Change detection in linear regression with time series errors

被引：0

作者：

Gombay, Edit ^{[1
]}

机构：

[1] Univ Alberta, Dept Math & Stat Sci, Edmonton, AB T2G 2G1, Canada

来源：

CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 2010年 / 38卷 / 01期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Change-point problem; linear regression; time series; CHANGE-POINT; PARAMETER; MODELS; MEMORY; TESTS;

D O I：

暂无

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：

A new test for detecting a change in linear regression parameters assuming a general weakly dependent error structure is given. It extends earlier methods based on cumulative sums assuming independent errors. The novelty is in the new standardization method and in smoothing when the time series is dominated by high frequencies. Simulations show the excellent performance of the test. Examples are taken from environmental applications. The algorithm is easy to implement. Testing for multiple changes can be done by segmentation. The Canadian Journal of Statistics 38: 65-79; 2010 (c) 2010 Statistical Society of Canada

引用

页码：65 / 79

页数：15

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