Package: Boom 0.9.15

Boom: Bayesian Object Oriented Modeling

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.

Authors: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, NEWUOA, and a modified version of the R math libraries. 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.

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Boom.pdf |Boom.html✨
Boom/json (API)

# Install 'Boom' in R:
install.packages('Boom', repos = c('https://steve-the-bayesian.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5.34 score 9 stars 6 packages 58 scripts 7.8k downloads 78 exports 1 dependencies

Last updated 10 months agofrom:bea70a9879. Checks:OK: 3 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-win-x86_64OKOct 31 2024
R-4.5-linux-x86_64OKOct 31 2024
R-4.4-win-x86_64NOTEOct 31 2024
R-4.4-mac-x86_64NOTEOct 31 2024
R-4.4-mac-aarch64NOTEOct 31 2024
R-4.3-win-x86_64NOTEOct 31 2024
R-4.3-mac-x86_64NOTEOct 31 2024
R-4.3-mac-aarch64NOTEOct 31 2024

Exports:AddExternalLegendAddSegmentsAr1CoefficientPriorBetaPriorBoxplotMcmcMatrixBoxplotTruecheck.nonnegative.scalarcheck.positive.scalarcheck.probability.distributioncheck.scalar.booleancheck.scalar.integercheck.scalar.probabilityCheckMcmcMatrixCheckMcmcVectorcirclesCompareDensitiesCompareDynamicDistributionsCompareManyDensitiesCompareManyTsCompareVectorBoxplotsddirichletdInverseWishartdinvgammaDirichletPriorDiscreteUniformPriordmvndWishartExternalLegendLayoutGammaPriorGaussianSufGenerateFactorDatahistabunchInverseWishartPriorIsEvenIsOddlmgammaLogIntegratedGaussianLikelihoodLognormalPriorMarkovPriorMatchDataFrameMcmcMatrixReportmscanMvnDiagonalPriorMvnGivenSigmaMatrixPriorMvnIndependentSigmaPriorMvnPriorNormalInverseGammaPriorNormalInverseWishartPriorNormalPriorPairsDensitypinvgammaPlotDensityContoursPlotDynamicDistributionPlotMacfPlotManyTsPointMassPriorPoissonPriorqinvgammardirichletRegressionCoefficientConjugatePriorRegressionSufRepListrinvgammarmvnRVectorFunctionrWishartScaledMatrixNormalPriorSdPriorSuggestBurnLogLikelihoodthinThinMatrixTimeSeriesBoxplotToStringToString.defaultToString.tableTraceProductTruncatedGammaPriorUniformPrior

Dependencies:MASS

Readme and manuals

Help Manual

Help pageTopics
BoomBoom-package Boom
Function to add horizontal line segments to an existing plotadd.segments AddSegments
Normal prior for an AR1 coefficientAr1CoefficientPrior
Beta prior for a binomial proportionBetaPrior
Plot the distribution of a matrixboxplot.mcmc.matrix BoxplotMcmcMatrix
Compare Boxplots to True Valuesboxplot.true BoxplotTrue
Check MCMC OutputCheckMcmcMatrix CheckMcmcVector McmcMatrixReport
Checking data formatscheck.data check.nonnegative.scalar check.positive.scalar check.probability.distribution check.scalar.boolean check.scalar.integer check.scalar.probability
Draw Circlescircles
Compare several density estimates.compare.den compare.densities CompareDen CompareDensities
Compare Dynamic DistributionsCompareDynamicDistributions
Compare several density estimates.compare.many.densities CompareManyDensities
Compares several density estimates.compare.many.ts CompareManyTs
Boxplots to compare distributions of vectorscompare.vector.boxplots CompareVectorBoxplots
DiffDoubleModelDiffDoubleModel
The Dirichlet Distributionddirichlet rdirichlet
Dirichlet prior for a multinomial distributionDirichletPrior
Discrete prior distributionsDiscreteUniformPrior PointMassPrior PoissonPrior
Multivariate Normal Densitydmvn
Prior distributions for a real valued scalardouble.model DoubleModel
Add an external legend to an array of plots.AddExternalLegend ExternalLegendLayout
Gamma prior distributionGammaPrior TruncatedGammaPrior
Generate a data frame of all factor dataGenerateFactorData
A Bunch of Histogramshistabunch
Inverse Wishart DistributiondInverseWishart InverseWishartPrior
Inverse Gamma Distributiondinvgamma pinvgamma qinvgamma rinvgamma
Check whether a number is even or odd.is.even is.odd IsEven IsOdd
Log Multivariate Gamma Functionlmgamma
Log Integrated Gaussian LikelihoodLogIntegratedGaussianLikelihood
Lognormal Prior DistributionLognormalPrior
Prior for a Markov chainMarkovPrior
MatchDataFrameMatchDataFrame
Scan a Matrixmscan
diagonal MVN priorMvnDiagonalPrior
Independence prior for the MVNMvnIndependentSigmaPrior
Multivariate normal priorMvnPrior
Conditional Multivaraite Normal Prior Given VarianceMvnGivenSigmaMatrixPrior
Normal inverse gamma priorNormalInverseGammaPrior
Normal inverse Wishart priorNormalInverseWishartPrior
Normal (scalar Gaussian) prior distributionNormalPrior
Pairs plot for posterior distributions.PairsDensity
Contour plot of a bivariate density.PlotDensityContours
Plots the pointwise evolution of a distribution over an index set.PlotDynamicDistribution
Plots individual autocorrelation functions for many-valued time seriesplot.macf PlotMacf
Multiple time series plotsplot.many.ts PlotManyTs
Regression Coefficient Conjugate PriorRegressionCoefficientConjugatePrior
Repeated Lists of ObjectsRepList
Multivariate Normal Simulationrmvn
RVectorFunctionRVectorFunction
Scaled Matrix-Normal PriorScaledMatrixNormalPrior
Prior for a standard deviation or varianceSdPrior
Sufficient StatisticsGaussianSuf RegressionSuf
Suggest MCMC Burn-in from Log LikelihoodSuggestBurnLogLikelihood
Thin the rows of a matrixthin
Thin a MatrixThinMatrix
Time Series BoxplotsTimeSeriesBoxplot
Convert to Character StringToString ToString.default ToString.table
Trace of the Product of Two MatricesTraceProduct
Uniform prior distributionUniformPrior
Wishart DistributiondWishart rWishart