A multivariate descriptor method for change-point detection in nonlinear time series

被引：8

作者：

Balestrassi, P. P. ^{[2
]}

Paiva, A. P. ^{[2
]}

Zambroni de Souza, A. C. ^{[2
]}

Turrioni, J. B. ^{[2
]}

Popova, Elmira ^{[1
]}

机构：

[1] Univ Texas Austin, Dept Ind Engn & Operat Res, Austin, TX 78712 USA

[2] Univ Fed Itajuba, Inst Engn Prod & Gestao, BR-37500 Itajuba, MG, Brazil

来源：

JOURNAL OF APPLIED STATISTICS | 2011年 / 38卷 / 02期

关键词：

nonlinear time series; Hjorth's descriptors; Hotelling control chart; change point; NEURAL-NETWORKS; ALGORITHMS;

D O I：

10.1080/02664760903406496

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：

The purpose of this paper is to present a novel method that is applied to detect dynamic changes in nonlinear time series. The method combines a multivariate control chart that monitors the variation of three normalized descriptors - Hjorth's descriptors of activity, mobility and complexity - and is applied to the change-point detection problem of nonlinear time series. The approach is estimated using six simulated nonlinear time series. In addition, a case study of six time series of short-term electricity load consumption was used to illustrate the power of the method.

引用

页码：327 / 342

页数：16

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