38 Higher-Order Spatial Structure Functions for Exploring Spatial Extremes

Likun Zhang Co-Author
University of Missouri-Columbia
 
Christopher Wikle Co-Author
University of Missouri-Columbia
 
Souvik Bag First Author
 
Souvik Bag Presenting Author
 
Tuesday, Aug 6: 2:00 PM - 3:50 PM
2981 
Contributed Posters 
Oregon Convention Center 
Spatial statistics has long relied on measures of second-order dependence (e.g., covariance functions and variograms) to characterize and model spatial dependence. In the turbulence literature, higher-order spatial dependence measures, such as third and fourth-order structure functions (variograms) have been instrumental in characterizing important behavior such as turbulent energy cascades. Here, we investigate the use of these higher-order structure functions to better characterize the dependence structure of spatial extremes, which can help with the specification of appropriate statistical models for such dependence. We illustrate the approach on simulated and real-world environmental data.

Keywords

structure functions

spatial extremes

turbulence 

Abstracts


Main Sponsor

Section on Statistics and the Environment