Control Charts for Multivariate Nonlinear Time Series

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

In this paper control charts for the simultaneous monitoring of the means and the variances of multivariate nonlinear time series are introduced. The underlying target process is assumed to be a constant conditional correlation process (cf. [3]). The new schemes make use of local measures of the means and the variances based on current observations, conditional moments, or residuals. Exponential smoothing and cumulative sums are applied to these characteristic quantities. Distances between these quantities and target values are measured by the Mahalanobis distance. The introduced schemes are compared via a simulation study. As a measure of performance the average run length is used.

Details

Original languageEnglish
Pages (from-to)131-144
Number of pages14
JournalREVSTAT-Statistical Journal
Volume13
Issue number2
Publication statusPublished - 2015
Peer-reviewedYes

External IDs

Scopus 84936953229
ORCID /0000-0002-9732-9405/work/173987781

Keywords

Keywords

  • statistical process control, multivariate CUSUM charts, multivariate EWMA charts, Conditional correlation model