Package: bayesm
Version: 2.1-2
Date: 2007-03-15
Title: Bayesian Inference for Marketing/Micro-econometrics
Author: Peter Rossi <peter.rossi@ChicagoGsb.edu>, Rob McCulloch
        <robert.mcculloch@ChicagoGsb.edu>.
Maintainer: Peter Rossi <peter.rossi@chicagosb.edu>
Depends: R (>= 2.2.0)
Description: bayesm covers many important models used in marketing and
        micro-econometrics applications. The package includes: Bayes
        Regression (univariate or multivariate dep var), Bayes
        Seemingly Unrelated Regression (SUR), Binary and Ordinal
        Probit, Multinomial Logit (MNL) and Multinomial Probit (MNP),
        Multivariate Probit, Negative Binomial (Poisson) Regression,
        Multivariate Mixtures of Normals (including clustering),
        Hierarchical Linear Models with normal prior and covariates,
        Hierarchical Linear Models with a mixture of normals prior and
        covariates, Hierarchical Multinomial Logits with a mixture of
        normals prior and covariates, Hierarchical Negative Binomial
        Regression Models, Bayesian analysis of choice-based conjoint
        data, Bayesian treatment of linear instrumental variables
        models, and Analyis of Multivariate Ordinal survey data with
        scale usage heterogeneity (as in Rossi et al, JASA (01)). For
        further reference, consult our book, Bayesian Statistics and
        Marketing by Rossi, Allenby and McCulloch.
License: GPL (version 2 or later)
URL: http://faculty.chicagogsb.edu/peter.rossi/research/bsm.html
Packaged: Thu Mar 15 17:10:45 2007; per
Built: R 2.4.1; x86_64-pc-linux-gnu; 2007-04-29 02:09:39; unix
