Time-changed extremal process as a random sup measure

被引:14
作者
Lacaux, Celine [1 ,2 ,3 ]
Samorodnitsky, Gennady [4 ,5 ]
机构
[1] Univ Lorraine, Inst Elie Cartan De Lorraine, UMR 7502, F-54506 Vandoeuvre Les Nancy, France
[2] CNRS, Inst Elie Cartan De Lorraine, UMR 7502, F-54506 Vandoeuvre Les Nancy, France
[3] Inria, BIGS, F-54600 Villers Les Nancy, France
[4] Cornell Univ, Sch Operat Res & Informat Engn, Ithaca, NY 14853 USA
[5] Cornell Univ, Dept Stat Sci, Ithaca, NY 14853 USA
关键词
extremal limit theorem; extremal process; heavy tails; random sup measure; stable process; stationary max-increments; self-similar process; ALPHA-STABLE PROCESSES; MOVING AVERAGES; LIMIT THEORY; LONG MEMORY; STATIONARY;
D O I
10.3150/15-BEJ717
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
A functional limit theorem for the partial maxima of a long memory stable sequence produces a limiting process that can be described as a beta-power time change in the classical Frechet extremal process, for,8 in a subinterval of the unit interval. Any such power time change in the extremal process for 0 < beta < 1 produces a process with stationary max-increments. This deceptively simple time change hides the much more delicate structure of the resulting process as a self-affine random sup measure. We uncover this structure and show that in a certain range of the parameters this random measure arises as a limit of the partial maxima of the same long memory stable sequence, but in a different space. These results open a way to construct a whole new class of self-similar Frechet processes with stationary max-increments.
引用
收藏
页码:1979 / 2000
页数:22
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