66 citations · 189 across the 22 of their papers we have counts for
3 papers · 1 filter
Dirichlet Process Mixture Models for Modeling and Generating Synthetic Versions of Nested Categorical Data
Jingchen Hu, Jerome P. Reiter, Quanli Wang
We present a Bayesian model for estimating the joint distribution of multivariate categorical data when units are nested within groups. Such data arise frequently in social science…
Multiple Imputation of Missing Categorical and Continuous Values via Bayesian Mixture Models with Local Dependence
Jared S. Murray, Jerome P. Reiter
We present a nonparametric Bayesian joint model for multivariate continuous and categorical variables, with the intention of developing a flexible engine for multiple imputation of…
Bayesian Marked Point Process Modeling for Generating Fully Synthetic Public Use Data with Point-Referenced Geography
Harrison Quick, Scott H. Holan, Christopher K. Wikle +1
Many data stewards collect confidential data that include fine geography. When sharing these data with others, data stewards strive to disseminate data that are informative for a w…