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Higher-Order Spatial Structure Functions for Exploring Spatial Extremes

Abstract Number:

2981 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Poster 

Participants:

Souvik Bag (1), Likun Zhang (1), Christopher Wikle (1)

Institutions:

(1) University of Missouri-Columbia, USA

Co-Author(s):

Likun Zhang  
University of Missouri-Columbia
Christopher Wikle  
University of Missouri-Columbia

First Author:

Souvik Bag  
University of Missouri-Columbia

Presenting Author:

Souvik Bag  
N/A

Abstract Text:

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| | |

Sponsors:

Section on Statistics and the Environment

Tracks:

Spatio-temporal statistics

Can this be considered for alternate subtype?

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I have read and understand that JSM participants must abide by the Participant Guidelines.

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I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.

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