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: 1.2
Depends: R (≥ 2.10)
Suggests: bayesm, MASS, lattice, Matrix
Published: 2012-11-20
Author: Ryan Sermas [aut], John V Colias [ctb, cre], Decision Analyst, Inc. [cph]
Maintainer: John V Colias <jcolias at decisionanalyst.com>
License: GPL (≥ 3) (see file LICENSE)
Copyright: (C) 2012 Decision Analyst, Inc. (ChoiceModelR is a trademark of Decision Analyst, Inc.)
URL: http://www.decisionanalyst.com
NeedsCompilation: no
CRAN checks: ChoiceModelR results

Documentation:

Reference manual: ChoiceModelR.pdf

Downloads:

Package source: ChoiceModelR_1.2.tar.gz
Windows binaries: r-devel: ChoiceModelR_1.2.zip, r-release: ChoiceModelR_1.2.zip, r-oldrel: ChoiceModelR_1.2.zip
macOS binaries: r-release (arm64): ChoiceModelR_1.2.tgz, r-release (x86_64): ChoiceModelR_1.2.tgz, r-oldrel: ChoiceModelR_1.2.tgz
Old sources: ChoiceModelR archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ChoiceModelR to link to this page.