Package: MNP
Version: 2.6-2
Date: 2010-10-27
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: 2010-10-28 02:53:15 UTC; kimai
Repository: CRAN
Date/Publication: 2010-10-28 08:26:49

Package: MNP
Version: 2.6-3
Date: 2011-12-06
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: 2011-12-07 01:33:35 UTC; kimai
Repository: CRAN
Date/Publication: 2011-12-07 10:13:42