UpdatePhiWeighted: Update phi.

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

Description

Update phi – the 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 – 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.

Usage

UpdatePhiWeighted(data, M_all, FF, SS, d, maxd, struc_weight)

Arguments

data	Data matrix for the individual-level data from both the original data and the sampled impossible households.
M_all	A vector of both the household-level and individual-level latent class indexes for all households both in the original data and the sampled impossible households.
FF	Maximum number of household-level latent classes allowed.
SS	Maximum number of individual-level latent classes allowed.
d	A vector for the number of levels of each individual-level variable.
maxd	Maximum value in d.
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 phi when the weighting/capping option is used.

Value

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

Author(s)

Quanli Wang, Olanrewaju Akande

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