Abstract
This paper deals with a formal identification of outliers in regression based on tests of hypotheses. The hypothesis is not the standard one but is based on performance criteria that relates to the coefficient estimation and predictive capabilities of the model. The cri-teria include the trace of the mean square error matrix on the coefficients and integrated mean square error of prediction. Both the mean shift outlier model and the variance in-flation model are discussed.
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