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	Weighted estimation of the dependence function for an extreme-value distribution
	Peng, Liang ; Qian, Linyi ; Yang, Jingping
	2013
关键词	bivariate extreme dependence function jackknife empirical likelihood method EMPIRICAL COPULA PROCESSES CONFIDENCE-INTERVALS LIKELIHOOD
英文摘要	Bivariate extreme-value distributions have been used in modeling extremes in environmental sciences and risk management. An important issue is estimating the dependence function, such as the Pickands dependence function. Some estimators for the Pickands dependence function have been studied by assuming that the marginals are known. Recently, Genest and Segers [Ann. Statist. 37 (2009) 2990-3022] derived the asymptotic distributions of those proposed estimators with marginal distributions replaced by the empirical distributions. In this article, we propose a class of weighted estimators including those of Genest and Segers (2009) as special cases. We propose a jackknife empirical likelihood method for constructing confidence intervals for the Pickands dependence function, which avoids estimating the complicated asymptotic variance. A simulation study demonstrates the effectiveness of our proposed jackknife empirical likelihood method.; Statistics & Probability; SCI(E); 1; ARTICLE; 2; 492-520; 19
语种	英语
出处	SCI
出版者	bernoulli
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/391736]
专题	数学科学学院
推荐引用方式 GB/T 7714	Peng, Liang,Qian, Linyi,Yang, Jingping. Weighted estimation of the dependence function for an extreme-value distribution. 2013-01-01.

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