91 citations · 257 across the 49 of their papers we have counts for
38 papers · 1 filter
Nonprobability Samples for Small Area Estimation: A Review and Comparative Simulation Study
Sho Kawano, Daniel Vedensky, Qianyu Dong +5
Nonprobability samples (NPS) are attractive because they are less costly to collect, can provide substantially larger sample sizes, and may reach populations that traditional proba…
Bayesian Modeling of Gibbs Point Processes via Basis Function Expansions
Christopher Hassett, Athanasios C. Micheas, Scott H. Holan +1
We present a hierarchical Bayesian framework for non-homogeneous pairwise interaction Gibbs point process models, where the global and local effect functions are modeled via basis…
Scalable Joint Modeling of Dependent Multi-Type Survey Data for Small Area Estimation
Zewei Kong, Paul A. Parker, Scott H. Holan
We develop a Bayesian area-level small area estimation framework that jointly models binomial and Gaussian survey responses through shared spatial random effects. This work is moti…
A Bayesian Approach to Unit-level Dependent Multi-type Survey Data
Zewei Kong, Paul A. Parker, Jonathan R. Bradley +1
The American Community Survey (ACS) Public Use Microdata Sample (PUMS) provides access to a wide range of unit-level survey data consisting of correlated Gaussian and binomial dist…
Bayesian Unit-level Modeling of Categorical Survey Data with a Longitudinal Design
Daniel Vedensky, Paul A. Parker, Scott H. Holan
Categorical response data are ubiquitous in complex survey applications, yet few methods model the dependence across different outcome categories when the response is ordinal. Like…
Bayesian Methods to Improve The Accuracy of Differentially Private Measurements of Constrained Parameters
Ryan Janicki, Scott H. Holan, Kyle M. Irimata +2
Formal disclosure avoidance techniques are necessary to ensure that published data can not be used to identify information about individuals. The addition of statistical noise to u…