rbiNormGibbs

initial value of parameter on x axis (def: 2)

initx

initial value of parameter on y axis (def: -2)

inity

burnin

<code>rbiNormGibbs</code> implements a Gibbs Sampler for the bivariate normal distribution.
  Intermediate moves are shown and the output is contrasted with the iid sampler. i
  This function is designed for illustrative/teaching purposes.

distribution

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 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. 

Peter Rossi

bayesm

Bayesian Inference for Marketing/Micro-econometrics

rbiNormGibbs function

<ul><li>bayes</li><li>Gibbs Sampling</li><li>MCMC</li><li>normal distribution</li></ul>

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rbiNormGibbs: Illustrate Bivariate Normal Gibbs Sampler

Description

Usage

Arguments

Value

concept

Details

References

Examples