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CHANGE-POINT DETECTION WITH RANK STATISTICS IN LONG-MEMORY TIME-SERIES MODELS

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Summary

Wilcoxon-type rank statistics are considered for testing a long-memory time-series model with a common distribution against the alternatives involving a change in the distribution at an unknown time point. The asymptotic properties of the test statistics and the change-point estimators are studied. Finite-sample behaviours are investigated in a small Monte Carlo simulation study. Data examples from hydrology and telecommunications illustrate the method.
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Keywords: change-point analysis; long-memory process; rank statistics

Document Type: Research Article

Publication date: September 1, 2008

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