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310 !
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Wed, 8/5/2020,
10:00 AM -
11:50 AM
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Virtual
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Modern Approaches to Small Area Estimation with Spatial Modeling and Machine Learning — Topic Contributed Papers
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Survey Research Methods Section, Government Statistics Section, Section on Bayesian Statistical Science
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Organizer(s): Scott H. Holan, University of Missouri
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Chair(s): Scott H. Holan, University of Missouri
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10:05 AM
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Bayesian Nonparametric Multivariate Spatial Mixture Mixed Effects Models with Application to American Community Survey Special Tabulations
Ryan Janicki, U.S. Census Bureau ; Andrew M. Raim, U.S. Census Bureau; Scott H. Holan, University of Missouri; Jerry Maples, U.S. Census Bureau
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10:25 AM
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A Bivariate Dirichlet-Multinomial Small Area Share Model with Application to Joint Estimation of School District Population and Poverty
Jerry Maples, U.S. Census Bureau
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10:45 AM
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Computationally Efficient Deep Bayesian Unit-Level Modeling of Survey Data Under Informative Sampling for Small Area Estimation
Paul A. Parker, University of Missouri; Scott H. Holan, University of Missouri
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11:05 AM
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Interpolating Population Distributions using Public-use Data with Application to the American Community Survey
Matthew Simpson, SAS Institute; Scott H. Holan, University of Missouri; Christopher Wikle, University of Missouri; Jonathan Bradley, Florida State University
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11:25 AM
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Bayesian Analysis of Areal Data with Unknown Adjacencies Using the Stochastic Edge Mixed Effects Model
Jonathan Bradley, Florida State University
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11:45 AM
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Floor Discussion
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