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131
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Mon, 8/9/2021,
1:30 PM -
3:20 PM
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Virtual
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Methods for Spatial, Temporal, and Spatio-Temporal Data — Contributed Speed
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Section on Statistics and the Environment
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Chair(s): Brooke Alhanti, Duke University
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1:35 PM
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Nonstationary Nearest Neighbor Gaussian Process: Hierarchical Model Architecture and MCMC Sampling
Sébastien Coube-Sisqueille, Université de Pau et des Pays de l'Adour; Sudipto Banerjee, University of California Los Angeles ; Benoît Liquet, Université de Pau et des Pays de l'Adour
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1:40 PM
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Computational Developments and Applications of the Multi-Resolution Approximation for Massive Spatial Data
Lewis Blake, Colorado School of Mines; Huang Huang, King Abdullah University of Science and Technology; Matthias Katzfuss, Texas A&M University; Dorit Hammerling, Colorado School of Mines
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1:45 PM
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Fast Correlation-Based Sparse Inverse Cholesky Factorization for Gaussian Processes
Myeongjong Kang, Texas A&M University; Matthias Katzfuss, Texas A&M University
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1:50 PM
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Bag of DAGs: Flexible and Scalable Modeling of Spatiotemporal Dependence
Bora Jin, Duke University; Michele Peruzzi, Duke University; James Johndrow, University of Pennsylvania; David Dunson, Duke University
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1:55 PM
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A Semiparametric Approach for Prediction with Large Geostatistical Data Sets
Joshua French, University of Colorado Denver; Mohammad Meysami, University of Colorado Denver
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2:00 PM
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Regionalized Models with Spatially Continuous Predictions at the Borders
Jadon Wagstaff, Utah State University; Brennan Bean, Utah State University
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2:05 PM
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Ordered Conditional Approximation of Potts Models
Anirban Chakraborty, Texas A&M University; Matthias Katzfuss, Texas A&M University
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2:10 PM
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Response Envelopes for Multivariate Spatial Data
Hossein Moradi Rekabdarkolaee, South Dakota State University
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2:15 PM
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Continuous-Time Discrete-Space Movement Models Over Two- and Three-Dimensional Space
Joshua Hewitt, Duke University; Robert S Schick, Duke University; Alan E Gelfand, Duke University
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2:20 PM
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Extensions of Dynamic Factor Analysis for Better Modeling of Noisy Ecological Time Series
Eric Ward, NOAA; Sean Anderson, Fisheries and Oceans Canada; Mary Hunsicker, NOAA; Mike Litzow, NOAA
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2:30 PM
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Transformed-Linear Prediction for Extremes
Jeongjin Lee, Colorado State University; Daniel Cooley, Colorado State University
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2:35 PM
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Modeling Short-Ranged Dependence in Block Extrema with Application to Polar Temperature Data
Brook Russell, Clemson University School of Mathematical and Statistical Sciences; Whitney Huang, Clemson University School of Mathematical and Statistical Sciences
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2:40 PM
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Spatio-Temporal Analysis Frequency Separation and Block Bootstraps of Periodically Correlated Time Series
Edward L Valachovic, University at Albany, State University of New York
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2:45 PM
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Spatial Analysis of Nonstationary Spatial Interval-Valued Data
Austin Workman, Baylor University; Joon Jin Song, Baylor University
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2:50 PM
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Data-Driven Approach to Nonlinear Dynamic Equation Discovery
Joshua S North, University of Missouri; Erin M Schliep, University of Missouri; Christopher Wikle, University of Missouri
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2:55 PM
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Modeling Spatial Dependence with Cauchy Convolution Processes
Pavel Krupskii, University of Melbourne; Raphaël Huser, KAUST
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3:00 PM
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Nonlinear Spatial Prediction with Predictor Subject to Limit of Detection
Minho Kim, Baylor University; Kyuhee Shin, Kyungpook National University; Gyuwon Lee , Kyungpook National University; Joon Jin Song, Baylor University
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3:05 PM
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A General Ensemble Filtering Framework Using Quantiles
Jeffrey Anderson, National Center for Atmospheric Research
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3:10 PM
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Floor Discussion
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