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
收藏
页码：1133 / 1137
页数：5
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