The ARMA model in state space form

被引：29

作者：

de Jong, P

Penzer, J

机构：

[1] Univ London London Sch Econ & Polit Sci, Dept Stat, London WC2A 2AE, England

[2] Macquarie Univ, Dept Actuarial Studies, N Ryde, NSW 2109, Australia

来源：

STATISTICS & PROBABILITY LETTERS | 2004年 / 70卷 / 01期

关键词：

filter steady state; Kalman filter smoother; state space model; time series;

D O I：

10.1016/j.spl.2004.08.006

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 article explores alternative state space representations for ARMA models. We advocate representations that have minimal state order and appealing Kalman filter steady state properties. We derive expressions for smoother output and describe concrete connections to classical infinite sample representations. (C) 2004 Elsevier B.V. All rights reserved.

引用

页码：119 / 125

页数：7

共 18 条

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