A hierarchical Bayesian spatio-temporal model for extreme precipitation events

被引：40

作者：

Ghosh, Souparno ^{[1
]}

Mallick, Bani K. ^{[1
]}

机构：

[1] Texas A&M Univ, Dept Stat, College Stn, TX 77843 USA

来源：

ENVIRONMETRICS | 2011年 / 22卷 / 02期

基金：

美国国家科学基金会;

关键词：

copula; spatio-temporal; Markov chain Monte Carlo; TRENDS;

D O I：

10.1002/env.1043

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

We propose a new approach to model a sequence of spatially distributed time series of extreme values. Unlike common practice, we incorporate spatial dependence directly in the likelihood and allow the temporal component to be captured at the second level of hierarchy. Inferences about the parameters and spatio-temporal predictions are obtained via MCMC technique. The model is fitted to a gridded precipitation data set collected over 99 years across the continental U.S. Copyright (C) 2010 John Wiley & Sons, Ltd.

引用

页码：192 / 204

页数：13

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