3 citations · 3 across the 6 of their papers we have counts for
9 papers
Robust Bayesian Predictive Model Selection using Bregman Divergence
Jongwoo Choi, Neil A. Spencer, Dipak K. Dey
Predictive Bayesian model comparison often relies on leave-one-out (LOO) cross-validation criteria such as the expected log predictive density (ELPD). However, model rankings can b…
Robust model selection using likelihood as data
Jongwoo Choi, Neil A. Spencer, Jeffrey W. Miller
Model selection is a central task in statistics, but standard methods are not robust in misspecified settings where the true data-generating process (DGP) is not in the set of cand…
Strong uniform laws of large numbers for bootstrap means and other randomly weighted sums
Neil A. Spencer, Jeffrey W. Miller
This article establishes novel strong uniform laws of large numbers for randomly weighted sums such as bootstrap means. By leveraging recent advances, these results extend previous…
IsoCheck: An R Package to check Isomorphism for Two-level Factorial Designs with Randomization Restrictions
Pratishtha Batra, Neil A. Spencer, Pritam Ranjan
Factorial designs are often used in various industrial and sociological experiments to identify significant factors and factor combinations that may affect the process response. In…
Faster MCMC for Gaussian Latent Position Network Models
Neil A. Spencer, Brian Junker, Tracy M. Sweet
Latent position network models are a versatile tool in network science; applications include clustering entities, controlling for causal confounders, and defining priors over unobs…
A Bayesian Hierarchical Model for Evaluating Forensic Footwear Evidence
Neil A. Spencer, Jared S. Murray
When a latent shoeprint is discovered at a crime scene, forensic analysts inspect it for distinctive patterns of wear such as scratches and holes (known as accidentals) on the sour…
Projective, Sparse, and Learnable Latent Position Network Models
Neil A. Spencer, Cosma Rohilla Shalizi
When modeling network data using a latent position model, it is typical to assume that the nodes' positions are independently and identically distributed. However, this assumption…
Isomorphism Check for Factorial Designs with Randomization Restrictions
Neil A. Spencer, Pritam Ranjan, Franklin Mendivil
Factorial designs with randomization restrictions are often used in industrial experiments when a complete randomization of trials is impractical. In the statistics literature, the…
Space-filling Latin Hypercube Designs based on Randomization Restrictions in Factorial Experiments
Pritam Ranjan, Neil Spencer
Latin hypercube designs (LHDs) with space-filling properties are widely used for emulating computer simulators. Over the last three decades, a wide spectrum of LHDs have been propo…