Contributed Papers

Advancement in Statistical and Machine Learning Methods for Environmental Data

Mon, Aug 4, 10:30 AM - 12:20 PM Room CC-211 Music City Center

Section on Statistics and the Environment

7 Presentations

Decentralized Inference for Spatial Data Using Low-Rank Models

10:35 AM - 10:50 AM

Co-authors: Jianwei Shi (King Abdullah University of Science and Technology), Jianwei Shi (King Abdullah University of Science and Technology), Sameh Abdulah (King Abdullah University of Science and Technology), Ying Sun (King Abdullah University of Science and Technology), Marc Genton (King Abdullah University of Science and Technology)

Block descent method Dynamic consensus averaging Evidence lower bound Multi-consensus Spatial dependence

Estimation of Impact Ranges for Functional Valued Predictors

10:50 AM - 11:05 AM

Co-authors: Rory Samuels, Joon Jin Song (Baylor University), Nimrod Carmon (Jet Propulsion Laboratory), Bledar Komoni (University of Cincinnati), Jonathan Hobbs (Jet Propulsion Laboratory), Amy Braverman (Jet Propulsion Laboratory), Dean Young, Joon Jin Song (Baylor University)

Functional Data Analysis Functional Partial Least Squares Spectroscopy Impact Range

Frequency Domain Empirical Likelihood Using Distributional Constraint.

11:05 AM - 11:20 AM

Co-authors: Souvick Bera (Colorado School of Mines), Souvick Bera (Colorado School of Mines), Debdeep Pati (University of Wisconsin-Madison), Soutir Bandyopadhyay (Colorado School of Mines)

Frequency Domain Empirical Likelihood Robust Inference Whittle Estimation Spectral Distribution Periodograms

Modeling Bayesian Transport Map Uncertainty for Non-Gaussian Spatial Data via Laplace Approximation

11:20 AM - 11:35 AM

Co-authors: Jacob Johnson (University of Wisconsin - Madison), Matthias Katzfuss (University of Wisconsin–Madison), Jacob Johnson (University of Wisconsin - Madison), Felix Jimenez

Gaussian process Generative modeling Laplace approximation Uncertainty quantification

Multivariate confluent hypergeometric covariance functions with origin and tail flexibility

11:35 AM - 11:50 AM

Co-authors: Andrew Yarger (Purdue University), Andrew Yarger (Purdue University), Anindya Bhadra (Purdue University)

Cross-covariances Multivariate geostatistics Oceanography Spectral construction

On modeling discrete lattice data using the Potts model

11:50 AM - 12:05 PM

Co-authors: Maria Paula Duenas Herrera (The Pennsylvania State University), Maria Paula Duenas Herrera (The Pennsylvania State University), Stephen Berg, Murali Haran (Penn State University)

Potts model Lattice data modeling Discrete lattice data

Spatial Hyperspheric Models for Compositional Data

12:05 PM - 12:20 PM

Co-authors: Michael Schwob (Virginia Tech), Michael Schwob (Virginia Tech), Mevin Hooten (The University of Texas At Austin), Nicholas Calzada (The University of Texas At Austin), Timothy Keitt (University of Texas at Austin)

Bayesian generative hyperspheric regression uncertainty propagation compositional data directional data