Detection ot Outliers and Level Shifts in Time Series: an Evaluation of Two Alternatives Procedures
A unified method to detect and handle innovational and additive outliers, and permanent and transient level changes has been presented by R.S. Tsay, N.S. Balke has found that the presence of level changes may lead to misidentification and loss of test-power, and suggests augmenting Tsay's procedure by conducting an additional disturbance search based on a white-noise model.
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