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- Title
Change-point monitoring in linear models.
- Authors
Aue, Alexander; Horváth, Lajos; Hušková, Marie; Kokoszka, Piotr
- Abstract
We consider a linear regression model with errors modelled by martingale difference sequences, which include heteroskedastic augmented GARCH processes. We develop asymptotic theory for two monitoring schemes aimed at detecting a change in the regression parameters. The first method is based on the CUSUM of the residuals and was studied earlier in the context of independent identically distributed errors. The second method is new and is based on the squares of prediction errors. Both methods use a training sample of size m. We show that, as , both methods have correct asymptotic size and detect a change with probability approaching unity. The methods are illustrated and compared in a small simulation study.
- Subjects
REGRESSION analysis; LINEAR statistical models; PROBABILITY theory; ERRORS; MATHEMATICAL statistics; MULTIVARIATE analysis
- Publication
Econometrics Journal, 2006, Vol 9, Issue 3, p373
- ISSN
1368-4221
- Publication type
Article
- DOI
10.1111/j.1368-423X.2006.00190.x