Jonathan R. Bradley
Recent News and Upcoming Events:
New NSF-DMS grant awarded on, “Developing Conjugate Models for Exact MCMC free Bayesian Inference with Application to High-Dimensional Spatio-Temporal Data”.
Pre-prints of recently submitted manuscripts have been made available:
Bradley, JR, and Clinch, M (2023). Generating Independent Replicates Directly from the Posterior Distribution for a Class of Spatial Latent Gaussian Process Models. arXiv preprint: https://arxiv.org/abs/2203.10028
Zhou, S and Bradley, JR (2023). Bayesian Hierarchical Modeling for Bivariate Multiscale Spatial Data with Application to Blood Test Monitoring. arXiv preprint: https://arxiv.org/abs/2310.13580
The following articles have been recently accepted or published:
Saha, S and Bradley, JR (2024+). Incorporating Subsampling into Bayesian Models for High-Dimensional Spatial Data. Bayesian Analysis.
Wu, H and Bradley, JR. (2024). Global-Local Shrinkage Multivariate Logit-Beta Priors for Multiple Response-Type Data. Statistics and Computing. 34: 1-14.
Bradley, JR, Zhou, S, and Liu, X. (2023). Deep Hierarchical Generalized Transformation Models for Spatio-Temporal Data with Discrepancy Errors. Spatial Statistics. 55: 100749.
Simpson, M, Holan, SH, Wikle, CK, Bradley, JR, (2023). Interpolating Population Distributions using Public-use Data: An Application to Income Segregation using American Community Survey Data. Journal of the American Statistical Association. 118: 84 - 96.
Zong, Q, Bradley, JR, (2023). Criterion Constrained Bayesian Hierarchical Models. TEST. 32: 294 - 320.
Xu, Z, Bradley, JR, and Sinha, D (2023). Latent Multivariate Log-Gamma Models for High-Dimensional Multi-Type Responses with Application to Daily Fine Particulate Matter and Mortality Counts. The Annals of Applied Statistics. 17: 1175 - 1198.
Qu, K., Bradley, JR, (2023). Bayesian models for spatial count data with informative finite populations with application to the American community survey. Journal of Applied Statistics. 50: 2701-2716.