momMix {bayesm} | R Documentation

## Compute Posterior Expectation of Normal Mixture Model Moments

### Description

`momMix` averages the moments of a normal mixture model over MCMC draws.

### Usage

    momMix(probdraw, compdraw)

### Arguments

`probdraw` | R x ncomp list of draws of mixture probs
`compdraw` | list of length R of draws of mixture component moments

### Details

R is the number of MCMC draws in argument list above.
ncomp is the number of mixture components fitted.
compdraw is a list of lists of lists with mixture components.
compdraw[[i]] is ith draw.
compdraw[[i]][[j]][[1]] is the mean parameter vector for the jth component, ith MCMC draw.
compdraw[[i]][[j]][[2]] is the UL decomposition of Sigma^{-1} for the jth component, ith MCMC draw.

### Value

a list of the following items ...

`mu` | Posterior Expectation of Mean
`sigma` | Posterior Expecation of Covariance Matrix
`sd` | Posterior Expectation of Vector of Standard Deviations
`corr` | Posterior Expectation of Correlation Matrix

### Warning

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

### Author(s)

Peter Rossi, Graduate School of Business, University of Chicago, Peter.Rossi@ChicagoGsb.edu.

### References

For further discussion, see Bayesian Statistics and Marketing by Rossi, Allenby and McCulloch, Chapter 5.
http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html

### See Also

`rmixGibbs`

[Package bayesm version 2.0-8 Index]