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Activity Number: 87 - Invited ePoster Session: a Statistical Smörgåsbord
Type: Invited
Date/Time: Sunday, July 29, 2018 : 8:30 PM to 10:30 PM
Sponsor: Section on Statistics and the Environment
Abstract #329742
Title: Spatiotemporal Analysis of Environmental Health Risk
Author(s): Renjun Ma* and Edward Hughes
Companies: University of New Brunswick and Edward Hughes Consulting
Keywords: best linear unbiased predictors; mixed models; Poisson regression; random effects; spatial clustering; temporal trend

Big data with complex spatiotemporal structures are common in environmental studies. In order to account for such spatiotemporal structures, spatially and temporally correlated random effects are often incorporated into generalized linear models for such data. The estimation of these models often poses theoretical and computational challenges. We propose an orthodox best linear unbiased predictor (BLUP) approach to these models. Our approach is illustrated with application to Ohio lung cancer data where the annual lung cancer deaths for 88 counties were obtained from 1968-1988. With estimated spatial and temporal random effects, we will also discuss the identification of high/low risk areas, spatial clustering as well as temporal trend.

Authors who are presenting talks have a * after their name.

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