Least squares estimation for critical random coefficient first-order autoregressive processes

被引：11

作者：

Hwang, SY ^{[1
]}

Basawa, IV

Kim, TY

机构：

[1] Sookmyung Womens Univ, Dept Stat, Seoul, South Korea

[2] Univ Georgia, Dept Stat, Athens, GA USA

[3] Keimyung Univ, Dept Stat, Taegu, South Korea

来源：

STATISTICS & PROBABILITY LETTERS | 2006年 / 76卷 / 03期

关键词：

critical process; random coefficient AR(1); test of criticality; weighted and ordinary least squares;

D O I：

10.1016/j.spl.2005.08.024

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：

Critical random coefficient AR(l) processes are investigated where the random coefficient is binary, taking values -1 and 1. Asymptotic behavior of least squares estimator for the mean of the random coefficient is discussed. Ordinary least squares estimator is shown to be consistent. Weighted least squares estimator turns out to be asymptotically normally distributed. This enables us to present a unified limit result for the weighted least squares estimator valid for the stationary, explosive and critical cases. Also, a test of criticality is discussed. (c) 2005 Elsevier B.V. All rights reserved.

引用

页码：310 / 317

页数：8

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