GetMCZ: Convert disjointed structrual zeros to a dataframe, using the...

In NPBayesImputeCat: Non-Parametric Bayesian Multiple Imputation for Categorical Data

Convert disjointed structrual zeros to a dataframe, using the same setting from original structrual zero data.

Description

This is a utility function to convert the disjointed structrual zero matrix to a dataframe. This function will be implemented as a RCPP internal function later on.

Usage

GetMCZ(dest, from, mcz, cols = 1:NCOL(from))

Arguments

dest	the output data matrix for disjointed structrual zeros.
from	the original input dataframe.
mcz	the original input dataframe for structrual zeros.
cols	optinal. Always use default for now.

Value

The returned dataframe object for disjointed structrual zeros.

References

Manrique-Vallier, D. and Reiter, J.P. (2013), "Bayesian Estimation of Discrete Multivariate Latent Structure Models with Structural Zeros", JCGS.

Si, Y. and Reiter, J.P. (2013), "Nonparametric Bayesian multiple imputation for incomplete categorical variables in large-scale assessment surveys", Journal of Educational and Behavioral Statistics, 38, 499 - 521

Manrique-Vallier, D. and Reiter, J.P. (2014), "Bayesian Multiple Imputation for Large-Scale Categorical Data with Structural Zeros", Survey Methodology.

NPBayesImputeCat documentation built on Oct. 3, 2022, 5:05 p.m.