MNP is a publicly available R package that fits the Bayesian
multinomial probit model via Markov chain Monte Carlo. The
multinomial probit model is often used to analyze the discrete
choices made by individuals recorded in survey data. Examples where
the multinomial probit model may be useful include the analysis of
product choice by consumers in market research and the analysis of
candidate or party choice by voters in electoral studies. The MNP
software can also fit the model with different choice sets for each
individual, and complete or partial individual choice orderings of
the available alternatives from the choice set. The estimation is
based on the efficient marginal data augmentation algorithm that is
developed by Imai and van Dyk (2005) ``
A Bayesian Analysis of the Multinomial Probit Model
Using the Data Augmentation,''
Journal of
Econometrics, Vol. 124, No. 2 (February), pp. 311-334.