ChoiceModelR: Choice Modeling in R

Implements an MCMC algorithm to estimate a hierarchical multinomial logit model with a normal heterogeneity distribution. The algorithm uses a hybrid Gibbs Sampler with a random walk metropolis step for the MNL coefficients for each unit. Dependent variable may be discrete or continuous. Independent variables may be discrete or continuous with optional order constraints. Means of the distribution of heterogeneity can optionally be modeled as a linear function of unit characteristics variables.

Version: 1.3.0
Depends: R (≥ 3.5.0)
Suggests: bayesm, MASS, lattice, Matrix, testthat (≥ 3.0.0)
Published: 2022-05-30
DOI: 10.32614/CRAN.package.ChoiceModelR
Author: Ryan Sermas [aut], John V Colias [ctb, cre], Decision Analyst, Inc. [cph]
Maintainer: John V Colias <jcolias at>
License: GPL (≥ 3)
Copyright: Copyright (C) 2012 Decision Analyst, Inc.; 604 Avenue H East, Arlington, Texas 76011;; 817-640-6166 (ChoiceModelR is a trademark of Decision Analyst, Inc.)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: ChoiceModelR results


Reference manual: ChoiceModelR.pdf


Package source: ChoiceModelR_1.3.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): ChoiceModelR_1.3.0.tgz, r-oldrel (arm64): ChoiceModelR_1.3.0.tgz, r-release (x86_64): ChoiceModelR_1.3.0.tgz, r-oldrel (x86_64): ChoiceModelR_1.3.0.tgz
Old sources: ChoiceModelR archive


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