RprobitB: Bayes Estimation of Latent Class Mixed Multinomial Probit Models

Fitting latent class mixed multinomial probit (LCMMNP) models to simulated or empirical choice data via Bayesian estimation. The number of latent classes can be updated within the algorithm on a weight-based strategy. For a reference on the method see Oelschlaeger and Bauer (2021) <https://trid.trb.org/view/1759753>.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: Rcpp, mvtnorm, viridis
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, mlogit, vdiffr, testthat (≥ 3.0.0)
Published: 2021-11-12
Author: Lennart Oelschläger [aut, cre], Dietmar Bauer [aut], Sebastian Büscher [ctb], Manuel Batram [ctb]
Maintainer: Lennart Oelschläger <lennart.oelschlaeger at uni-bielefeld.de>
License: GPL-3
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: RprobitB results


Reference manual: RprobitB.pdf
Vignettes: Data management
Introduction to RprobitB and model formulation
Model fitting


Package source: RprobitB_1.0.0.tar.gz
Windows binaries: r-devel: RprobitB_1.0.0.zip, r-devel-UCRT: RprobitB_1.0.0.zip, r-release: RprobitB_1.0.0.zip, r-oldrel: RprobitB_1.0.0.zip
macOS binaries: r-release (arm64): RprobitB_1.0.0.tgz, r-release (x86_64): RprobitB_1.0.0.tgz, r-oldrel: RprobitB_1.0.0.tgz
Old sources: RprobitB archive


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