 Boom-0.6/Boom/R/mscan.R                                                                                   |only
 Boom-0.6/Boom/R/plot.many.ts.R                                                                            |   15 
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 Boom-0.6/Boom/R/rmvn.R                                                                                    |only
 Boom-0.6/Boom/R/suggest_burn_log_likelihood.R                                                             |   13 
 Boom-0.6/Boom/R/thin.matrix.R                                                                             |only
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 Boom-0.6/Boom/inst/include/LinAlg/Matrix.hpp                                                              |    7 
 Boom-0.6/Boom/inst/include/LinAlg/SpdMatrix.hpp                                                           |   12 
 Boom-0.6/Boom/inst/include/LinAlg/Vector.hpp                                                              |   14 
 Boom-0.6/Boom/inst/include/LinAlg/VectorView.hpp                                                          |    2 
 Boom-0.6/Boom/inst/include/Models/Bart/Bart.hpp                                                           |   10 
 Boom-0.6/Boom/inst/include/Models/Bart/PosteriorSamplers/BartPosteriorSampler.hpp                         |    4 
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 Boom-0.6/Boom/inst/include/Models/Bart/PosteriorSamplers/ProbitBartPosteriorSampler.hpp                   |    4 
 Boom-0.6/Boom/inst/include/Models/BetaModel.hpp                                                           |   26 
 Boom-0.6/Boom/inst/include/Models/DataTypes.hpp                                                           |   16 
 Boom-0.6/Boom/inst/include/Models/DirichletModel.hpp                                                      |    3 
 Boom-0.6/Boom/inst/include/Models/DoubleModel.hpp                                                         |   52 
 Boom-0.6/Boom/inst/include/Models/ExponentialModel.hpp                                                    |   29 
 Boom-0.6/Boom/inst/include/Models/FiniteMixtureModel.hpp                                                  |   32 
 Boom-0.6/Boom/inst/include/Models/GammaModel.hpp                                                          |   75 
 Boom-0.6/Boom/inst/include/Models/GaussianModelBase.hpp                                                   |    4 
 Boom-0.6/Boom/inst/include/Models/Glm/AggregatedRegressionModel.hpp                                       |    5 
 Boom-0.6/Boom/inst/include/Models/Glm/BinomialLogitModel.hpp                                              |   29 
 Boom-0.6/Boom/inst/include/Models/Glm/BinomialProbitModel.hpp                                             |    2 
 Boom-0.6/Boom/inst/include/Models/Glm/LogisticRegressionModel.hpp                                         |   31 
 Boom-0.6/Boom/inst/include/Models/Glm/MultinomialLogitModel.hpp                                           |    6 
 Boom-0.6/Boom/inst/include/Models/Glm/MvReg2.hpp                                                          |    1 
 Boom-0.6/Boom/inst/include/Models/Glm/MvnGivenXandSigma.hpp                                               |  123 
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 Boom-0.6/Boom/inst/include/Models/Glm/PoissonRegressionData.hpp                                           |    4 
 Boom-0.6/Boom/inst/include/Models/Glm/PoissonRegressionModel.hpp                                          |   12 
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 Boom-0.6/Boom/inst/include/Models/Glm/RegressionModel.hpp                                                 |   15 
 Boom-0.6/Boom/inst/include/Models/Glm/TRegression.hpp                                                     |    4 
 Boom-0.6/Boom/inst/include/Models/Glm/VariableSelectionPrior.hpp                                          |    4 
 Boom-0.6/Boom/inst/include/Models/Glm/WeightedRegressionModel.hpp                                         |   26 
 Boom-0.6/Boom/inst/include/Models/Glm/ZeroInflatedPoissonRegression.hpp                                   |   26 
 Boom-0.6/Boom/inst/include/Models/HMM/PosteriorSamplers/HmmPosteriorSampler.hpp                           |    2 
 Boom-0.6/Boom/inst/include/Models/IRT/DafePcrRwm.hpp                                                      |   31 
 Boom-0.6/Boom/inst/include/Models/IRT/Item.hpp                                                            |   11 
 Boom-0.6/Boom/inst/include/Models/IRT/PartialCreditModel.hpp                                              |    4 
 Boom-0.6/Boom/inst/include/Models/IRT/SubjectSliceSampler.hpp                                             |    9 
 Boom-0.6/Boom/inst/include/Models/LognormalModel.hpp                                                      |    7 
 Boom-0.6/Boom/inst/include/Models/Mixtures/DirichletProcessMvnModel.hpp                                   |    9 
 Boom-0.6/Boom/inst/include/Models/Mixtures/PosteriorSamplers/DirichletProcessMvnCollapsedGibbsSampler.hpp |   49 
 Boom-0.6/Boom/inst/include/Models/ModelTypes.hpp                                                          |   57 
 Boom-0.6/Boom/inst/include/Models/MultinomialModel.hpp                                                    |    3 
 Boom-0.6/Boom/inst/include/Models/MvnBase.hpp                                                             |   76 
 Boom-0.6/Boom/inst/include/Models/MvnGivenSigma.hpp                                                       |   19 
 Boom-0.6/Boom/inst/include/Models/MvnModel.hpp                                                            |    3 
 Boom-0.6/Boom/inst/include/Models/MvtModel.hpp                                                            |   49 
 Boom-0.6/Boom/inst/include/Models/Nonparametric/BayesRules.hpp                                            |    1 
 Boom-0.6/Boom/inst/include/Models/ParamTypes.hpp                                                          |   13 
 Boom-0.6/Boom/inst/include/Models/PointProcess/BoundedPoissonProcessSimulator.hpp                         |    3 
 Boom-0.6/Boom/inst/include/Models/PointProcess/CosinePoissonProcess.hpp                                   |    4 
 Boom-0.6/Boom/inst/include/Models/PointProcess/HomogeneousPoissonProcess.hpp                              |    4 
 Boom-0.6/Boom/inst/include/Models/PointProcess/MarkovModulatedPoissonProcess.hpp                          |    4 
 Boom-0.6/Boom/inst/include/Models/PointProcess/PoissonClusterProcess.hpp                                  |   11 
 Boom-0.6/Boom/inst/include/Models/PointProcess/PoissonProcess.hpp                                         |    3 
 Boom-0.6/Boom/inst/include/Models/PointProcess/WeeklyCyclePoissonProcess.hpp                              |   10 
 Boom-0.6/Boom/inst/include/Models/Policies/CompositeParamPolicy.hpp                                       |   11 
 Boom-0.6/Boom/inst/include/Models/Policies/ManyParamPolicy.hpp                                            |    4 
 Boom-0.6/Boom/inst/include/Models/Policies/NonparametricParamPolicy.hpp                                   |    8 
 Boom-0.6/Boom/inst/include/Models/Policies/NullParamPolicy.hpp                                            |   11 
 Boom-0.6/Boom/inst/include/Models/Policies/ParamPolicy_1.hpp                                              |    8 
 Boom-0.6/Boom/inst/include/Models/Policies/ParamPolicy_2.hpp                                              |    4 
 Boom-0.6/Boom/inst/include/Models/Policies/ParamPolicy_3.hpp                                              |    4 
 Boom-0.6/Boom/inst/include/Models/Policies/ParamPolicy_4.hpp                                              |    4 
 Boom-0.6/Boom/inst/include/Models/PosteriorSamplers/GenericGaussianVarianceSampler.hpp                    |    3 
 Boom-0.6/Boom/inst/include/Models/PosteriorSamplers/Imputer.hpp                                           |  547 ++-
 Boom-0.6/Boom/inst/include/Models/PosteriorSamplers/PoissonGammaPosteriorSampler.hpp                      |    3 
 Boom-0.6/Boom/inst/include/Models/PosteriorSamplers/PosteriorSampler.hpp                                  |   41 
 Boom-0.6/Boom/inst/include/Models/PosteriorSamplers/ZeroMeanGaussianConjSampler.hpp                       |   29 
 Boom-0.6/Boom/inst/include/Models/ProductVectorModel.hpp                                                  |only
 Boom-0.6/Boom/inst/include/Models/ScaledChisqModel.hpp                                                    |    4 
 Boom-0.6/Boom/inst/include/Models/SpdData.hpp                                                             |  106 
 Boom-0.6/Boom/inst/include/Models/StateSpace/AggregatedStateSpaceRegression.hpp                           |    7 
 Boom-0.6/Boom/inst/include/Models/StateSpace/Filters/ScalarKalmanStorage.hpp                              |    5 
 Boom-0.6/Boom/inst/include/Models/StateSpace/Filters/SparseMatrix.hpp                                     |  240 +
 Boom-0.6/Boom/inst/include/Models/StateSpace/PosteriorSamplers/StateSpacePosteriorSampler.hpp             |   44 
 Boom-0.6/Boom/inst/include/Models/StateSpace/PosteriorSamplers/StateSpaceStudentPosteriorSampler.hpp      |    8 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateModels/ArStateModel.hpp                                 |   10 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateModels/DynamicRegressionStateModel.hpp                  |    6 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateModels/LocalLevelStateModel.hpp                         |    8 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateModels/LocalLinearTrend.hpp                             |    8 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateModels/RandomWalkHolidayStateModel.hpp                  |    8 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateModels/SeasonalStateModel.hpp                           |   17 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateModels/SemilocalLinearTrend.hpp                         |only
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateModels/StateModel.hpp                                   |   21 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateModels/StudentLocalLinearTrend.hpp                      |    2 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateModels/TrigStateModel.hpp                               |   14 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateSpaceLogitModel.hpp                                     |  131 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateSpaceModel.hpp                                          |   61 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateSpaceModelBase.hpp                                      |  621 +++-
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateSpaceNormalMixture.hpp                                  |    2 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateSpacePoissonModel.hpp                                   |  107 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateSpaceRegressionModel.hpp                                |   44 
 Boom-0.6/Boom/inst/include/Models/StateSpace/StateSpaceStudentRegressionModel.hpp                         |   70 
 Boom-0.6/Boom/inst/include/Models/Sufstat.hpp                                                             |    1 
 Boom-0.6/Boom/inst/include/Models/TruncatedGammaModel.hpp                                                 |   32 
 Boom-0.6/Boom/inst/include/Models/UniformModel.hpp                                                        |    6 
 Boom-0.6/Boom/inst/include/Models/VectorModel.hpp                                                         |   81 
 Boom-0.6/Boom/inst/include/Models/WishartModel.hpp                                                        |   10 
 Boom-0.6/Boom/inst/include/Models/ZeroInflatedGammaModel.hpp                                              |   35 
 Boom-0.6/Boom/inst/include/Models/ZeroInflatedLognormalModel.hpp                                          |   16 
 Boom-0.6/Boom/inst/include/Models/ZeroInflatedPoissonModel.hpp                                            |    2 
 Boom-0.6/Boom/inst/include/Models/ZeroMeanGaussianModel.hpp                                               |    3 
 Boom-0.6/Boom/inst/include/Samplers/MetropolisHastings.hpp                                                |    6 
 Boom-0.6/Boom/inst/include/Samplers/MoveAccounting.hpp                                                    |   28 
 Boom-0.6/Boom/inst/include/Samplers/ScalarSliceSampler.hpp                                                |    4 
 Boom-0.6/Boom/inst/include/Samplers/SliceSampler.hpp                                                      |    4 
 Boom-0.6/Boom/inst/include/Samplers/TIM.hpp                                                               |    3 
 Boom-0.6/Boom/inst/include/Samplers/UnivariateSliceSampler.hpp                                            |   18 
 Boom-0.6/Boom/inst/include/TargetFun/LogPost.hpp                                                          |    5 
 Boom-0.6/Boom/inst/include/TargetFun/TargetFun.hpp                                                        |   15 
 Boom-0.6/Boom/inst/include/cpputil/ParamFileIoManager.hpp                                                 |    6 
 Boom-0.6/Boom/inst/include/cpputil/ProgramOptions.hpp                                                     |    7 
 Boom-0.6/Boom/inst/include/cpputil/Ptr.hpp                                                                |   14 
 Boom-0.6/Boom/inst/include/cpputil/RefCounted.hpp                                                         |   59 
 Boom-0.6/Boom/inst/include/cpputil/ThreadTools.hpp                                                        |only
 Boom-0.6/Boom/inst/include/cpputil/stream.hpp                                                             |    2 
 Boom-0.6/Boom/inst/include/cpputil/string_utils.hpp                                                       |   18 
 Boom-0.6/Boom/inst/include/distributions.hpp                                                              |   43 
 Boom-0.6/Boom/inst/include/distributions/BoundedAdaptiveRejectionSampler.hpp                              |    4 
 Boom-0.6/Boom/inst/include/distributions/DoublyBoundedAdaptiveRejectionSampler.hpp                        |    4 
 Boom-0.6/Boom/inst/include/distributions/inverse_gaussian.hpp                                             |   19 
 Boom-0.6/Boom/inst/include/numopt.hpp                                                                     |  279 +
 Boom-0.6/Boom/inst/include/numopt/Integral.hpp                                                            |    4 
 Boom-0.6/Boom/inst/include/numopt/NelderMead.hpp                                                          |    3 
 Boom-0.6/Boom/inst/include/r_interface/boom_r_tools.hpp                                                   |   55 
 Boom-0.6/Boom/inst/include/r_interface/create_state_model.hpp                                             |   11 
 Boom-0.6/Boom/inst/include/r_interface/list_io.hpp                                                        |   55 
 Boom-0.6/Boom/inst/include/r_interface/prior_specification.hpp                                            |   70 
 Boom-0.6/Boom/inst/include/stats/Bspline.hpp                                                              |   41 
 Boom-0.6/Boom/inst/include/stats/DataTable.hpp                                                            |    4 
 Boom-0.6/Boom/inst/include/stats/Mspline.hpp                                                              |only
 Boom-0.6/Boom/inst/include/stats/Spline.hpp                                                               |   93 
 Boom-0.6/Boom/inst/include/stats/ks_critical_value.hpp                                                    |only
 Boom-0.6/Boom/man/ToString.Rd                                                                             |only
 Boom-0.6/Boom/man/beta.prior.Rd                                                                           |    6 
 Boom-0.6/Boom/man/compare.vector.distributions.Rd                                                         |    4 
 Boom-0.6/Boom/man/dirichlet-distribution.Rd                                                               |only
 Boom-0.6/Boom/man/dmvn.Rd                                                                                 |only
 Boom-0.6/Boom/man/double.model.Rd                                                                         |   12 
 Boom-0.6/Boom/man/gamma.prior.Rd                                                                          |   18 
 Boom-0.6/Boom/man/inverse-wishart.Rd                                                                      |only
 Boom-0.6/Boom/man/lmgamma.Rd                                                                              |only
 Boom-0.6/Boom/man/mscan.Rd                                                                                |only
 Boom-0.6/Boom/man/plot.many.ts.Rd                                                                         |   94 
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 Boom-0.6/Boom/man/rmvn.Rd                                                                                 |only
 Boom-0.6/Boom/man/suggest.burn.log.likelihood.Rd                                                          |   10 
 Boom-0.6/Boom/man/thin.matrix.Rd                                                                          |only
 Boom-0.6/Boom/man/traceproduct.Rd                                                                         |only
 Boom-0.6/Boom/man/wishart.Rd                                                                              |only
 Boom-0.6/Boom/src/Bmath/d1mach.cpp                                                                        |    4 
 Boom-0.6/Boom/src/Bmath/fprec.cpp                                                                         |    2 
 Boom-0.6/Boom/src/Bmath/fround.cpp                                                                        |    2 
 Boom-0.6/Boom/src/Bmath/gamma_cody.cpp                                                                    |    4 
 Boom-0.6/Boom/src/Bmath/i1mach.cpp                                                                        |    4 
 Boom-0.6/Boom/src/Bmath/mlutils.cpp                                                                       |   13 
 Boom-0.6/Boom/src/Bmath/pf.cpp                                                                            |    2 
 Boom-0.6/Boom/src/Bmath/pgamma.cpp                                                                        |    7 
 Boom-0.6/Boom/src/Bmath/pnorm.cpp                                                                         |    5 
 Boom-0.6/Boom/src/Bmath/pnt.cpp                                                                           |   16 
 Boom-0.6/Boom/src/Bmath/polygamma.cpp                                                                     |    8 
 Boom-0.6/Boom/src/Bmath/qbinom.cpp                                                                        |    4 
 Boom-0.6/Boom/src/Bmath/qf.cpp                                                                            |    2 
 Boom-0.6/Boom/src/Bmath/qgamma.cpp                                                                        |    2 
 Boom-0.6/Boom/src/Bmath/qhyper.cpp                                                                        |    2 
 Boom-0.6/Boom/src/Bmath/qnbinom.cpp                                                                       |    5 
 Boom-0.6/Boom/src/Bmath/qpois.cpp                                                                         |    5 
 Boom-0.6/Boom/src/Bmath/rbeta.cpp                                                                         |    4 
 Boom-0.6/Boom/src/Bmath/rgamma.cpp                                                                        |   24 
 Boom-0.6/Boom/src/Bmath/rloggamma_small_alpha.cpp                                                         |only
 Boom-0.6/Boom/src/Bmath/snorm.cpp                                                                         |    3 
 Boom-0.6/Boom/src/Interfaces/R/BoomInterface/test/dirichlet_test.R                                        |only
 Boom-0.6/Boom/src/Interfaces/R/BoomInterface/test/dmvn_test.R                                             |only
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 Boom-0.6/Boom/src/Interfaces/R/BoomInterface/test/mvn_test.R                                              |only
 Boom-0.6/Boom/src/Interfaces/R/BoomInterface/test/wishart_test.R                                          |only
 Boom-0.6/Boom/src/LinAlg/Array.cpp                                                                        |   76 
 Boom-0.6/Boom/src/LinAlg/Matrix.cpp                                                                       |    5 
 Boom-0.6/Boom/src/LinAlg/SpdMatrix.cpp                                                                    | 1470 +++++-----
 Boom-0.6/Boom/src/LinAlg/Vector.cpp                                                                       |   20 
 Boom-0.6/Boom/src/LinAlg/VectorView.cpp                                                                   |    2 
 Boom-0.6/Boom/src/Makevars                                                                                |    3 
 Boom-0.6/Boom/src/Models/Bart/Bart.cpp                                                                    |    4 
 Boom-0.6/Boom/src/Models/Bart/PosteriorSamplers/BartPosteriorSampler.cpp                                  |    4 
 Boom-0.6/Boom/src/Models/Bart/PosteriorSamplers/GaussianBartPosteriorSampler.cpp                          |    4 
 Boom-0.6/Boom/src/Models/Bart/PosteriorSamplers/LogitBartPosteriorSampler.cpp                             |    4 
 Boom-0.6/Boom/src/Models/Bart/PosteriorSamplers/PoissonBartPosteriorSampler.cpp                           |    4 
 Boom-0.6/Boom/src/Models/Bart/PosteriorSamplers/ProbitBartPosteriorSampler.cpp                            |    4 
 Boom-0.6/Boom/src/Models/BetaModel.cpp                                                                    |  147 -
 Boom-0.6/Boom/src/Models/CategoricalData.cpp                                                              |  265 -
 Boom-0.6/Boom/src/Models/ConstrainedVectorParams.cpp                                                      |    2 
 Boom-0.6/Boom/src/Models/FiniteMixtureModel.cpp                                                           |  111 
 Boom-0.6/Boom/src/Models/GammaModel.cpp                                                                   |  270 -
 Boom-0.6/Boom/src/Models/Glm/GlmCoefs.cpp                                                                 |    1 
 Boom-0.6/Boom/src/Models/Glm/MultinomialLogitModel.cpp                                                    |    6 
 Boom-0.6/Boom/src/Models/Glm/MvReg2.cpp                                                                   |    1 
 Boom-0.6/Boom/src/Models/Glm/MvnGivenXandSigma.cpp                                                        |  153 -
 Boom-0.6/Boom/src/Models/Glm/OrdinalCutpointModel.cpp                                                     |    6 
 Boom-0.6/Boom/src/Models/Glm/PoissonRegressionData.cpp                                                    |    4 
 Boom-0.6/Boom/src/Models/Glm/PoissonRegressionModel.cpp                                                   |   10 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/BinomialLogitAuxmixSampler.cpp                             |  185 -
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/BinomialLogitSamplerTim.cpp                                |   14 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/BregVsSampler.cpp                                          |    2 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/CumulativeLogitSampler.cpp                                 |    4 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/CumulativeProbitSampler.cpp                                |    4 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/DAFE_MLM.cpp                                               |    9 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/MLVS.cpp                                                   |   30 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/MLVS_data_imputer.cpp                                      |   17 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/MultinomialLogitCompleteDataSuf.cpp                        |    8 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/NonconjugateRegressionSampler.cpp                          |only
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/NormalMixtureApproximation.cpp                             |  133 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/PoissonDataImputer.cpp                                     |   10 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/PoissonRegressionAuxMixSampler.cpp                         |   60 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/PoissonRegressionSpikeSlabSampler.cpp                      |   22 
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 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/RegressionConjSampler.cpp                                  |    2 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/SpikeSlabDaRegressionSampler.cpp                           |   14 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/TRegressionSampler.cpp                                     |    2 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/ZeroInflatedPoissonRegressionSampler.cpp                   |   12 
 Boom-0.6/Boom/src/Models/Glm/PosteriorSamplers/poisson_mixture_approximation_table.cpp                    |    2 
 Boom-0.6/Boom/src/Models/Glm/ProbitRegression.cpp                                                         |   11 
 Boom-0.6/Boom/src/Models/Glm/QuantileRegressionModel.cpp                                                  |only
 Boom-0.6/Boom/src/Models/Glm/RegressionModel.cpp                                                          |   39 
 Boom-0.6/Boom/src/Models/Glm/TRegression.cpp                                                              |    4 
 Boom-0.6/Boom/src/Models/Glm/VariableSelectionPrior.cpp                                                   |   22 
 Boom-0.6/Boom/src/Models/Glm/ZeroInflatedPoissonRegression.cpp                                            |   18 
 Boom-0.6/Boom/src/Models/HMM/Clickstream/NestedHmm.cpp                                                    |    2 
 Boom-0.6/Boom/src/Models/HMM/HmmFilter.cpp                                                                |   32 
 Boom-0.6/Boom/src/Models/HMM/PosteriorSamplers/HmmPosteriorSampler.cpp                                    |    2 
 Boom-0.6/Boom/src/Models/Hierarchical/HierarchicalGammaModel.cpp                                          |    4 
 Boom-0.6/Boom/src/Models/Hierarchical/PosteriorSamplers/HierarchicalPoissonSampler.cpp                    |    9 
 Boom-0.6/Boom/src/Models/IRT/DafePcrDataImputer.cpp                                                       |   31 
 Boom-0.6/Boom/src/Models/IRT/DafePcrItemSampler.cpp                                                       |   21 
 Boom-0.6/Boom/src/Models/IRT/DafePcrRwmItemSampler.cpp                                                    |    9 
 Boom-0.6/Boom/src/Models/IRT/DafePcrRwmSubject.cpp                                                        |   23 
 Boom-0.6/Boom/src/Models/IRT/DafePcrSubject.cpp                                                           |   16 
 Boom-0.6/Boom/src/Models/IRT/IrtModel.cpp                                                                 |    5 
 Boom-0.6/Boom/src/Models/IRT/Item.cpp                                                                     |   38 
 Boom-0.6/Boom/src/Models/IRT/PartialCreditModel.cpp                                                       |   28 
 Boom-0.6/Boom/src/Models/IRT/Subject.cpp                                                                  |    2 
 Boom-0.6/Boom/src/Models/MarkovModel.cpp                                                                  |   52 
 Boom-0.6/Boom/src/Models/Mixtures/DirichletProcessMvnModel.cpp                                            |   39 
 Boom-0.6/Boom/src/Models/Mixtures/PosteriorSamplers/DirichletProcessMvnCollapsedGibbsSampler.cpp          |  147 -
 Boom-0.6/Boom/src/Models/ModelTypes.cpp                                                                   |   49 
 Boom-0.6/Boom/src/Models/MultinomialModel.cpp                                                             |    4 
 Boom-0.6/Boom/src/Models/MvnBase.cpp                                                                      |   81 
 Boom-0.6/Boom/src/Models/MvnGivenSigma.cpp                                                                |  117 
 Boom-0.6/Boom/src/Models/MvnModel.cpp                                                                     |    2 
 Boom-0.6/Boom/src/Models/MvtModel.cpp                                                                     |  153 -
 Boom-0.6/Boom/src/Models/PointProcess/BoundedPoissonProcessSimulator.cpp                                  |    2 
 Boom-0.6/Boom/src/Models/PointProcess/CosinePoissonProcess.cpp                                            |    2 
 Boom-0.6/Boom/src/Models/PointProcess/HomogeneousPoissonProcess.cpp                                       |    2 
 Boom-0.6/Boom/src/Models/PointProcess/PointProcess.cpp                                                    |    2 
 Boom-0.6/Boom/src/Models/PointProcess/PoissonClusterProcess.cpp                                           |    9 
 Boom-0.6/Boom/src/Models/PointProcess/WeeklyCyclePoissonProcess.cpp                                       |    5 
 Boom-0.6/Boom/src/Models/Policies/CompositeParamPolicy.cpp                                                |   11 
 Boom-0.6/Boom/src/Models/Policies/ManyParamPolicy.cpp                                                     |    4 
 Boom-0.6/Boom/src/Models/Policies/NullParamPolicy.cpp                                                     |    4 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/BetaBinomialPosteriorSampler.cpp                               |   11 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/BetaBinomialSampler.cpp                                        |    8 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/BetaPosteriorSampler.cpp                                       |    5 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/DirichletPosteriorSampler.cpp                                  |    6 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/GammaPosteriorSampler.cpp                                      |   20 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/GaussianConjSampler.cpp                                        |    5 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/GaussianVarSampler.cpp                                         |    2 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/GenericGaussianVarianceSampler.cpp                             |    7 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/IndependentMvnConjSampler.cpp                                  |    2 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/IndependentMvnVarSampler.cpp                                   |    2 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/MvnIndependentVarianceSampler.cpp                              |    2 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/PoissonGammaPosteriorSampler.cpp                               |   20 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/PoissonGammaSampler.cpp                                        |   15 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/PosteriorSampler.cpp                                           |   15 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/SharedSigsqSampler.cpp                                         |    3 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/ZeroMeanGaussianConjSampler.cpp                                |   55 
 Boom-0.6/Boom/src/Models/PosteriorSamplers/ZeroMeanMvnIndependenceSampler.cpp                             |    4 
 Boom-0.6/Boom/src/Models/ProductVectorModel.cpp                                                           |only
 Boom-0.6/Boom/src/Models/SpdData.cpp                                                                      |  312 +-
 Boom-0.6/Boom/src/Models/StateSpace/AggregatedStateSpaceRegression.cpp                                    |    9 
 Boom-0.6/Boom/src/Models/StateSpace/Filters/SparseMatrix.cpp                                              |    8 
 Boom-0.6/Boom/src/Models/StateSpace/PosteriorSamplers/DynamicRegressionPosteriorSampler.cpp               |    2 
 Boom-0.6/Boom/src/Models/StateSpace/PosteriorSamplers/StateSpaceLogitPosteriorSampler.cpp                 |   43 
 Boom-0.6/Boom/src/Models/StateSpace/PosteriorSamplers/StateSpacePoissonPosteriorSampler.cpp               |   87 
 Boom-0.6/Boom/src/Models/StateSpace/PosteriorSamplers/StateSpacePosteriorSampler.cpp                      |  140 
 Boom-0.6/Boom/src/Models/StateSpace/PosteriorSamplers/StateSpaceStudentPosteriorSampler.cpp               |   63 
 Boom-0.6/Boom/src/Models/StateSpace/PosteriorSamplers/StudentLocalLinearTrendPosteriorSampler.cpp         |   83 
 Boom-0.6/Boom/src/Models/StateSpace/StateModels/ArStateModel.cpp                                          |   34 
 Boom-0.6/Boom/src/Models/StateSpace/StateModels/DynamicRegressionStateModel.cpp                           |   22 
 Boom-0.6/Boom/src/Models/StateSpace/StateModels/LocalLevelStateModel.cpp                                  |   26 
 Boom-0.6/Boom/src/Models/StateSpace/StateModels/LocalLinearTrend.cpp                                      |   34 
 Boom-0.6/Boom/src/Models/StateSpace/StateModels/RandomWalkHolidayStateModel.cpp                           |   10 
 Boom-0.6/Boom/src/Models/StateSpace/StateModels/SeasonalStateModel.cpp                                    |   32 
 Boom-0.6/Boom/src/Models/StateSpace/StateModels/SemilocalLinearTrend.cpp                                  |only
 Boom-0.6/Boom/src/Models/StateSpace/StateModels/StateModel.cpp                                            |    9 
 Boom-0.6/Boom/src/Models/StateSpace/StateModels/StudentLocalLinearTrend.cpp                               |    8 
 Boom-0.6/Boom/src/Models/StateSpace/StateModels/TrigStateModel.cpp                                        |    6 
 Boom-0.6/Boom/src/Models/StateSpace/StateSpaceLogitModel.cpp                                              |   97 
 Boom-0.6/Boom/src/Models/StateSpace/StateSpaceModel.cpp                                                   |  110 
 Boom-0.6/Boom/src/Models/StateSpace/StateSpaceModelBase.cpp                                               |  559 +++
 Boom-0.6/Boom/src/Models/StateSpace/StateSpacePoissonModel.cpp                                            |   98 
 Boom-0.6/Boom/src/Models/StateSpace/StateSpaceRegressionModel.cpp                                         |  130 
 Boom-0.6/Boom/src/Models/StateSpace/StateSpaceStudentRegressionModel.cpp                                  |   93 
 Boom-0.6/Boom/src/Models/Sufstat.cpp                                                                      |    7 
 Boom-0.6/Boom/src/Models/TimeSeries/ArModel.cpp                                                           |   10 
 Boom-0.6/Boom/src/Models/TimeSeries/PosteriorSamplers/ArPosteriorSampler.cpp                              |    2 
 Boom-0.6/Boom/src/Models/TimeSeries/PosteriorSamplers/ArSpikeSlabSampler.cpp                              |    2 
 Boom-0.6/Boom/src/Models/TimeSeries/PosteriorSamplers/NonzeroMeanAr1Sampler.cpp                           |    2 
 Boom-0.6/Boom/src/Models/TruncatedGammaModel.cpp                                                          |   58 
 Boom-0.6/Boom/src/Models/UniformCorrelationModel.cpp                                                      |    1 
 Boom-0.6/Boom/src/Models/UniformModel.cpp                                                                 |  115 
 Boom-0.6/Boom/src/Models/WishartModel.cpp                                                                 |  110 
 Boom-0.6/Boom/src/Models/ZeroInflatedGammaModel.cpp                                                       |   99 
 Boom-0.6/Boom/src/Models/ZeroInflatedLognormalModel.cpp                                                   |   99 
 Boom-0.6/Boom/src/Models/ZeroInflatedPoissonModel.cpp                                                     |   84 
 Boom-0.6/Boom/src/Models/ZeroMeanGaussianModel.cpp                                                        |    9 
 Boom-0.6/Boom/src/Samplers/MetropolisHastings.cpp                                                         |    5 
 Boom-0.6/Boom/src/Samplers/MoveAccounting.cpp                                                             |   20 
 Boom-0.6/Boom/src/Samplers/SliceSampler.cpp                                                               |   19 
 Boom-0.6/Boom/src/Samplers/TIM.cpp                                                                        |   19 
 Boom-0.6/Boom/src/Samplers/UnivariateSliceSampler.cpp                                                     |   49 
 Boom-0.6/Boom/src/TargetFun/TargetFun.cpp                                                                 |    5 
 Boom-0.6/Boom/src/boom_r_tools.cpp                                                                        |  184 -
 Boom-0.6/Boom/src/cpputil/ThreadTools.cpp                                                                 |only
 Boom-0.6/Boom/src/cpputil/cat_string.cpp                                                                  |   14 
 Boom-0.6/Boom/src/cpputil/parse_range.cpp                                                                 |    2 
 Boom-0.6/Boom/src/cpputil/split.cpp                                                                       |    2 
 Boom-0.6/Boom/src/cpputil/strip.cpp                                                                       |    2 
 Boom-0.6/Boom/src/create_mixture_component.cpp                                                            |   11 
 Boom-0.6/Boom/src/create_state_model.cpp                                                                  |   98 
 Boom-0.6/Boom/src/distributions/mvn.cpp                                                                   |  103 
 Boom-0.6/Boom/src/extract_mixture_data.cpp                                                                |    8 
 Boom-0.6/Boom/src/list_io.cpp                                                                             |  144 
 Boom-0.6/Boom/src/math/lmultigamma.cpp                                                                    |only
 Boom-0.6/Boom/src/math/special_functions.hpp                                                              |   37 
 Boom-0.6/Boom/src/numopt/Brent.cpp                                                                        |   33 
 Boom-0.6/Boom/src/numopt/Integral.cpp                                                                     |    6 
 Boom-0.6/Boom/src/numopt/NelderMead.cpp                                                                   |  210 -
 Boom-0.6/Boom/src/numopt/bfgs.cpp                                                                         |    7 
 Boom-0.6/Boom/src/numopt/conj_grad.cpp                                                                    |   85 
 Boom-0.6/Boom/src/numopt/max_nd.cpp                                                                       |  110 
 Boom-0.6/Boom/src/numopt/nelder_mead.cpp                                                                  |   43 
 Boom-0.6/Boom/src/prior_specification.cpp                                                                 |  128 
 Boom-0.6/Boom/src/spike_slab_prior.cpp                                                                    |    7 
 Boom-0.6/Boom/src/stats/Bspline.cpp                                                                       |   65 
 Boom-0.6/Boom/src/stats/DataTable.cpp                                                                     |    6 
 Boom-0.6/Boom/src/stats/ECDF.cpp                                                                          |   22 
 Boom-0.6/Boom/src/stats/IQagent.cpp                                                                       |   31 
 Boom-0.6/Boom/src/stats/Mspline.cpp                                                                       |only
 Boom-0.6/Boom/src/stats/Spline.cpp                                                                        |  143 
 Boom-0.6/Boom/src/stats/moments.cpp                                                                       |    6 
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New package micEconIndex with initial version 0.1-6
Package: micEconIndex
Version: 0.1-6
Date: 2017-04-07
Title: Price and Quantity Indices
Author: Arne Henningsen
Maintainer: Arne Henningsen <arne.henningsen@gmail.com>
Depends: R (>= 2.4.0)
Imports: miscTools (>= 0.6-1)
Suggests: Ecdat (>= 0.1-5), micEcon (>= 0.6-12)
Description: Tools for calculating Laspeyres, Paasche, and Fisher price and quantity indices.
License: GPL (>= 2)
URL: http://www.micEcon.org
NeedsCompilation: no
Packaged: 2017-04-07 17:18:24 UTC; arne
Repository: CRAN
Date/Publication: 2017-04-07 18:20:38 UTC

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Package stpm updated to version 1.6.6 with previous version 1.6.4 dated 2017-03-05

Title: Stochastic Process Model for Analysis of Longitudinal and Time-to-Event Outcomes
Description: Utilities to estimate parameters of the models with survival functions induced by stochastic covariates. Miscellaneous functions for data preparation and simulation are also provided. For more information, see: (i)"Stochastic model for analysis of longitudinal data on aging and mortality" by Yashin A. et al. (2007), Mathematical Biosciences, 208(2), 538-551, <DOI:10.1016/j.mbs.2006.11.006>; (ii) "Health decline, aging and mortality: how are they related?" by Yashin A. et al. (2007), Biogerontology 8(3), 291(302), <DOI:10.1007/s10522-006-9073-3>.
Author: I. Y. Zhbannikov, Liang He, K. G. Arbeev, A. I. Yashin.
Maintainer: Ilya Y. Zhbannikov <ilya.zhbannikov@duke.edu>

Diff between stpm versions 1.6.4 dated 2017-03-05 and 1.6.6 dated 2017-04-07

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Package secure updated to version 0.5 with previous version 0.3 dated 2017-04-01

Title: Sequential Co-Sparse Factor Regression
Description: Sequential factor extraction via co-sparse unit-rank estimation (SeCURE).
Author: Aditya Mishra [aut, cre], Kun Chen [aut, cre]
Maintainer: Aditya Mishra <aditya.mishra@uconn.edu>

Diff between secure versions 0.3 dated 2017-04-01 and 0.5 dated 2017-04-07

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Package SCRSELECT updated to version 1.1-1 with previous version 1.1-0 dated 2016-09-28

Title: Performs Bayesian Variable Selection on the Covariates in a Semi-Competing Risks Model
Description: Contains four functions used in the DIC-tau_g procedure. SCRSELECT() and SCRSELECTRUN() uses Stochastic Search Variable Selection to select important covariates in the three hazard functions of a semi-competing risks model. These functions perform the Gibbs sampler for variable selection and a Metropolis-Hastings-Green sampler for the number of split points and parameters for the three baseline hazard function. The function SCRSELECT() returns the posterior sample of all quantities sampled in the Gibbs sampler after a burn-in period to a desired file location, while the function SCRSELECTRUN() returns posterior values of important quantities to the DIC-Tau_g procedure in a list. The function DICTAUG() returns a list containing the DIC values for the unique models visited by the DIC-Tau_g grid search. The function ReturnModel() uses SCRSELECTRUN() and DICTAUG() to return a summary of the posterior coefficient vectors for the optimal model along with saving this posterior sample to a desired path location.
Author: Andrew Chapple [aut, cre]
Maintainer: Andrew Chapple <Andrew.G.Chapple@rice.edu>

Diff between SCRSELECT versions 1.1-0 dated 2016-09-28 and 1.1-1 dated 2017-04-07

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Package RSiteCatalyst updated to version 1.4.12 with previous version 1.4.11 dated 2017-03-04

Title: R Client for Adobe Analytics API V1.4
Description: Functions for interacting with the Adobe Analytics API V1.4 (<https://api.omniture.com/admin/1.4/rest/>).
Author: Willem Paling, Randy Zwitch & Jowanza Joseph
Maintainer: Randy Zwitch <rzwitch+rsitecatalyst@gmail.com>

Diff between RSiteCatalyst versions 1.4.11 dated 2017-03-04 and 1.4.12 dated 2017-04-07

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Package RNRCS updated to version 0.1.1 with previous version 0.1.0 dated 2017-04-06

Title: Download NRCS Data
Description: Downloads Natural Resources Conservation Service (NRCS) data for sites in the Soil Climate Analysis Network (SCAN) <https://www.wcc.nrcs.usda.gov/scan/>, and Snow Telemetry (SNOTEL and SNOLITE) <https://www.wcc.nrcs.usda.gov/snow/> networks. Metadata can be returned for all sites in the NRCS' Air and Water Data Base (AWDB) <https://www.wcc.nrcs.usda.gov/report_generator/AWDB_Network_Codes.pdf>.
Author: Robert Lee <rhlee@colorado.edu>, Josh Roberti <jaroberti87@gmail.com>,
Maintainer: Robert Lee <rhlee@colorado.edu>

Diff between RNRCS versions 0.1.0 dated 2017-04-06 and 0.1.1 dated 2017-04-07

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New package rdlocrand with initial version 0.1
Package: rdlocrand
Title: Local Randomization Methods for RD Designs
Version: 0.1
Author: Matias D. Cattaneo, Rocio Titiunik, Gonzalo Vazquez-Bare
Maintainer: Gonzalo Vazquez-Bare <gvazquez@umich.edu>
Description: The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. Under the local randomization approach, RD designs can be interpreted as randomized experiments inside a window around the cutoff. This package provides tools to perform randomization inference for RD designs under local randomization: rdrandinf() to perform hypothesis testing using randomization inference, rdwinselect() to select a window around the cutoff in which randomization is likely to hold, rdsensitivity() to assess the sensitivity of the results to different window lengths and null hypotheses and rdrbounds() to construct Rosenbaum bounds for sensitivity to unobserved confounders.
Imports: AER, sandwich
Depends: R (>= 3.1)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-04-07 17:27:17 UTC; gvazq
Repository: CRAN
Date/Publication: 2017-04-07 17:54:08 UTC

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Package psychomix updated to version 1.1-4 with previous version 1.1-3 dated 2015-09-09

Title: Psychometric Mixture Models
Description: Psychometric mixture models based on 'flexmix' infrastructure. At the moment Rasch mixture models with different parameterizations of the score distribution (saturated vs. mean/variance specification), Bradley-Terry mixture models, and MPT mixture models are implemented. These mixture models can be estimated with or without concomitant variables. See vignette('raschmix', package = 'psychomix') for details on the Rasch mixture models.
Author: Hannah Frick [aut, cre], Friedrich Leisch [aut], Carolin Strobl [aut], Florian Wickelmaier [aut], Achim Zeileis [aut]
Maintainer: Hannah Frick <hannah.frick@gmail.com>

Diff between psychomix versions 1.1-3 dated 2015-09-09 and 1.1-4 dated 2017-04-07

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Package precrec updated to version 0.7.1 with previous version 0.6.2 dated 2017-01-18

Title: Calculate Accurate Precision-Recall and ROC (Receiver Operator Characteristics) Curves
Description: Accurate calculations and visualization of precision-recall and ROC (Receiver Operator Characteristics) curves.
Author: Takaya Saito [aut, cre], Marc Rehmsmeier [aut]
Maintainer: Takaya Saito <takaya.saito@outlook.com>

Diff between precrec versions 0.6.2 dated 2017-01-18 and 0.7.1 dated 2017-04-07

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New package plink with initial version 1.5-0
Package: plink
Version: 1.5-0
Date: 2017-04-04
Title: IRT Separate Calibration Linking Methods
Depends: R (>= 3.3.3), methods, lattice
Imports: MASS, statmod
Author: Jonathan P. Weeks <weeksjp@gmail.com>
Maintainer: Jonathan P. Weeks <weeksjp@gmail.com>
Description: Item response theory based methods are used to compute linking constants and conduct chain linking of unidimensional or multidimensional tests for multiple groups under a common item design. The unidimensional methods include the Mean/Mean, Mean/Sigma, Haebara, and Stocking-Lord methods for dichotomous (1PL, 2PL and 3PL) and/or polytomous (graded response, partial credit/generalized partial credit, nominal, and multiple-choice model) items. The multidimensional methods include the least squares method and extensions of the Haebara and Stocking-Lord method using single or multiple dilation parameters for multidimensional extensions of all the unidimensional dichotomous and polytomous item response models. The package also includes functions for importing item and/or ability parameters from common IRT software, conducting IRT true score and observed score equating, and plotting item response curves/surfaces, vector plots, information plots, and comparison plots for examining parameter drift.
LazyLoad: Yes
LazyData: Yes
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2017-04-07 14:33:11 UTC; Jonathan
Repository: CRAN
Date/Publication: 2017-04-07 17:05:38 UTC

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Package MonteCarlo updated to version 1.0.1 with previous version 1.0.0 dated 2017-03-17

Title: Automatic Parallelized Monte Carlo Simulations
Description: Simplifies Monte Carlo simulation studies by automatically setting up loops to run over parameter grids and parallelising the Monte Carlo repetitions. It also generates LaTeX tables.
Author: Christian Hendrik Leschinski
Maintainer: Christian Hendrik Leschinski <leschinski@statistik.uni-hannover.de>

Diff between MonteCarlo versions 1.0.0 dated 2017-03-17 and 1.0.1 dated 2017-04-07

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Package microPop updated to version 1.1 with previous version 1.0 dated 2017-03-29

Title: Modelling Microbial Populations
Description: Modelling interacting microbial populations - example applications include human gut microbiota, rumen microbiota and phytoplankton. Solves a system of ordinary differential equations to simulate microbial growth and resource uptake over time.
Author: Helen Kettle [aut, cre]
Maintainer: Helen Kettle <Helen.Kettle@bioss.ac.uk>

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Package heemod updated to version 0.9.0 with previous version 0.8.0 dated 2017-02-10

Title: Models for Health Economic Evaluation
Description: Health Economic Evaluation Modelling: decision trees and cohort simulations. Provides a simple and consistent interface for Markov models specification, comparison, sensitivity and probabilistic analysis, input of survival models, etc. Models with time varying properties (non-homogeneous Markov models and semi-Markov models) are supported.
Author: Antoine Filipovic-Pierucci [aut, cre], Kevin Zarca [aut], Matthew Wiener [ctb], Zdenek Kabat [ctb], Vojtech Filipec [ctb], Jordan Amdahl [ctb]
Maintainer: Antoine Filipovic-Pierucci <pierucci@gmail.com>

Diff between heemod versions 0.8.0 dated 2017-02-10 and 0.9.0 dated 2017-04-07

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Permanent link

Package filehash updated to version 2.4-1 with previous version 2.3 dated 2015-08-16

Title: Simple Key-Value Database
Description: Implements a simple key-value style database where character string keys are associated with data values that are stored on the disk. A simple interface is provided for inserting, retrieving, and deleting data from the database. Utilities are provided that allow 'filehash' databases to be treated much like environments and lists are already used in R. These utilities are provided to encourage interactive and exploratory analysis on large datasets. Three different file formats for representing the database are currently available and new formats can easily be incorporated by third parties for use in the 'filehash' framework.
Author: Roger D. Peng <rdpeng@jhu.edu>
Maintainer: Roger D. Peng <rdpeng@jhu.edu>

Diff between filehash versions 2.3 dated 2015-08-16 and 2.4-1 dated 2017-04-07

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Permanent link

New package duckduckr with initial version 1.0.0
Package: duckduckr
Type: Package
Title: Simple Client for the DuckDuckGo Instant Answer API
Version: 1.0.0
Authors@R: c(person("Schumacher", "Dirk", email = "mail@dirk-schumacher.net", role = c("aut", "cre")))
Description: Programmatic access to the DuckDuckGo Instant Answer API <https://api.duckduckgo.com/api>.
License: MIT + file LICENSE
URL: https://github.com/dirkschumacher/duckduckr
BugReports: https://github.com/dirkschumacher/duckduckr/issues
Encoding: UTF-8
LazyData: true
Imports: crul, jsonlite
Suggests: testthat, covr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-04-07 13:48:06 UTC; dirkschumacher
Author: Schumacher Dirk [aut, cre]
Maintainer: Schumacher Dirk <mail@dirk-schumacher.net>
Repository: CRAN
Date/Publication: 2017-04-07 17:06:07 UTC

More information about duckduckr at CRAN
Permanent link

Package checkpoint updated to version 0.3.22 with previous version 0.3.18 dated 2016-10-31

Title: Install Packages from Snapshots on the Checkpoint Server for Reproducibility
Description: The goal of checkpoint is to solve the problem of package reproducibility in R. Specifically, checkpoint allows you to install packages as they existed on CRAN on a specific snapshot date as if you had a CRAN time machine. To achieve reproducibility, the checkpoint() function installs the packages required or called by your project and scripts to a local library exactly as they existed at the specified point in time. Only those packages are available to your project, thereby avoiding any package updates that came later and may have altered your results. In this way, anyone using checkpoint's checkpoint() can ensure the reproducibility of your scripts or projects at any time. To create the snapshot archives, once a day (at midnight UTC) Microsoft refreshes the Austria CRAN mirror on the "Microsoft R Archived Network" server (<https://mran.microsoft.com/>). Immediately after completion of the rsync mirror process, the process takes a snapshot, thus creating the archive. Snapshot archives exist starting from 2014-09-17.
Author: Microsoft Corporation
Maintainer: Andrie de Vries <adevries@microsoft.com>

Diff between checkpoint versions 0.3.18 dated 2016-10-31 and 0.3.22 dated 2017-04-07

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More information about checkpoint at CRAN
Permanent link

New package BART with initial version 1.0
Package: BART
Type: Package
Title: Bayesian Additive Regression Trees
Version: 1.0
Date: 2017-04-06
Author: Robert McCulloch <robert.e.mcculloch@gmail.com> and Rodney Sparapani <rsparapa@mcw.edu>
Maintainer: Rodney Sparapani <rsparapa@mcw.edu>
Description: Bayesian Additive Regression Trees (BART) provide flexible nonparametric modeling of covariates for continuous, binary and time-to-event outcomes. For more information on BART, see Chipman, George and McCulloch (2010) <doi:10.1214/09-AOAS285> and Sparapani, Logan, McCulloch and Laud (2016) <doi:10.1002/sim.6893>.
License: GPL (>= 2)
Depends: R (>= 2.10), parallel, survival, tools
Imports: Rcpp (>= 0.12.3)
LinkingTo: Rcpp
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2017-04-07 15:22:37 UTC; rsparapa
Repository: CRAN
Date/Publication: 2017-04-07 17:01:15 UTC

More information about BART at CRAN
Permanent link

Package TLMoments updated to version 0.7.2.1 with previous version 0.6.3.1 dated 2017-01-18

Title: Calculate TL-Moments and Convert Them to Distribution Parameters
Description: Calculates empirical TL-moments (trimmed L-moments) of arbitrary order and trimming, and converts them to distribution parameters.
Author: Jona Lilienthal
Maintainer: Jona Lilienthal <lilienthal@statistik.tu-dortmund.de>

Diff between TLMoments versions 0.6.3.1 dated 2017-01-18 and 0.7.2.1 dated 2017-04-07

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More information about TLMoments at CRAN
Permanent link

Package stringi updated to version 1.1.5 with previous version 1.1.3 dated 2017-03-21

Title: Character String Processing Facilities
Description: Allows for fast, correct, consistent, portable, as well as convenient character string/text processing in every locale and any native encoding. Owing to the use of the ICU library, the package provides R users with platform-independent functions known to Java, Perl, Python, PHP, and Ruby programmers. Available features include: pattern searching (e.g., with ICU Java-like regular expressions or the Unicode Collation Algorithm), random string generation, case mapping, string transliteration, concatenation, Unicode normalization, date-time formatting and parsing, etc.
Author: Marek Gagolewski [aut, cre], Bartek Tartanus [ctb], and other contributors (stringi source code); IBM and other contributors (ICU4C 55.1 source code); Unicode, Inc. (Unicode Character Database)
Maintainer: Marek Gagolewski <gagolews@rexamine.com>

Diff between stringi versions 1.1.3 dated 2017-03-21 and 1.1.5 dated 2017-04-07

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Package repr updated to version 0.12.0 with previous version 0.10 dated 2016-11-25

Title: Serializable Representations
Description: String and binary representations of objects for several formats / mime types.
Author: Philipp Angerer [aut, cre], Thomas Kluyver [aut], Jan Schulz [aut], abielr [ctb], Denilson Figueiredo de Sa [ctb], Jim Hester [ctb], karldw [ctb]
Maintainer: Philipp Angerer <phil.angerer@gmail.com>

Diff between repr versions 0.10 dated 2016-11-25 and 0.12.0 dated 2017-04-07

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More information about repr at CRAN
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Package vegan updated to version 2.4-3 with previous version 2.4-2 dated 2017-01-17

Title: Community Ecology Package
Description: Ordination methods, diversity analysis and other functions for community and vegetation ecologists.
Author: Jari Oksanen, F. Guillaume Blanchet, Michael Friendly, Roeland Kindt, Pierre Legendre, Dan McGlinn, Peter R. Minchin, R. B. O'Hara, Gavin L. Simpson, Peter Solymos, M. Henry H. Stevens, Eduard Szoecs, Helene Wagner
Maintainer: Jari Oksanen <jari.oksanen@oulu.fi>

Diff between vegan versions 2.4-2 dated 2017-01-17 and 2.4-3 dated 2017-04-07

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More information about vegan at CRAN
Permanent link

Package TANDEM updated to version 1.0.1 with previous version 1.0.0 dated 2016-09-19

Title: A Two-Stage Approach to Maximize Interpretability of Drug Response Models Based on Multiple Molecular Data Types
Description: A two-stage regression method that can be used when various input data types are correlated, for example gene expression and methylation in drug response prediction. In the first stage it uses the upstream features (such as methylation) to predict the response variable (such as drug response), and in the second stage it uses the downstream features (such as gene expression) to predict the residuals of the first stage. In our manuscript (Aben et al., 2016, <doi:10.1093/bioinformatics/btw449>), we show that using TANDEM prevents the model from being dominated by gene expression and that the features selected by TANDEM are more interpretable.
Author: Nanne Aben
Maintainer: Nanne Aben <nanne.aben@gmail.com>

Diff between TANDEM versions 1.0.0 dated 2016-09-19 and 1.0.1 dated 2017-04-07

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More information about TANDEM at CRAN
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New package splithalf with initial version 0.1.0
Package: splithalf
Type: Package
Title: Calculate Task Split Half Reliability Estimates
Version: 0.1.0
Authors@R: person("Sam", "Parsons", email = "sam.parsons@psy.ox.ac.uk", role = c("aut", "cre"))
Maintainer: Sam Parsons <sam.parsons@psy.ox.ac.uk>
Description: A series of functions to calculate the split half reliability of RT based tasks. The core function performs a Monte Carlo procedure to process a user defined number of random splits in order to provide a better reliability estimate. The current functions target the dot- probe task, however, can be modified for other tasks.
Depends: R (>= 3.3.2)
Imports: plyr, stats
Suggests: testthat, knitr, rmarkdown, tools, ggplot2
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1.9000
URL: http://github.com/sdparsons/splithalf
BugReports: http://github.com/sdparsons/splithalf
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-04-07 09:50:21 UTC; parsonss
Author: Sam Parsons [aut, cre]
Repository: CRAN
Date/Publication: 2017-04-07 12:33:43 UTC

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Package rpsftm updated to version 1.1.0 with previous version 1.0.2 dated 2016-11-25

Title: Rank Preserving Structural Failure Time Models
Description: Implements methods described by the paper Robins and Tsiatis (1991) <DOI:10.1080/03610929108830654>. These use g-estimation to estimate the causal effect of a treatment in a two-armed randomised control trial where non-compliance exists and is measured, under an assumption of an accelerated failure time model and no unmeasured confounders.
Author: Simon Bond [aut, cre] (primary author of code, secondary author of vignette), Annabel Allison [aut] (primary author of vignette, secondary author of code)
Maintainer: Simon Bond <simon.bond@addenbrookes.nhs.uk>

Diff between rpsftm versions 1.0.2 dated 2016-11-25 and 1.1.0 dated 2017-04-07

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More information about rpsftm at CRAN
Permanent link

Package gldist (with last version 2160.2) was removed from CRAN

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

2012-04-02 2160.2
2012-03-27 2160.1

Permanent link
Package sdcTable updated to version 0.22.4 with previous version 0.22.1 dated 2017-02-23

Title: Methods for Statistical Disclosure Control in Tabular Data
Description: Methods for statistical disclosure control in tabular data such as primary and secondary cell suppression are covered in this package.
Author: Bernhard Meindl
Maintainer: Bernhard Meindl <bernhard.meindl@statistik.gv.at>

Diff between sdcTable versions 0.22.1 dated 2017-02-23 and 0.22.4 dated 2017-04-07

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Package epiR updated to version 0.9-82 with previous version 0.9-79 dated 2016-07-18

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

Diff between epiR versions 0.9-79 dated 2016-07-18 and 0.9-82 dated 2017-04-07

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More information about epiR at CRAN
Permanent link

Package rslurm updated to version 0.3.2 with previous version 0.3.1 dated 2016-06-18

Title: Submit R Calculations to a 'SLURM' Cluster
Description: Functions that simplify the R interface the 'SLURM' cluster workload manager, and automate the process of dividing a parallel calculation across cluster nodes.
Author: Philippe Marchand [aut], Mike Smorul [ctb], Ian Carroll [ctb, cre]
Maintainer: Ian Carroll <icarroll@sesync.org>

Diff between rslurm versions 0.3.1 dated 2016-06-18 and 0.3.2 dated 2017-04-07

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Permanent link

Package rnbn (with last version 1.1.2) was removed from CRAN

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

2017-01-12 1.1.2
2014-12-12 1.0.3
2014-07-22 1.0.0

Permanent link
Package spind updated to version 2.0.1 with previous version 2.0.0 dated 2017-04-04

Title: Spatial Methods and Indices
Description: Functions for spatial methods based on generalized estimating equations (GEE) and wavelet-revised methods (WRM), functions for scaling by wavelet multiresolution regression (WMRR), conducting multi-model inference, and stepwise model selection. Further, contains functions for spatially corrected model accuracy measures.
Author: Gudrun Carl [cre, aut], Ingolf Kuehn [aut], Sam Levin [aut]
Maintainer: Sam Levin <levisc8@gmail.com>

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Package sjmisc updated to version 2.4.0 with previous version 2.3.1 dated 2017-03-06

Title: Data Transformation and Labelled Data Utility Functions
Description: Collection of miscellaneous utility functions (especially intended for people coming from other statistical software packages like 'SPSS', and/ or who are new to R), supporting following common tasks when working with data : 1) Reading and writing data between R and other statistical software packages like 'SPSS', 'SAS' or 'Stata' and working with labelled data; this includes easy ways to get and set label attributes, to convert labelled vectors into factors (and vice versa), or to deal with multiple declared missing values etc. 2) Data transformation tasks like recoding, dichotomizing or grouping variables, setting and replacing missing values. The data transformation functions also support labelled data, and all integrate seamlessly into a 'tidyverse'-workflow.
Author: Daniel Lüdecke <d.luedecke@uke.de>
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between sjmisc versions 2.3.1 dated 2017-03-06 and 2.4.0 dated 2017-04-07

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More information about sjmisc at CRAN
Permanent link

Package beyondWhittle updated to version 0.18.1 with previous version 0.17 dated 2017-01-23

Title: Bayesian Spectral Inference for Stationary Time Series
Description: Implementations of a Bayesian parametric (autoregressive), a Bayesian nonparametric (Whittle likelihood with Bernstein-Dirichlet prior) and a Bayesian semiparametric (autoregressive likelihood with Bernstein-Dirichlet correction) procedure are provided. The work is based on the corrected parametric likelihood by C. Kirch et al (2017) <arXiv:1701.04846>. It was supported by DFG grant KI 1443/3-1.
Author: Alexander Meier [aut, cre], Claudia Kirch [aut], Matthew C. Edwards [aut], Renate Meyer [aut]
Maintainer: Alexander Meier <alexander.meier@ovgu.de>

Diff between beyondWhittle versions 0.17 dated 2017-01-23 and 0.18.1 dated 2017-04-07

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Package umx updated to version 1.7.5 with previous version 1.5.5 dated 2017-03-21

Title: Structural Equation Modelling in R with 'OpenMx'
Description: Quickly create, run, and report structural equation and twin models. See '?umx' to learn more.
Author: Timothy C Bates [aut, cre]
Maintainer: Timothy C Bates <timothy.c.bates@gmail.com>

Diff between umx versions 1.5.5 dated 2017-03-21 and 1.7.5 dated 2017-04-07

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More information about umx at CRAN
Permanent link

Package textmineR updated to version 2.0.5 with previous version 2.0.4 dated 2016-11-03

Title: Functions for Text Mining and Topic Modeling
Description: An aid for text mining in R, with a syntax that should be familiar to experienced R users. Provides a wrapper for several topic models that take similarly-formatted input and give similarly-formatted output. Has additional functionality for analyzing and diagnostics for topic models.
Author: Thomas Jones [aut, cre], William Doane [ctb]
Maintainer: Thomas Jones <jones.thos.w@gmail.com>

Diff between textmineR versions 2.0.4 dated 2016-11-03 and 2.0.5 dated 2017-04-07

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New package sylcount with initial version 0.1-0
Package: sylcount
Type: Package
Title: Syllable Counting and Readability Measurements
Version: 0.1-0
Description: An English language syllable counter, plus readability score measure-er. The package has been carefully optimized and should be very efficient, both in terms of run time performance and memory consumption. The main methods are 'vectorized' by document, and scores for multiple documents are computed in parallel via 'OpenMP'.
License: BSD 2-clause License + file LICENSE
Depends: R (>= 3.0.0)
LazyData: yes
LazyLoad: yes
NeedsCompilation: yes
ByteCompile: yes
Authors@R: c(person("Drew", "Schmidt", role=c("aut", "cre"), email="wrathematics@gmail.com"))
Maintainer: Drew Schmidt <wrathematics@gmail.com>
URL: https://github.com/wrathematics/sylcount
BugReports: https://github.com/wrathematics/sylcount/issues
RoxygenNote: 6.0.1
Packaged: 2017-04-07 04:48:46 UTC; mschmid3
Author: Drew Schmidt [aut, cre]
Repository: CRAN
Date/Publication: 2017-04-07 06:19:11 UTC

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New package MedDietCalc with initial version 0.1.0
Package: MedDietCalc
Type: Package
Title: Multi Calculator to Compute Scores of Adherence to Mediterranean Diet
Version: 0.1.0
Authors@R: c( person("Miguel", "Menendez", email = "miguelmo@gmail.com", role = c("aut", "cre")), person("David", "Lora", email = "david@h12o.es", role = "ctb"), person("Agustin", "Gomez-Camara", role = "dtc"))
Author: Miguel Menendez [aut, cre], David Lora [ctb], Agustin Gomez-Camara [dtc]
Maintainer: Miguel Menendez <miguelmo@gmail.com>
Description: Multi Calculator of different scores to measure adherence to Mediterranean Diet, to compute them in nutriepidemiological data. Additionally, a sample dataset of this kind of data is provided, and some other minor tools useful in epidemiological studies.
License: GPL-3
LazyData: TRUE
RoxygenNote: 5.0.1
Imports: stats
Suggests: graphics, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-04-06 23:13:40 UTC; miguel
Repository: CRAN
Date/Publication: 2017-04-07 06:19:15 UTC

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Package lavaan.shiny updated to version 1.2 with previous version 1.1 dated 2016-06-24

Title: Latent Variable Analysis with Shiny
Description: Interactive shiny application for working with different kinds of latent variable analysis, with the 'lavaan' package. Graphical output for models are provided and different estimators are supported.
Author: W. Kyle Hamilton <kyle.hamilton@gmail.com>
Maintainer: W. Kyle Hamilton <kyle.hamilton@gmail.com>

Diff between lavaan.shiny versions 1.1 dated 2016-06-24 and 1.2 dated 2017-04-07

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New package IMTest with initial version 1.0.0
Package: IMTest
Title: Information Matrix Test for Generalized Partial Credit Models
Version: 1.0.0
Authors@R: person("Daphna","Harel",email = "daphna.harel@nyu.edu",role=c("cre","aut"))
Description: Implementation of the information matrix test for generalized partial credit models.
Depends: R (>= 3.3.0), ltm
Imports: MASS, lme4, reshape2
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-04-07 01:37:58 UTC; daphnaharel
Author: Daphna Harel [cre, aut]
Maintainer: Daphna Harel <daphna.harel@nyu.edu>
Repository: CRAN
Date/Publication: 2017-04-07 06:19:14 UTC

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Package getCRUCLdata updated to version 0.1.5 with previous version 0.1.4 dated 2017-02-03

Title: Use and Explore CRU CL v. 2.0 Climatology Elements in R
Description: Provides functions that automate downloading and importing University of East Anglia Climate Research Unit (CRU) CL v. 2.0 climatology data into R, facilitates the calculation of minimum temperature and maximum temperature and formats the data into a tidy data frame as a tibble or a list of raster stack objects for use in an R session. CRU CL v. 2.0 data are a gridded climatology of 1961-1990 monthly means released in 2002 and cover all land areas (excluding Antarctica) at 10 arcminutes (0.1666667 degree) resolution. For more information see the description of the data provided by the University of East Anglia Climate Research Unit, <https://crudata.uea.ac.uk/cru/data/hrg/tmc/readme.txt>.
Author: Adam Sparks [aut, cre]
Maintainer: Adam Sparks <adamhsparks@gmail.com>

Diff between getCRUCLdata versions 0.1.4 dated 2017-02-03 and 0.1.5 dated 2017-04-07

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Package chinese.misc updated to version 0.1.5 with previous version 0.1.4 dated 2017-03-23

Title: Miscellaneous Tools for Chinese Text Mining and More
Description: Efforts are made to make Chinese text mining easier, faster, and robust to errors. Document term matrix can be generated by only one line of code; detecting encoding, segmenting and removing stop words are done automatically. Some convenient tools are also supplied.
Author: Jiang Wu [aut, cre] (from Tsinghua University)
Maintainer: Jiang Wu <textidea@sina.com>

Diff between chinese.misc versions 0.1.4 dated 2017-03-23 and 0.1.5 dated 2017-04-07

 DESCRIPTION           |    8 +++---
 MD5                   |   20 ++++++++--------
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Package rscproxy (with last version 2.0-5) was removed from CRAN

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

2012-05-02 2.0-5
2012-04-25 2.0-1
2009-04-15 1.3-1
2009-03-20 1.2-0
2008-10-30 1.0-12
2008-10-17 1.0-11
2008-10-14 1.0-9
2008-08-14 1.0-6

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