NMixMCMC function. The summary also takes into account
possible scaling and shifting of the data (see argument scale
in NMixMCMC function). Note that even though the mixture components are re-labeled before the
summary is computed to achieve identifiability, posterior summaries of
individual mixture means and variances are not always the quantity we
would like to see. For density estimation, usually posterior
predictive density (NMixPredDensMarg,
NMixPredDensJoint2) is usually the right stuff one
should be interested in.
NMixSummComp(x)NMixMCMCx. The rest is printed on output device.NMixMCMC.