rmixGibbs

prior mean for mean vector of each norm comp

Bbar

prior location matrix for covariance priro

component identities for each observation -- "indicators"

list of components for the normal mixture

comps

<code>rmixGibbs</code> makes one draw using the Gibbs Sampler for a mixture of multivariate normals.

multivariate

bayesm covers many important models used
  in marketing and micro-econometrics applications. 
  The package includes:
  Bayes Regression (univariate or multivariate dep var),
  Multinomial Logit (MNL) and Multinomial Probit (MNP),
  Multivariate Probit,
  Negative Binomial Regression,
  Multivariate Mixtures of Normals,
  Hierarchical Linear Models with normal prior and covariates,
  Hierarchical Multinomial Logits with 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 Allenby, McCulloch and Rossi. 

Peter Rossi

bayesm

Bayesian Inference for Marketing/Micro-econometrics

rmixGibbs function

This routine is a utility routine that does <strong>not</strong> check the
  input arguments for proper dimensions and type.

rmixGibbs: Gibbs Sampler for Normal Mixtures w/o Error Checking

Description

Usage

Arguments

Value

Warning

Details

References

See Also