Package: MNP
Version: 2.6-4
Date: 2013-06-09
Title: R Package for Fitting the Multinomial Probit Model
Author: Kosuke Imai <kimai@princeton.edu>, David A. van Dyk
<dvd@uci.edu>.
Maintainer: Kosuke Imai <kimai@princeton.edu>
Depends: R (>= 2.1), MASS, utils
Description: 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. Detailed examples are given in Imai
and van Dyk (2005). ``MNP: R Package for Fitting the
Multinomial Probit Model.'' Journal of Statistical Software,
Vol. 14, No. 3 (May), pp. 1-32.
LazyLoad: yes
LazyData: yes
License: GPL (>= 2)
URL: http://imai.princeton.edu/software/MNP.html
Packaged: 2013-06-09 17:45:34 UTC; kimai
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2013-06-09 20:16:42

person("Kosuke", "Imai", , "kimai@princeton.edu", c("aut", "cre")),
person("David", "van Dyk", , "dvandyk@imperial.ac.uk", c("aut")),
person("Jin", "Hubert", , "hubertj@princeton.edu", c("ctb"))
Description: 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 package 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.
<DOI:10.1016/j.jeconom.2004.02.002>  Detailed examples are given in
Imai and van Dyk (2005). ``MNP: R Package for Fitting the Multinomial
Probit Model.''  Journal of Statistical Software, Vol. 14, No. 3 (May),