3 papers
math.ST2026
Bayesian Multiplicity Correction in the Probabilistic Forward Stepwise Framework
Andrew Womack, Daniel Taylor-Rodriguez
We develop a natural Bayesian multiplicity-correcting prior distribution within the probabilistic forward stepwise representation of model space priors for regression problems. The…
stat.ME2025
Clustering the Nearest Neighbor Gaussian Process
Ashlynn Crisp, Daniel Taylor-Rodriguez, Andrew O. Finley
Gaussian processes are ubiquitous as the primary tool for modeling spatial data. However, the Gaussian process is limited by its cost, making direct parameter fi…
stat.ME2025
The matryoshka doll prior: principled multiplicity correction in Bayesian model comparison
Andrew J Womack, Daniel Taylor-Rodriguez, Claudio Fuentes
This paper introduces a general and principled construction of model space priors with a focus on regression problems. The proposed formulation regards each model as a `local` null…