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.

Author
Ryan Sermas, assisted by John V. Colias, Ph.D. <DecisionAnalystR@decisionanalyst.com>
Date of publication
2012-11-20 23:23:09
Maintainer
John V Colias <jcolias@decisionanalyst.com>
License
GPL (>= 3)
Version
1.2
URLs

View on CRAN

Man pages

choicemodelr
Choice Modeling in R
ChoiceModelR-package
Choice Modeling in R
datar
Arificial (Simulated) Choice Data for choicemodelr
sharedatar
Arificial (Simulated) Fractional Choice Data for choicemodelr
truebetas
True betas used to simulate data in the choice data set named...

Files in this package

ChoiceModelR
ChoiceModelR/MD5
ChoiceModelR/R
ChoiceModelR/R/ChoiceModelR.R
ChoiceModelR/NAMESPACE
ChoiceModelR/man
ChoiceModelR/man/truebetas.Rd
ChoiceModelR/man/sharedatar.Rd
ChoiceModelR/man/datar.Rd
ChoiceModelR/man/choicemodelr.Rd
ChoiceModelR/man/ChoiceModelR-package.Rd
ChoiceModelR/LICENSE
ChoiceModelR/inst
ChoiceModelR/inst/doc
ChoiceModelR/inst/doc/ChoiceModelR-manual.pdf
ChoiceModelR/INDEX
ChoiceModelR/DESCRIPTION
ChoiceModelR/data
ChoiceModelR/data/truebetas.rda
ChoiceModelR/data/sharedatar.rda
ChoiceModelR/data/datar.rda