2 citations · 3 across the 5 of their papers we have counts for
5 papers
Simulation-based Calibration of Uncertainty Intervals under Approximate Bayesian Estimation
Terrance D. Savitsky, Julie Gershunskaya
The mean field variational Bayes (VB) algorithm implemented in Stan is relatively fast and efficient, making it feasible to produce model-estimated official statistics on a rapid t…
Review of Quasi-Randomization Approaches for Estimation from Non-probability Samples
Vladislav Beresovsky, Julie Gershunskaya, Terrance D. Savitsky
The recent proliferation of computers and the internet have opened new opportunities for collecting and processing data. However, such data are often obtained without a well-planne…
Joint Point and Variance Estimation under a Hierarchical Bayesian model for Survey Count Data
Terrance D. Savitsky, Julie Gershunskaya, Mark Crankshaw
We propose a novel Bayesian framework for the joint modeling of survey point and variance estimates for count data. The approach incorporates an induced prior distribution on the m…
Methods for Combining Probability and Nonprobability Samples Under Unknown Overlaps
Terrance D. Savitsky, Matthew R. Williams, Julie Gershunskaya +2
Nonprobability (convenience) samples are increasingly sought to reduce the estimation variance for one or more population variables of interest that are estimated using a randomize…
Methods for Combining Probability and Nonprobability Samples Under Unknown Overlaps
Terrance D. Savitsky, Matthew R. Williams, Julie Gershunskaya +2
Nonprobability (convenience) samples are increasingly sought to stabilize estimations for one or more population variables of interest that are performed using a randomized survey…