3 papers
stat.AP2025
Neural posterior inference with state-space models for calibrating ice sheet simulators
Bao Anh Vu, Andrew Zammit-Mangion, David Gunawan +2
Ice sheet models are routinely used to quantify and project an ice sheet's contribution to sea level rise. In order for an ice sheet model to generate realistic projections, its pa…
stat.ME2025
Bayesian copula-based spatial random effects models for inference with complex spatial data
Alan Pearse, David Gunawan, Noel Cressie
In this article, we develop fully Bayesian, copula-based, spatial-statistical models for large, noisy, incomplete, and non-Gaussian spatial data. Our approach includes novel constr…
stat.ME2024
Optimal prediction of positive-valued spatial processes: asymmetric power-divergence loss
Alan R. Pearse, Noel Cressie, David Gunawan
This article studies the use of asymmetric loss functions for the optimal prediction of positive-valued spatial processes. We focus on the family of power-divergence loss functions…