91 citations · 187 across the 22 of their papers we have counts for
23 papers
Restricted Spatial Regression is Reasonable Statistical Practice: Clarifications, Interpretations, and New Developments
Jonathan R. Bradley
The spatial linear mixed model (SLMM) consists of fixed and spatial random effects that may be linearly dependent. Partially motivated as a means to address potential issues with c…
A Criterion for Aggregation Error for Multivariate Spatial Data
Ranadeep Daw, Jonathan R. Bradley, Christopher K. Wikle +1
The criterion for aggregation error (CAGE) is an important metric that aims to measure errors that arise in multiscale (or multi-resolution) spatial data, referred to as the modifi…
Incorporating Subsampling into Bayesian Models for High-Dimensional Spatial Data
Sudipto Saha, Jonathan R. Bradley
Additive spatial statistical models with weakly stationary process assumptions have become standard in spatial statistics. However, one disadvantage of such models is the computati…
Bayesian Hierarchical Models For Multi-type Survey Data Using Spatially Correlated Covariates Measured With Error
Saikat Nandy, Scott H. Holan, Jonathan R. Bradley +1
We introduce Bayesian hierarchical models for predicting high-dimensional tabular survey data which can be distributed from one or multiple classes of distributions (e.g., Gaussian…
Generating Independent Replicates Directly from the Posterior Distribution for a Class of Spatial Latent Gaussian Process Models
Jonathan R. Bradley, Madelyn Clinch
Markov chain Monte Carlo (MCMC) allows one to generate dependent replicates from a posterior distribution for effectively any Bayesian hierarchical model. However, MCMC can produce…
Constrained Bayesian Hierarchical Models for Gaussian Data: A Model Selection Criterion Approach
Qingying Zong, Jonathan R. Bradley
Consider the setting where there are B>1 candidate statistical models, and one is interested in model selection. Two common approaches to solve this problem are to select a single…