Clustering of large deviations in moving average processes: The long memory regime✩

被引：1

作者：

Chakrabarty, Arijit ^{[1
]}

Samorodnitsky, Gennady ^{[2
]}

机构：

[1] Indian Stat Inst, Theoret Stat & Math Unit, Kolkata, India

[2] Cornell Univ, Sch Operat Res & Informat Engn, Ithaca, NY 14850 USA

来源：

STOCHASTIC PROCESSES AND THEIR APPLICATIONS | 2023年 / 163卷

基金：

美国国家科学基金会;

关键词：

Large deviations; Clustering; Infinite moving average; Long memory;

D O I：

10.1016/j.spa.2023.06.009

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：

We investigate how large deviations events cluster in the framework of an infinite moving average process with light-tailed noise and long memory. The long memory makes clusters larger, and the asymptotic behaviour of the size of the cluster turns out to be described by the first hitting time of a randomly shifted fractional Brownian motion with drift. & COPY; 2023 Elsevier B.V. All rights reserved.

引用

页码：387 / 423

页数：37

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