Long-memory continuous-time correlation models

被引：11

作者：

Ma, CS ^{[1
]}

机构：

[1] Wichita State Univ, Dept Math & Stat, Wichita, KS 67260 USA

来源：

JOURNAL OF APPLIED PROBABILITY | 2003年 / 40卷 / 04期

关键词：

continuous-time autoregressive and moving-average process; long-range dependence; power-law decay; short-range dependence; slow decay; Ornstein-Uhlenbeck process;

D O I：

10.1239/jap/1067436105

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：

This paper introduces a rather general class of stationary continuous-time processes with long memory by randomizing the time-scale of short-memory processes. In particular, by randomizing the time-scale of continuous-time autoregressive and moving-average processes, many power-law decay and slow decay correlation functions are obtained.

引用

页码：1133 / 1146

页数：14

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