Package: mombf 4.0.0

mombf: Model Selection with Bayesian Methods and Information Criteria

Model selection and averaging for regression and mixtures, inclusing Bayesian model selection and information criteria (BIC, EBIC, AIC, GIC).

Authors:David Rossell [aut, cre], John D. Cook [aut], Donatello Telesca [aut], P. Roebuck [aut], Oriol Abril [aut], Miquel Torrens [aut]

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
mombf/json (API)

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

Bug tracker:https://github.com/davidrusi/mombf/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

openblascppopenmp

6.64 score 7 stars 2 packages 172 scripts 374 downloads 82 exports 40 dependencies

Last updated from:35b288ea72. Checks:12 ERROR, 1 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64ERROR266
linux-devel-x86_64ERROR232
source / vignettesERROR395
linux-release-arm64ERROR258
linux-release-x86_64ERROR189
macos-release-arm64ERROR168
macos-release-x86_64ERROR322
macos-oldrel-arm64ERROR182
macos-oldrel-x86_64ERROR404
windows-develERROR240
windows-releaseERROR254
windows-oldrelERROR253
wasm-releaseOK171

Exports:aicbbPriorbestAICbestBICbestEBICbestICbfnormmixbicbicpriorbinomPriorcilcoefByModeldalaplddirdemomdemomigmargdimomdiwishdmomdmomigmargdpostNIWemomprioreprodexponentialpriorgetAICgetBICgetEBICgetICgroupemompriorgroupimompriorgroupmompriorgroupzellnerprioricicarplusprioricovigpriorimombfimomknownimompriorimomunknownlocalnulltestlocalnulltest_fdalocalnulltest_fda_givenknotslocalnulltest_givenknotsmarginalNIWmodelbbpriormodelbinompriormodelcomplexpriormodelsearchBlockDiagmodelSelectionmodelSelection_eBayesmodelSelectionGGMmodelunifpriormombfmomknownmompriormomunknownnlpMarginalnormalidpriorpalaplpemompemomigmargpimompimomMarginalKpimomMarginalUplotpriorpmompmomigmargpmomMarginalKpmomMarginalUpostModeBlockDiagpostModeOrthopostProbpostSamplespriorp2gqimomqmomralaplrnlprpostNIWunifPriorzellnerprior

Dependencies:clicodetoolscpp11dplyrforeachgenericsglmnetgluehugeigraphintervalsiteratorslatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmclustmgcvmvtnormncvregnlmepillarpkgconfigpracmaR6RcppRcppArmadilloRcppEigenrlangshapesparseMatrixStatssurvivaltibbletidyselectutf8vctrswithr

Readme and manuals

Help Manual

Help pageTopics
Priors on model space for variable selection problemsbbPrior binomPrior unifPrior
Model with best AIC, BIC, EBIC or other general information criteria (getIC)bestAIC bestBIC bestEBIC bestIC
Number of Normal mixture components under Normal-IW and Non-local priorsbfnormmix
Treatment effect estimation for linear models via Confounder Importance Learning using non-local priors.cil
Density and random draws from the asymmetric Laplace distributiondalapl palapl ralapl
Dirichlet densityddir
Density for Inverse Wishart distributiondiwish
Non-local prior density, cdf and quantile functions.demom demom,data.frame-method demom,matrix-method demom,vector-method demom-methods demomigmarg dimom dmom dmomigmarg pemom pemomigmarg pimom pmom pmomigmarg qimom qmom
Posterior Normal-IWishart densitydpostNIW rpostNIW
Expectation of a product of powers of Normal or T random variableseprod
Obtain AIC, BIC, EBIC or other general information criteria (getIC)getAIC getAIC,msfit-method getAIC-methods getBIC getBIC,msfit-method getBIC-methods getEBIC getEBIC,msfit-method getEBIC-methods getIC getIC,msfit-method getIC-methods
Hald Datahald x.hald y.hald
Class "icfit"icfit icfit-class icfit.coef icfit.predict icfit.summary show,icfit-method
Extract estimated inverse covarianceicov
Local variable selectionlocalnulltest localnulltest_fda localnulltest_fda_givenknots localnulltest_givenknots
Marginal likelihood under a multivariate Normal likelihood and a conjugate Normal-inverse Wishart prior.marginalNIW marginalNIW,matrix,missing,missing,missing,missing-method marginalNIW,matrix,missing,missing,missing,vector-method marginalNIW,missing,ANY,matrix,numeric,missing-method marginalNIW,missing,list,list,numeric,missing-method marginalNIW-methods
Class "mixturebf"coef.mixturebf mixturebf mixturebf-class show,mixturebf-method
Bayesian variable selection for generalized linear and generalized additive models.modelsearchBlockDiag modelSelection modelSelection_eBayes
Bayesian variable selection for linear models via non-local priors.modelSelectionGGM
Moment and inverse moment Bayes factors for linear models.imombf imombf.lm mombf mombf.lm
Bayes factors for moment and inverse moment priorsimomknown imomunknown momknown momunknown
Class "msfit_ggm"msfit_ggm msfit_ggm-class msfit_ggm.coef show,msfit_ggm-method
Class "msfit"coefByModel coefByModel,msfit-method coefByModel-methods msfit msfit-class msfit.coef msfit.plot msfit.predict show,msfit-method
Class "msPriorSpec"aic bic bicprior emomprior exponentialprior groupemomprior groupimomprior groupmomprior groupzellnerprior ic icarplusprior igprior imomprior modelbbprior modelbinomprior modelcomplexprior modelunifprior momprior msPriorSpec msPriorSpec-class normalidprior zellnerprior
Marginal density of the observed data for linear regression with Normal, two-piece Normal, Laplace or two-piece Laplace residuals under non-local and Zellner priorsnlpMarginal nlpmarginals pimomMarginalK pimomMarginalU pmomMarginalK pmomMarginalU
Plot estimated marginal prior inclusion probabilitiesplotprior plotprior,cilfit-method plotprior-methods
Bayesian model selection and averaging under block-diagonal X'X for linear models.postModeBlockDiag postModeOrtho
Obtain posterior model probabilitiespostProb postProb,cilfit-method postProb,localtest-method postProb,mixturebf-method postProb,msfit-method postProb,msfit_ggm-method postProb-methods
Extract posterior samples from an objectpostSamples postSamples,mixturebf-method postSamples-methods
Moment and inverse moment prior elicitationpriorp2g
Posterior sampling for regression parametersrnlp rnlp,ANY,matrix,missing,missing,missing,character,character-method rnlp,ANY,matrix,missing,missing,missing,missing,missing-method rnlp,ANY,matrix,missing,missing,msfit,missing,missing-method rnlp,missing,missing,missing,missing,msfit,missing,missing-method rnlp,missing,missing,numeric,matrix,missing,missing,missing-method rnlp-methods