Detection ot Outliers and Level Shifts in Time Series: an Evaluation of Two Alternatives Procedures
AbstractA 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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Bibliographic InfoPaper provided by Department of Economics, University of Bergen in its series Norway; Department of Economics, University of Bergen with number 206.
Length: 14 pages
Date of creation: 1999
Date of revision:
Contact details of provider:
Postal: Department of Economics, University of Bergen Fosswinckels Gate 6. N-5007 Bergen, Norway
Web page: http://www.uib.no/econ/
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TIME SERIES ; SIMULATION ; REGRESSION ANALYSIS;
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