RprobitB: Bayes Estimation of Latent Class Mixed Multinomial Probit Models

Fitting latent class mixed multinomial probit (LCMMNP) models to simulated or empirical data. Estimation takes place in a Bayesian framework using a Gibbs sampler. The number of latent classes can be updated within the algorithm on a weight-based strategy. For a reference on the method see Oelschl\"ager and Bauer (2021) <https://trid.trb.org/view/1759753>.

Version: 0.1.1
Depends: R (≥ 3.5.0)
Imports: Rcpp, mvtnorm, viridis
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
Published: 2021-05-25
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: Introduction to RprobitB
Package source: RprobitB_0.1.1.tar.gz
Windows binaries: r-devel: RprobitB_0.1.1.zip, r-devel-UCRT: RprobitB_0.1.1.zip, r-release: RprobitB_0.1.1.zip, r-oldrel: RprobitB_0.1.1.zip
macOS binaries: r-release (arm64): RprobitB_0.1.1.tgz, r-release (x86_64): RprobitB_0.1.1.tgz, r-oldrel: RprobitB_0.1.1.tgz
Old sources: RprobitB archive


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