JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 91
Type: Invited
Date/Time: Sunday, August 9, 2015 : 9:30 PM to 10:15 PM
Sponsor: Section on Statistics and the Environment
Abstract #316322
Title: A Gauss-Pareto Process Model for Spatial Prediction of Extreme Precipitation
Author(s): Robert Alohimakalani Yuen* and Peter Guttorp
Companies: University of Michigan and University of Washington
Keywords: spatial ; extremes ; precipitation ; prediction ; censoring
Abstract:

In order to develop adaptive strategies for dealing with consequences of extreme precipitation such as insufficient drainage and various aspects of flooding, it is necessary to be able to estimate extremes at unobserved sites. We introduce a hierarchical Gauss-Pareto model for spatial prediction of precipitation given nearby observations that are extreme. The model belongs to the max-domain of attraction of popular Brown-Resnick max-stable processes and retains the essential dependence structure of their corresponding generalized Pareto processes. An MCMC algorithm is developed for inference. The algorithm allows for left censored data from precipitation that accumulates below instrument precision, which often ocurrs despite nearby observations that are extreme. The model and methodology is applied to summer 24 hour cumulative precipitation over south central Sweden.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2015 program





For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, 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.

2015 JSM Online Program Home