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.


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install.packages("ChoiceModelR")

1.2 by John V Colias, 7 years ago


http://www.decisionanalyst.com


Browse source code at https://github.com/cran/ChoiceModelR


Authors: Ryan Sermas , assisted by John V. Colias , Ph.D. <[email protected]>


Documentation:   PDF Manual  


GPL (>= 3) license


Suggests bayesm, MASS, lattice, Matrix


See at CRAN