On sequential detection of parameter changes in linear regression

被引：31

作者：

Horvath, Lajos ^{[1
]}

Kokoszka, Piotr

Steinebach, Josef

机构：

[1] Univ Utah, Salt Lake City, UT 84112 USA

[2] Utah State Univ, Logan, UT 84322 USA

[3] Univ Cologne, D-5000 Cologne, Germany

来源：

STATISTICS & PROBABILITY LETTERS | 2007年 / 77卷 / 09期

基金：

美国国家科学基金会;

关键词：

Darling-Erdos limit theorem; linear regression model; sequential monitoring;

D O I：

10.1016/j.spl.2006.12.014

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：

Horvath et al. [2004. Monitoring changes in linear models. J. Statist. Plann. Inference 126, 225-251] developed a family of monitoring procedures to detect a change in the parameters of a linear regression model. These procedures, which are akin to the schemes proposed by Chu et al. [1996. Monitoring structural change. Econometrica 64, 1045-1065], depend on a parameter 0 <= gamma < 1/2. If gamma is close to 1/2, the detection delay is small, so it is desirable to consider the case gamma =1/2, but an extension is not obvious. We show that it can be developed by establishing a Darling-Erdos type limit theorem. (C) 2007 Elsevier B.V. All rights reserved.

引用

页码：885 / 895

页数：11

共 12 条

[1] Delay time in sequential detection of change [J].