Outlier Detection and Time Series Modeling


Abraham, Bovas; Chuang, Alice   (1989, ASQC and the American Statistical Association)   University of Waterloo, Canada; Bowling Green State University, Bowling Green, OH

Technometrics    Vol. 31    No. 2
QICID: 9397    May 1989    pp. 241-248
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Article Abstract

Some statistics used in regression analysis are considered for detection of outliers in time series. Approximations and asymptotic distributions of these statistics are considered. A method is proposed for distinguishing an observational outlier from an innovational one. A four-step procedure for modeling time series in the presence of outliers is also proposed, and an example is presented to illustrate the methodology.


ARMA (autoregressive moving average) model,Autoregression,Diagnostics

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