Robust control charts for the mean of a locally linear time series. Issue 15 (12th October 2020)

• Record Type: Journal Article
• Authors: Abbas, Sermad; Fried, Roland
• Is Part Of: Journal of statistical computation and simulation. Volume 90:Issue 15(2020)
• Page Start: 2741
• Page End: 2765
• Publication Date: 2020-10-12
• Subjects: Change-point detection -- nonlinear time series -- online monitoring -- robust control charts; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2020.1788562
• Languages: English
• ISSNs: 0094-9655

Abstract

Abstract : We study residual control charts for the detection of sudden changes in time series with an underlying time-varying trend. Our control charts compare the most recent observations to their direct predecessors by applying two-sample tests in a moving time window to one-step-ahead prediction errors obtained from a local linear regression. Global model assumptions, a fixed target value, or large sets of historical in-control data are unnecessary therefore. Disturbing in-control structures, like short outlier patches or minor fluctuations, are resisted by using robust methods. Our simulation results indicate that a control chart based on the two-sample Hodges-Lehmann estimator in combination with repeated-median regression possesses an approximately distribution-free in-control average run length, good robustness against outliers, and a desirable detection quality.