This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 290
Type: Topic Contributed
Date/Time: Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics and the Environment
Abstract - #308486
Title: A Penalized Pointwise Likelihood Approach for m-Year Precipitation Return Values Estimation Based on Regional Climate Model Output
Author(s): Jun Zhang*+ and Wei Zheng
Companies: Statistical and Applied Mathematical Sciences Institute and Eli Lilly and Company
Address: 19 T.W. Alexander Drive, Research Triangle Park, NC, 27709-4006,
Keywords: penalized pointwise likelihood ; extreme value theory ; latent spatial structures
Abstract:

The estimation of m-year precipitation return values is important for evaluating the impacts of climate change. We present a penalized pointwise likelihood method in this paper for estimating generalized extreme value distribution(GEV) and generalized Pareto distribution (GPD) parameters. Based on pointwise likelihood models, we model the underlying GEV or GPD parameters through latent spatial structures expressed as spatial penalization terms in estimation equations. The penalization terms are selected by data-driven approaches. We evaluate the uncertainty of the estimates using both approximation and cross-validation. A simulated example and an example based on the North American Regional Climate Model output are used to demonstrate the effectiveness of the model.


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