UpdateLambdaWeighted: Update lambda.

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

Description

Update lambda – the list of matrices of the group-level probabilities for each group-level variable by the group-level latent classes – when the weighting/capping option is used. The weighting options allows capping the number of impossible households to sample and re-weight the multinomial counts within each latent class back to the expected truth. Each matrix in the list is for each group-level variable.

Usage

UpdateLambdaWeighted(HHdata_all, G_all, dHH, FF,struc_weight)

Arguments

HHdata_all	Data matrix for the household-level data from both the original data and the sampled impossible households.
G_all	A vector of the household-level latent class indexes for all households both in the original data and the sampled impossible households.
dHH	A vector containing the number of levels for each household-level variable.
FF	Maximum number of household-level latent classes allowed.
struc_weight	A vector of weights by household sizes used in capping the number of sampled impossible households.

Details

Function for obtaining a posterior sample of lambda when the weighting/capping option is used.

Value

Updated (posterior) value for lambda based on the corresponding full conditional distribution.

Author(s)

Quanli Wang, Olanrewaju Akande

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