First, mixture means and shifted-scaled to the original (data) scale, mixture
covariance matrices are scaled to the original (data) scale
(see argument scale in NMixMCMC function
or argument scale.b in GLMM_MCMC).
Possible derived parameters are standard deviations and correlation coefficients.
NMixChainComp(x, relabel = TRUE, param)## S3 method for class 'default':
NMixChainComp(x, relabel = TRUE, param)
## S3 method for class 'NMixMCMC':
NMixChainComp(x, relabel = TRUE,
param = c("w", "mu", "var", "sd", "cor", "Sigma", "Q", "Li"))
## S3 method for class 'GLMM_MCMC':
NMixChainComp(x, relabel = TRUE,
param = c("w_b", "mu_b", "var_b", "sd_b", "cor_b", "Sigma_b", "Q_b", "Li_b"))
NMixMCMC or GLMM_MCMC.NMixRelabel) or whether the chains are to be returned as
originally sampled.NMixMCMC, GLMM_MCMC.