Sept 30, 2022 (rescheduled to Dec 02)
Summary
{{https://sites.google.com/site/hssomal/, Sam Somal}} (William & Mary)
Full Description
Title: Using heterogenous computing to fit a class of spatial models
Abstract: A popular model for spatial association is the conditional autoregressive (CAR) model. I will present an independent sampling algorithm to fit a particular member of this class of models in the presence of missingness and describe a parallelized implementation of the algorithm that can be executed on a wide range of hardware. The merits of the model and algorithm are demonstrated through simulation and analysis of an environmental data set.
