Nonparametric Sequential Surveillance of Intervention Effects in Time Series

Peter Hackl

doi:10.1007/978-3-662-06824-3_7

Nonparametric Sequential Surveillance of Intervention Effects in Time Series

Peter Hackl

Statistics and Mathematics

Publikation: Beitrag in Buch/Konferenzband › Beitrag in Sammelwerk

Abstract

A nonparametric process procedure is proposed as a tool for continuous monitoring to detect intervention effects in a time series. The procedure uses exponentially weighted moving averages of the ranks of the post-intervention one-step-ahead forecast errors. The forecasts are based on the pre-intervention model, and the errors are ranked with respect to residuals in the pre-intervention period. The method is illustrated with the Los Angeles oxidant data previously analyzed by Box and Tiao (1975).

Originalsprache	Englisch
Titel des Sammelwerks	Economic Structural Change
Untertitel des Sammelwerks	Analysis and Forecasting
Herausgeber*innen	Peter Hackl, Anders Westlund
Erscheinungsort	Berlin
Verlag	Springer
Kapitel	7
Seiten	85-94
ISBN (elektronisch)	978-3-662-06824-3
ISBN (Print)	978-3-662-06826-7
DOIs	https://doi.org/10.1007/978-3-662-06824-3_7
Publikationsstatus	Veröffentlicht - 1991

Zugriff auf Dokument

10.1007/978-3-662-06824-3_7

Zitat

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abstract = "A nonparametric process procedure is proposed as a tool for continuous monitoring to detect intervention effects in a time series. The procedure uses exponentially weighted moving averages of the ranks of the post-intervention one-step-ahead forecast errors. The forecasts are based on the pre-intervention model, and the errors are ranked with respect to residuals in the pre-intervention period. The method is illustrated with the Los Angeles oxidant data previously analyzed by Box and Tiao (1975).",

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