Dr. Bernard Omolo, associate professor of mathematics, has co-authored a paper entitled “A survey of spatial extremes: measuring spatial dependence and modeling spatial effects,” which appears in the current issue of the journal  REVSTAT – Statistics Journal.

The paper surveys the current methodology for spatial extreme analysis with respect to climate modeling and geostatistics. Bayesian hierarchical models (BHMs) are highly suitable in this area, since observations are generated by complex processes and hence using the standard Gaussian framework to describe relationships between the observations and these processes is not appropriate. The detailed paper is available online at https://www.ine.pt/revstat/pdf/rs120106.pdf. Omolo teaches in the Division of Mathematics and Computer Science in the College of Arts and Sciences at the University of South Carolina Upstate.