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