Using the Penalized Likelihood Method for Model Selection with Nuisance Parameters Present only under the Alternative: An Application to Switching Regression Models
AbstractWe study the problem of model selection with nuisance parameters present only under the alternative. The common approach for testing in this case is to determine the true model through the use of some functionals over the nuisance parameters space. Since in such cases the distribution of these statistics is not known, critical values had to be approximated usually through computationally intensive simulations. Furthermore, the computed critical values are data and model dependent and hence cannot be tabulated. We address this problem by using the penalized likelihood method to choose the correct model. We start by viewing the likelihood ratio as a function of the unidentified parameters. By using the empirical process theory and the uniform law of the iterated logarithm (LIL) together with sufficient conditions on the penalty term, we derive the consistency properties of this method. Our approach generates a simple and consistent procedure for model selection. This methodology is presented in the context of switching regression models. We also provide some Monte Carlo simulations to analyze the finite sample performance of our procedure. Copyright 2005 Blackwell Publishing Ltd.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Wiley Blackwell in its journal Journal of Time Series Analysis.
Volume (Year): 26 (2005)
Issue (Month): 5 (09)
Contact details of provider:
Web page: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Preminger, Arie & Franck, Raphael, 2007.
"Forecasting exchange rates: A robust regression approach,"
International Journal of Forecasting,
Elsevier, vol. 23(1), pages 71-84.
- PREMINGER, Arie & FRANCK, Raphael, . "Forecasting exchange rates: a robust regression approach," CORE Discussion Papers RP -1917, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- PREMINGER, Arie & FRANCK, Raphael, 2005. "Forecasting exchange rates: a robust regression approach," CORE Discussion Papers 2005025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Anna Conte & John Hey, 2013.
"Assessing multiple prior models of behaviour under ambiguity,"
Journal of Risk and Uncertainty,
Springer, vol. 46(2), pages 113-132, April.
- Ana Conte & John D. Hey, 2011. "Assessing Multiple Prior Models of Behaviour under Ambiguity," Jena Economic Research Papers 2011-068, Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics.
- Anna Conte & John D. Hey, 2012. "Assessing Multiple Prior Models of Behaviour under Ambiguity," Discussion Papers 12/01, Department of Economics, University of York.
- PREMINGER, Arie & HAFNER, Christian M., 2006. "Deciding between GARCH and stochastic volatility via strong decision rules," CORE Discussion Papers 2006042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Jiménez-Gamero, M.D. & Pino-Mejías, R. & Alba-Fernández, V. & Moreno-Rebollo, J.L., 2011. "Minimum [phi]-divergence estimation in misspecified multinomial models," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3365-3378, December.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.