Package: Rprobit 1.0.0

Rprobit: Estimation of Multinomial Probit Models

Estimation of multinomial probit models based on panel data. It uses the full likelihood as well as the MaCML approach. The multinomial Gaussian CDF is approximated using the Solow-Joe method.

Authors:Dietmar Bauer [aut, cre], Manuel Batram [aut], Sebastian Büscher [aut], Lennart Oelschläger [aut], Thanh Thao Bui [aut]

Rprobit_1.0.0.tar.gz
Rprobit_1.0.0.zip(r-4.7-x86_64)Rprobit_1.0.0.zip(r-4.7-arm64)Rprobit_1.0.0.zip(r-4.6-x86_64)Rprobit_1.0.0.zip(r-4.6-arm64)Rprobit_1.0.0.zip(r-4.5-x86_64)
Rprobit_1.0.0.tgz(r-4.6-x86_64)Rprobit_1.0.0.tgz(r-4.6-arm64)Rprobit_1.0.0.tgz(r-4.5-x86_64)Rprobit_1.0.0.tgz(r-4.5-arm64)
Rprobit_1.0.0.tar.gz(r-4.7-arm64)Rprobit_1.0.0.tar.gz(r-4.7-x86_64)Rprobit_1.0.0.tar.gz(r-4.6-arm64)Rprobit_1.0.0.tar.gz(r-4.6-x86_64)
Rprobit_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
Rprobit/json (API)

# Install 'Rprobit' in R:
install.packages('Rprobit', repos = c('https://dbauer72.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

cpp

2.70 score 4 scripts 10 exports 133 dependencies

Last updated from:063898a3d3. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK243
linux-devel-x86_64OK231
source / vignettesOK605
linux-release-arm64OK176
linux-release-x86_64OK180
macos-release-arm64OK320
macos-release-x86_64OK432
macos-oldrel-arm64OK301
macos-oldrel-x86_64OK429
windows-devel-arm64OK430
windows-devel-x86_64OK220
windows-release-arm64OK515
windows-release-x86_64OK333
windows-oldrel-x86_64OK344
wasm-releaseOK161

Exports:choice_datafitll_cmlmodpred_probit_approxRprobitsetupSJSJ_gradSJ_hess

Dependencies:abindaskpassbackportsbase64encbayesplotBBbbmlebdsmatrixbenchmarkmebenchmarkmeDatabootbridgesamplingbrioBrobdingnagbslibcachemcallrcheckmatechoicedataclicodacodetoolsContourFunctionscpp11crayoncubaturecurldescdiffobjdigestdistributionaldoParalleldplyrevaluatefarverfastmapfontawesomeforeachFormulafsfuturefuture.applygenericsGenOrdggdistggplot2ggridgesglobalsglueGPArotationgtablehighrhtmltoolshttrisobanditeratorsjquerylibjsonliteknitrlabelinglatticelbfgsb3clhslifecyclelistenvloomagrittrMASSMatrixmatrixStatsmemoisemimemnormtmvtnormnleqslvnlmenumDerivoeliopenssloptimizeRotelparallellypillarpkgbuildpkgconfigpkgloadplyrposteriorpracmapraiseprocessxprogressrpspsychpurrrquadprogR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreshape2rlangrmarkdownRprobitBrprojrootS7sassscalesSimMultiCorrDatastringistringrsystensorATestFunctionstestthattibbletidyrtidyselecttinytextriangleucminfutf8vctrsVGAMviridisLitewaldowithrxfunyaml

Data and Simulation
Data | Example: Mode Choice | The choice_data Object | Example 2: A Wide Data Set | Linking Data with a Model | Simulation | Simulating a Full Data Set Including the Characteristics | Redrawing Choices | References
Rendered fromdata_simulation.Rmdusingknitr::rmarkdown

Last update: 2026-11-07
Started: 2026-11-07

Introduction
Outline of the Vignettes | License | Contact | Installing Rprobit | Typical Workflow
Rendered fromIntroduction.Rmdusingknitr::rmarkdown

Last update: 2026-11-07
Started: 2026-11-07

Model Definition
The Multinomial Probit Model | Model Formula | Example: Choice of a New Car | Identifiability | Model Unification | Representing Type II Variables as a Set of Type I Variables | Representing Type III Variables as a Set of Type I Variables | Choice Behavior Heterogeneity | Model Parameterization | Model Object | Working with the Model Objects | References
Rendered frommodel_definition.Rmdusingknitr::rmarkdown

Last update: 2026-11-07
Started: 2026-11-07

Model Fitting
Types of CML | Optimization Parameters | Initial Estimates | Example | Model Diagnostics | References
Rendered frommodel_fitting.Rmdusingknitr::rmarkdown

Last update: 2026-11-07
Started: 2026-11-07

Modeling Setup
The setup() Function | Setup Example for Empirical Choice Data in Wide Format | Setup Example for Empirical Choice Data in Long Format | Setup Example for Simulated Choice Data | References
Rendered frommodeling_setup.Rmdusingknitr::rmarkdown

Last update: 2026-11-07
Started: 2026-11-07

Readme and manuals

Help Manual

Help pageTopics
Calculate Approximated Probit Choice Probabilitycalc_choice_probs
Choice Datachoice_data
Fit an Rprobit Object Without Modifying It in Placefit
Initialize nMMNP Model Parametersinitialize
Calculate Approximated Composite Marginal or Full Probit Log-Likelihoodll_cml
Model Specificationmod
Predict Probit Choice Probabilitiespred_probit_approx
Rprobit ObjectRprobit
Rprobit MethodsAIC.Rprobit BIC.Rprobit coef.Rprobit confint.Rprobit logLik.Rprobit plot.Rprobit predict.Rprobit print.summary.Rprobit residuals.Rprobit Rprobit-methods summary.Rprobit vcov.Rprobit
Setup for Estimation of Multinomial Probit Modelssetup
Solow-Joe approximationSJ SJ_grad SJ_hess