Abstract Details
Activity Number:
|
661
|
Type:
|
Invited
|
Date/Time:
|
Thursday, August 8, 2013 : 10:30 AM to 12:20 PM
|
Sponsor:
|
IMS
|
Abstract - #307061 |
Title:
|
Multivariate Max-Stable Spatial Processes
|
Author(s):
|
Marc G. Genton*+ and Simone Padoan and Huiyan Sang
|
Companies:
|
KAUST and Bocconi University of Milan and TAMU
|
Keywords:
|
Composite likelihood ;
Cross-correlation ;
Madogram ;
Max-stable process ;
Multivariate ;
Spatial extremes
|
Abstract:
|
We extend some theoretical results and applications of max-stable processes to the multivariate setting to analyze extreme events of several variables observed across space. First, we study the maxima of independent replicates of multivariate processes, both in the Gaussian and Student-t cases. We describe two important Gaussian examples and discuss possible cross-correlation models. Second, we define a Poisson process construction in the multivariate setting and introduce multivariate versions of the Smith Gaussian extreme-value, the Schlather extremal- Gaussian and extremal-t, and the Brown-Resnick models. We discuss inferential aspects for those models based on composite likelihoods, multivariate extremal coefficients and madograms. We report the results of various Monte Carlo simulations and present an application to a dataset of summer daily temperature maxima and minima in Oklahoma, USA. Joint work with Simone Padoan and Huiyan Sang.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2013 program
|
2013 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.