3 papers
stat.ME2026
Bayesian Analysis Using a Constrained Mixture of Normal-Inverse-Gamma Models
Madelyn Clinch, Jonathan R. Bradley, Andrés F. Barrientos +1
Gaussian mixtures of regressions are commonly implemented via a Gibbs sampler. This Markov chain Monte Carlo (MCMC) algorithm can be computationally burdensome because of the need…
stat.ME2025
Bayesian Inference for Spatial-Temporal Non-Gaussian Data Using Predictive Stacking
Soumyakanti Pan, Lu Zhang, Jonathan R. Bradley +1
Analysing non-Gaussian spatial-temporal data requires introducing spatial as well as temporal dependence in generalised linear models through the link function of an exponential fa…
stat.ME2024
Markov Random Fields with Proximity Constraints for Spatial Data
Sudipto Saha, Jonathan R. Bradley
The conditional autoregressive (CAR) model, simultaneous autoregressive (SAR) model, and its variants have become the predominant strategies for modeling regional or areal-referenc…