2 citations · 2 across the 1 of their papers we have counts for
3 papers
stat.ME2020★ 2 cited
Computationally Efficient Bayesian Unit-Level Models for Non-Gaussian Data Under Informative Sampling
Paul A. Parker, Scott H. Holan, Ryan Janicki
Statistical estimates from survey samples have traditionally been obtained via design-based estimators. In many cases, these estimators tend to work well for quantities such as pop…
stat.ME2019
Conjugate Bayesian Unit-level Modeling of Count Data Under Informative Sampling Designs
Paul A. Parker, Scott H. Holan, Ryan Janicki
Unit-level models for survey data offer many advantages over their area-level counterparts, such as potential for more precise estimates and a natural benchmarking property. Howeve…
stat.ME2019
Unit Level Modeling of Survey Data for Small Area Estimation Under Informative Sampling: A Comprehensive Overview with Extensions
Paul A. Parker, Ryan Janicki, Scott H. Holan
Model-based small area estimation is frequently used in conjunction with survey data in order to establish estimates for under-sampled or unsampled geographies. These models can be…