ChoiceModelR (1.2)
Choice Modeling in R.
http://www.decisionanalyst.com
http://cran.r-project.org/web/packages/ChoiceModelR
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.
Maintainer:
John V Colias
Author(s): Ryan Sermas, assisted by John V. Colias, Ph.D. <DecisionAnalystR@decisionanalyst.com>
License: GPL (>= 3)
Uses: Matrix, bayesm, lattice, MASS
Released 6 months ago.
2 previous versions
- ChoiceModelR_1.1. Released about 1 year ago.
- ChoiceModelR_1.0. Released over 1 year ago.
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