Recursive estimation for regression with infinite variance fractional ARIMA noise

被引：0

作者：

Thavaneswaran, A ^{[1
]}

Peiris, S

机构：

[1] Univ Manitoba, Dept Stat, Winnipeg, MB R3T 2N2, Canada

[2] Univ Sydney, Sch Math & Stat, Sydney, NSW 2006, Australia

来源：

MATHEMATICAL AND COMPUTER MODELLING | 2001年 / 34卷 / 9-11期

基金：

加拿大自然科学与工程研究理事会;

关键词：

nonparametric estimation; stable distributions; heavy-tails; long memory; fractional ARIMA; recursive estimation; innovation; noise; regression;

D O I：

10.1016/S0895-7177(01)00121-2

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Recently, there has been a growing interest in modeling financial time series using fractional ARIMA models with stable innovations; see, for example, [1]. In this paper, the corresponding nonparametric problem for regression with fractional ARIMA noise is studied. A recursive algorithm for estimating time varying parameters is given. It is also shown that a number of existing algorithms are special cases of this proposed algorithm. (C) 2001 Elsevier Science Ltd. All rights reserved.

引用

页码：1133 / 1137

页数：5

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