Testing composite hypotheses applied to AR-model order estimation; the Akaike-criterion revised

R. Moddemeijer

University of Groningen, Department of Computing Science,
P.O. Box 800, NL-9700 AV Groningen, The Netherlands,
phone: +31.50.363 3940 - fax: +31.50.363 38005 - e-mail: rudy@cs.rug.nl


Akaike's criterion is used to test composite hypotheses; for example to determine the order of AR models. A modification is presented to test composite hypotheses given an upper-bound on the error of the first kind (Neyman-Pearson). The presented theory is applied to AR order estimation and verified by simulations. The experimental results are so good that we consider the AR order estimation problem as solved.

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Signal Processing Symposium (SPS '98), IEEE Benelux Signal Processing Chapter , March 26-27, 1998, Leuven Belgium, pp. 135-138, BibTeX

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