Maseeh Mathematics + Statistics Colloquium: Why all Statistical Models Should be Spatial
Friday, January 24, 2020 - 3:15pm

 The Maseeh Mathematics and Statistics Colloquium Series*



 Jay Ver Hoef, Ph.D.


National Oceanic and Atmospheric Administration


Why all Statistical Models Should be Spatial



This talk will contain some philosophical musings on modeling data, and why I think that we should always use spatial models.  I begin with a quick review of spatial statistics, drawing connections from probability, inference, and the linear model to Popper's philosophy, Occam's razor, and Neyman-Pearson hypothesis testing.  I present the idea that independence is not an appropriate null model on deciding whether or not to adopt a spatial model.  However, there are technical issues for spatial statistics, for both very small sample sizes, and very large sample sizes, that have stymied their use. For a long time, sample sizes on the order of 100 to 1000 have been practical limits.  For small sample sizes the problems centered on poor estimates of spatial autocorrelation.  However, these problems can be mitigated by marginalization of parameter estimates.  I show the connection between the t-distribution and MCMC sampling, and how those ideas can be extended to spatial models with small sample sizes. I verify their performance through simulations. For larger data, there are now a plethora of methods.  I review some of those methods, and illustrate one that I am developing based on data partitioning.  I show how to model tens of thousands of samples in mere minutes, verify the method with simulations, and illustrate it for stream network data. In summary, many technical issues have been solved for spatial models, from small to large sample sizes, and it is time for statisticians and scientists to adopt the more complicated spatial models as default.



Jay is a Fellow of the American Statistical Association (ASA) and past chair of the Section on Statistics and the Environment and the Alaska Chapter of the ASA. He is also an adjunct professor of statistics with the Department of Mathematics and Statistics at the University of Alaska Fairbanks. He received his B.S. in botany from Colorado State University, Fort Collins; his M.S. in botany from the University of Alaska Fairbanks; and his Ph.D., a co-major in statistics and EEB (ecology and evolutionary biology), from Iowa State University. Ames. Prior to joining NMML in 2005, Jay was a biometrician with the Alaska Department of Fish and Game for 14 years.


Friday, January 24, 2020 at 3:15pm

Fariborz Maseeh Hall room B128, 1855 SW Broadway

Light refreshments served


The faculty host of this speaker is Dr. Daniel Taylor-Rodriguez