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111 Mon, 8/8/2022, 8:30 AM - 10:20 AM CC-144A
Application and Development of Statistical Methods for Spatio-Temporal Data — Contributed Papers
Section on Bayesian Statistical Science
Chair(s): Yunjiang Ge, University of Maryland College Park
8:35 AM Bayesian Functional Principal Components Analysis Using Relaxed Mutually Orthogonal Processes
James Matuk, Duke University; Amy Herring, Duke University; David Dunson, Duke University
8:50 AM Bayesian Approach to the Mixture of Gaussian Random Fields and Its Application to an fMRI Study
Mozhdeh Forghaniarani, James Madison University; Khalil Shafie, University of Northern Colorado
9:05 AM Spatio-Temporal Log-Gaussian Cox Point Processes via Flexible Gaussian Random Fields
Shuwan Wang, University of Missouri-Columbia; Athanasios Micheas, University of Missouri-Columbia; Christopher K. Wikle, University of Missouri
9:20 AM Using Dirichlet Processes and Machine Learning to Estimate Crash Risk on Roadways
Benjamin K. Dahl, Brigham Young University; Matthew Heaton, BYU; Richard Warr, Brigham Young University; Philip White, BYU; Grant G. Schultz, Brigham Young University; Caleb Dayley, Brigham Young University
9:35 AM Covariate-Guided Bayesian Mixture of Spline Experts for the Analysis of Multivariate Time Series
Haoyi Fu, University of Pittsburgh; Ori Rosen, University of Texas at El Paso; Lu Tang, University of Pittsburgh; Alison Hipwell, University of Pittsburgh; Theodore Huppert, University of Pittsburgh; Kate Keenan, University of Chicago; Robert T Krafty, Emory University
9:50 AM Bayesian Analysis for Spatial Interval-Valued Data
Austin Workman, Baylor University; Joon Jin Song, Baylor Univeristy
10:05 AM Floor Discussion