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290 Wed, 8/11/2021, 1:30 PM - 3:20 PM Virtual
Advanced Bayesian Topics (Part 3) — Contributed Speed
Section on Bayesian Statistical Science
Chair(s): Yuexi Wang, University of Chicago
1:35 PM Bayesian Nonparametric Quantile Regression with Multiple Proxy Variables
Dongyoung Go, Yonsei university; Jongho Im, Yonsei university; Ickhoon Jin, Yonsei university
1:40 PM A Novel Finite Mixture Model to Cluster Dynamic Latent Ability in Item Response Theory Models
Jingyu Sun, University of Connecticut, Department of Statistics; Xiaojing Wang, University of Connecticut
1:45 PM Bayesian Functional Partial Membership Model
Nicholas Marco, University of California, Los Angeles; donatello telesca, UCLA
1:50 PM A Simulation-Based Comparison of Bayesian Computing Platforms in R
Evan Miyakawa, Baylor University
1:55 PM An Empirical Bayes Approach to Estimating Dynamic Models of Co-Regulated Gene Expression
Sara Venkatraman, Cornell University, Department of Statistics and Data Science; Sumanta Basu, Cornell University ; Sofie Delbare, Cornell University, Department of Statistics and Data Science; Myung Hee Lee, Weill Cornell Medical College, Department of Medicine; Martin Wells, Cornell University, Department of Statistics and Data Science
2:00 PM Geographic and Racial Disparities in the Incidence of Low Birthweight in Pennsylvania
Guangzi Song, Drexel Univerisity; Harrison Quick, Drexel Univerisity; Loni Tabb, Drexel Univerisity
2:05 PM Normalized Power Prior Bayesian Analysis
Keying Ye, The University of Texas at San Antonio; Zifei Han, University of International Business and Economics; Yuyan Duan, Novartis Inc.; Tianyu Bai, FDA
2:10 PM Bayesian Analysis of Sparse Multivariate Matched Proportions
Mark Meyer, Georgetown University; Tong John Li, Georgetown University; Katherine Hobbs Knutson, Partners Healthcare
2:15 PM Spatial Meshing for General Bayesian Multivariate Models
Michele Peruzzi, Duke University; David Dunson, Duke University
2:20 PM Exchangeable Bayesian Matrix-Variate Hierarchical Clustering with Parallel Computation
Hsin-Hsiung Huang, University of Central Florida
2:30 PM Bayesian Estimation of Constrained Mean-Covariance of Normal Distribution
Anupam Kundu, Texas A&M University; Mohsen Pourahmadi, Texas A&M University
2:35 PM WITHDRAWN: Causal BART Mixture Model for Estimating Heterogeneous Treatment Effects
Omar Chavez, University of Texas at Austin, Department of Statistics and Data Sciences; Sinead Williamson, University of Texas at Austin, Department of Statistics and Data Sciences; Michael J. Daniels, University of Florida
2:40 PM Bayesian Finite Mixture Regression Models with Cluster-Specific Variable Selection
Zhen Wang, University of Iowa; Aixin Tan, University of Iowa
2:45 PM Bayesian Latent Class Model for Predicting Gestational Age in Health Administrative Data
Shuang Wang, University of Rhode Island; Gavino Puggioni, University of Rhode Island; Xuerong Wen, University of Rhode Island
2:50 PM Using Subject-Level Covariate Information in Bayesian Mixture Models for Basket Trials
Sneha Govande, Florida State University; Elizabeth H. Slate, Florida State University
2:55 PM Sparse Bayesian High-Dimensional Vector Autoregressions
Rui Meng, Lawrence Berkeley National Laboratory
3:00 PM Semiparametric Bayesian Regression Analysis of Multi-Typed Matrix-Variate Responses
Inkoo Lee, Rice University; Dipankar Bandyopadhyay, Virginia Commonwealth University
3:05 PM A Modified Cauchy-Net for Anomaly Detection
Sierra Merkes, Virginia Tech; Scotland Leman, Virginia Tech; Eric Smith, Virgina Tech
3:10 PM State-Level Estimation by Combining Information from Two Health Surveys
Diba Khan, National Center for Health Statistics, Centers for Disease Control and Prevention; John R Pleis, National Center for Health Statistics, Centers for Disease Control and Prevention; Bill Cai, NCHS; Benmei Liu, National Cancer Institute; Eric J. Feuer, National Cancer Institute; Van Parsons, CDC; Yulei He, US Centers for Disease Control and Prevention; Machell Town, Centers for Disease Control and Prevention
3:15 PM WITHDRAWN An Interpretable and Identifiable Approach to Age Period Cohort Modeling
Sean Ryan, Cornell University; David S Matteson, Cornell University