UpdateOmegaWeighted: Update omega and v.

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

Description

Update omega – the matrix of the probabilities for the individual-level latent classes by the group-level latent classes – and v – the matrix of the beta-distributed variables in the stick breaking representation of the individual-level latent classes 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.

Usage

UpdateOmegaWeighted(beta, M_all, FF, SS, struc_weight)

Arguments

beta	Concentration parameter in the Dirichlet process for the individual-level latent classes. Currently, this is assumed to be the same within all group-level classes.
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.
struc_weight	A vector of weights by household sizes used in capping the number of sampled impossible households.

Value

A list containing the updated (posterior) values for omega and v based on the corresponding full conditional distributions.

Author(s)

Quanli Wang, Olanrewaju Akande

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