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05/22/2023
Incorporating Subsampling into Bayesian Models for High-Dimensional Spatial Data
Additive spatial statistical models with weakly stationary process assum...
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11/17/2022
Bayesian Hierarchical Models For Multi-type Survey Data Using Spatially Correlated Covariates Measured With Error
We introduce Bayesian hierarchical models for predicting high-dimensiona...
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03/18/2022
Efficiently Generating Independent Samples Directly from the Posterior Distribution for a Large Class of Bayesian Generalized Linear Mixed Effects Models
Markov chain Monte Carlo (MCMC) is an all-purpose tool that allows one t...
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04/20/2021
Constrained Bayesian Hierarchical Models for Gaussian Data: A Model Selection Criterion Approach
Consider the setting where there are B>1 candidate statistical models, a...
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02/23/2020
Bayesian analysis of count-valued, binary-valued, and continuous-valued responses using unknown transformations
Consider the situation where an analyst has a Bayesian statistical model...
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01/17/2020
Bayesian Inference for Big Spatial Data Using Non-stationary Spectral Simulation
It is increasingly understood that the assumption of stationarity is unr...
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12/10/2019
What is the best predictor that you can compute in five minutes using a given Bayesian hierarchical model?
The goal of this paper is to provide a way for statisticians to answer t...
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09/05/2019
Latent Multivariate Log-Gamma Models for High-Dimensional Multi-Type Responses with Application to Daily Fine Particulate Matter and Mortality Counts
Tracking and estimating Daily Fine Particulate Matter (PM2.5) is very im...
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04/27/2019
An R Package for Spatio-Temporal Change of Support
Spatio-temporal change of support (STCOS) methods are designed for stati...
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12/09/2018
Spatio-Temporal Models for Big Multinomial Data using the Conditional Multivariate Logit-Beta Distribution
We introduce a Bayesian approach for analyzing high-dimensional multinom...
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02/07/2018
