sampleM: Update individual level latent class indexes.

In NestedCategBayesImpute: Modeling, Imputing and Generating Synthetic Versions of Nested Categorical Data in the Presence of Impossible Combinations

Description

Update individual level latent class indexes.

Usage

sampleM(phi, data, omega, G, serial,  Parallel)

Arguments

phi	Matrix of posterior samples for the individual-level probabilities for each individual-level variable by each pair of group-level and individual-level latent classes.
data	Input individual-level data.
omega	Matrix of the probabilities for the individual-level latent classes by the group-level latent classes.
G	Household-level latent class indexes.
serial	Vector containing the household index for each individual in the data.
Parallel	Logical indicator for running the function in parallel mode.

Details

Function for obtaining a posterior sample of the individual-level latent class indexes for all individuals in the input data based on the corresponding full conditional distribution.

Value

A vector for the updated values of the individual-level latent class indexes for all individuals in the input data.

Author(s)

Quanli Wang

NestedCategBayesImpute documentation built on May 2, 2019, 3:26 p.m.