3 papers
stat.ME2026
A multi-stage Bayesian approach to fit spatial point process models
Rachael Ren, Mevin B. Hooten, Toryn L. J. Schafer +4
Spatial point process (SPP) models are commonly used to analyze point pattern data in many fields, including presence-only data in ecology. Existing exact Bayesian methods for fitt…
stat.AP2025
Dyadic Flow Models for Nonstationary Gene Flow in Landscape Genomics
Michael R. Schwob, Nicholas M. Calzada, Justin J. Van Ee +6
The field of landscape genomics aims to infer how landscape features affect gene flow across space. Most landscape genomic frameworks assume the isolation-by-distance and isolation…
stat.ME2025
Spatial Hyperspheric Models for Compositional Data
Michael R. Schwob, Mevin B. Hooten, Nicholas M. Calzada +1
Compositional observations are an increasingly prevalent data source in spatial statistics. Analysis of such data is typically done on log-ratio transformations or via Dirichlet re…