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LANS Seminar

March 30, 2022 @ 10:30 - 11:30 CDT

Seminar Title: Bayesian Inference for High-Dimensional Nonstationary Gaussian Processes
Speaker: Mark Risser, Research Scientist, Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory

Date/Time: March 30, 2022 / 10:30 am – 11:30 am
Location: See meeting URL on the cels-seminars website (requires Argonne login)

Host: Julie Bessac


Description: In spite of the diverse literature on nonstationary spatial modelling and approximate Gaussian process (GP) methods, there are no general approaches for conducting fully Bayesian inference for moderately sized nonstationary spatial data sets on a personal laptop. For statisticians and data scientists who wish to conduct posterior inference and prediction with appropriate uncertainty quantification, the lack of such approaches and software is a limitation. In this work, we develop methodology for implementing formal Bayesian inference for a general class of nonstationary GPs. Our novel approach uses pre-existing frameworks for characterizing nonstationarity in a new way while utilizing via modern GP likelihood approximations. Posterior sampling is implemented using flexible MCMC methods, with nonstationary posterior prediction conducted as a post-processing step. We demonstrate our novel methods on three data sets, ranging from several hundred to over several thousand locations. All of our methods are implemented in the freely available BayesNSGP software package for R.

Please note that the meeting URL for this event can be seen on the cels-seminars website, which requires an Argonne login.

Details

Date:
March 30, 2022
Time:
10:30 - 11:30 CDT
Event Category:

Venue

https://wordpress.cels.anl.gov/cels-seminars/event/lans-seminar-43/