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bayesm (version 3.0-2)

momMix: 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

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.

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.

References

For further discussion, see Bayesian Statistics and Marketing by Rossi, Allenby and McCulloch, Chapter 5. http://www.perossi.org/home/bsm-1

See Also

rmixGibbs