ChoiceModelR (version 1.2)
Description
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.