Efficient estimators and LAN in canonical bivariate POT models

被引:4
作者
Falk, M
Reiss, RD
机构
[1] Univ Wurzburg, Inst Angew Math & Stat, D-97074 Wurzburg, Germany
[2] Univ Gesamthsch Siegen, Siegen, Germany
关键词
bivariate max-stable distribution; bivariate generalized Pareto distribution; dependence function; canonical parameterization; peaks-over-threshold stability; BLUE; LAN; Hajek-LeCam convolution theorem; regular estimators;
D O I
10.1016/S0047-259X(02)00010-6
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Bivariate generalized Pareto distributions (GPs) with uniform margins are introduced and elementary properties such as peaks-over-threshold (POT) stability are discussed. A unified parameterization with parameter thetais an element of[0,1] of the GPs is provided by their canonical parameterization. We derive efficient estimators of theta and of the dependence function of the GP in various models and establish local asymptotic normality (LAN) of the loglikelihood function of a 2 x 2 table sorting of the observations. From this result we can deduce that the estimator of theta suggested by Falk and Reiss (2001, Statist. Probab. Lett. 52, 233-242) is not efficient, whereas a modification actually is. (C) 2003 Elsevier Science (USA). All rights reserved.
引用
收藏
页码:190 / 207
页数:18
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