An object of this class holds estimates of each parameter at each iteration of the MCMC simulation.

`theta`

means of each batch and component

`sigma2`

variances of each batch and component

`pi`

mixture probabilities

`mu`

overall mean in a marginal. In batch model, averaged across batches

`tau2`

overall variance in a marginal model. In a batch model, weighted average by precision across batches.

`nu.0`

shape parameter for sigma.2 distribution

`sigma2.0`

rate parameter for sigma.2 distribution

`logprior`

log likelihood of prior.

`loglik`

log likelihood.

`zfreq`

table of z.

`z`

latent variables

CNPBayes documentation built on May 2, 2018, 3:57 a.m.

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