NMixChainComp: Chains for mixture parameters

In mixAK: Multivariate Normal Mixture Models and Mixtures of Generalized Linear Mixed Models Including Model Based Clustering

Chains for mixture parameters

Description

This function returns chains for parameters derived from the (re-labeled) mixture weights, means, covariance matrices.

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.

Usage

NMixChainComp(x, relabel = TRUE, param)

## Default S3 method:
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"))

Arguments

x	an object of class NMixMCMC or GLMM_MCMC.
relabel	a logical argument indicating whether the chains are to be returned with components being re-labeled (see NMixRelabel) or whether the chains are to be returned as originally sampled.
param	a character string indicating which sample is to be returned: w, w_b mixture weights; mu, mu_b mixture means; var, var_b mixture variances; sd, sd_b mixture standard deviations; cor, cor_b correlations derived from the mixture covariance matrices; Sigma, Sigma_b mixture covariance matrices (their lower triangles); Q, Q_b mixture inverted covariance matrices (their lower triangles); Li, Li_b Cholesky factors (their lower triangles) of the mixture inverted covariance matrices.

Value

A matrix with sampled values in rows, parameters in columns.

Author(s)

Arnošt Komárek [e-mail]

See Also

NMixMCMC, GLMM_MCMC.

mixAK documentation built on Sept. 25, 2023, 5:08 p.m.