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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), Dirichlet Process Prior Density
Estimation with normal base, 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 Multinomial Logits with a Dirichlet Process
prior and covariates, Hierarchical Negative Binomial Regression Models,
Bayesian analysis of choice-based conjoint data, Bayesian treatment of linear
instrumental variables models, and Analysis of Multivariate Ordinal survey
data with scale usage heterogeneity (as in Rossi et al, JASA (01)).
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