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-release: RprobitB_1.0.0.zip, r-oldrel: RprobitB_1.0.0.zip |
| macOS binaries: | r-release (arm64): RprobitB_1.0.0.tgz, r-oldrel (arm64): RprobitB_1.0.0.tgz, r-release (x86_64): RprobitB_1.0.0.tgz, r-oldrel (x86_64): RprobitB_1.0.0.tgz |
| Old sources: | RprobitB archive |
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