Imai, Kosuke and David A. van Dyk. (2005). ``MNP: R Package for Fitting the Multinomial Probit Model,'' Journal of Statistical Software, Vol. 14, No. 3 (May), pp. 1-32.

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.

The current version is 2.3-3 (built on 06/23/05) which runs on R 2.0 and higher (see what's new? for the explanation of the changes). The source code is available for download from here or The Comprehensive R Archive Network (CRAN). While both articles and software have been published, I hope to keep making improvements to the software in the future. Your omments and suggestions are welcome.

Regardless of one's eperating system, the software can be installed by typing the following command at R prompt:

> install.packages("MNP")

This will install the latest version from CRAN.

In addition to the Journal of Econometrics article, the accompanying paper (published version; updated version) is available, which includes a brief description of the method implemented in this software as well as a few examples. The software also comes with standard R help files.