Package: RprobitB 1.1.4
RprobitB: Bayesian Probit Choice Modeling
Bayes estimation of probit choice models, both in the cross-sectional and panel setting. The package can analyze binary, multivariate, ordered, and ranked choices, as well as heterogeneity of choice behavior among deciders. The main functionality includes model fitting via Markov chain Monte Carlo m ethods, tools for convergence diagnostic, choice data simulation, in-sample and out-of-sample choice prediction, and model selection using information criteria and Bayes factors. The latent class model extension facilitates preference-based decider classification, where the number of latent classes can be inferred via the Dirichlet process or a weight-based updating heuristic. This allows for flexible modeling of choice behavior without the need to impose structural constraints. For a reference on the method see Oelschlaeger and Bauer (2021) <https://trid.trb.org/view/1759753>.
Authors:
RprobitB_1.1.4.tar.gz
RprobitB_1.1.4.tar.gz(r-4.5-noble)RprobitB_1.1.4.tar.gz(r-4.4-noble)
RprobitB_1.1.4.tgz(r-4.4-emscripten)RprobitB_1.1.4.tgz(r-4.3-emscripten)
RprobitB.pdf |RprobitB.html✨
RprobitB/json (API)
NEWS
# Install 'RprobitB' in R: |
install.packages('RprobitB', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/loelschlaeger/rprobitb/issues
Pkgdown:https://loelschlaeger.de
- train_choice - Stated Preferences for Train Traveling
Last updated 10 months agofrom:207d41e220. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 23 2024 |
R-4.5-linux-x86_64 | OK | Nov 23 2024 |
Exports:as_cov_namescheck_priorchoice_probabilitiesclassificationcompute_p_sicov_mixcreate_lagged_covd_to_gammadmvnormeuc_distfit_modelget_covll_orderedmmlmodel_selectionnparoverview_effectsplot_rocpoint_estimatespred_accprepare_dataR_hatrdirichletrmvnormRprobitB_parameterrtnormrttnormrwishartsimulate_choicestrain_testupdate_bupdate_dupdate_mupdate_Omegaupdate_regupdate_supdate_Sigmaupdate_Uupdate_U_rankedupdate_zWAIC
Dependencies:askpassassertthatbackportsbase64encBBbenchmarkmebenchmarkmeDatabriobslibcachemcallrcheckmateclicliprcodetoolscolorspacecommonmarkcpp11crayoncredentialscrosstalkcurldata.tabledescdiffobjdigestdoParalleldoSNOWdplyrevaluatefansifarverfastmapfontawesomeforeachfsgenericsGenOrdgertggfunggimageggplot2ggplotifyghgitcredsglueGPArotationgridExtragridGraphicsgridSVGgtablehexbinhexStickerhighrhmshtmltoolshtmlwidgetshttpuvhttrhttr2iniisobanditeratorsjquerylibjsonlitekernlabknitrlabelinglaterlatex2explatticelazyevallifecyclemagickmagrittrMASSMatrixmemoisemgcvmimemixtoolsmnormtmunsellmvtnormnleqslvnlmeoeliopensslpillarpkgbuildpkgconfigpkgloadplotlyplotROCplyrpraiseprettyunitsprocessxprogresspromisespspsychpurrrquadprogR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRdpackrlangrmarkdownrprojrootrstudioapisassscalessegmentedshinyshowtextshowtextdbSimMultiCorrDatasnowsourcetoolsstringistringrsurvivalsyssysfontstestthattibbletidyrtidyselecttinytextriangleusethisutf8vctrsVGAMviridisviridisLitewaldowhiskerwithrxfunXMLxtableyamlyulab.utilszip
Choice data
Rendered fromv02_choice_data.Rmd
usingknitr::rmarkdown
on Nov 23 2024.Last update: 2024-02-09
Started: 2022-07-22
Choice prediction
Rendered fromv05_choice_prediction.Rmd
usingknitr::rmarkdown
on Nov 23 2024.Last update: 2024-02-09
Started: 2022-07-22
Introduction
Rendered fromRprobitB.Rmd
usingknitr::rmarkdown
on Nov 23 2024.Last update: 2024-02-09
Started: 2022-07-22
Model definition
Rendered fromv01_model_definition.Rmd
usingknitr::rmarkdown
on Nov 23 2024.Last update: 2024-02-09
Started: 2022-07-22
Model fitting
Rendered fromv03_model_fitting.Rmd
usingknitr::rmarkdown
on Nov 23 2024.Last update: 2024-02-09
Started: 2022-07-22
Model selection
Rendered fromv06_model_selection.Rmd
usingknitr::rmarkdown
on Nov 23 2024.Last update: 2024-02-09
Started: 2022-07-22
Modeling heterogeneity
Rendered fromv04_modeling_heterogeneity.Rmd
usingknitr::rmarkdown
on Nov 23 2024.Last update: 2024-02-09
Started: 2022-07-22