MDL Mean Function Selection in Semiparametric Kernel Regression Models
AbstractWe study the problem of selecting the optimal functional form among a set of non-nested nonlinear mean functions for a semiparametric kernel based regression model. To this end we consider Rissanen's minimum description length (MDL) principle. We prove the consistency of the proposed MDL criterion. Its performance is examined via simulated data sets of univariate and bivariate nonlinear regression models.
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.
Bibliographic InfoPaper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 08-046/4.
Date of creation: 07 May 2008
Date of revision:
Contact details of provider:
Web page: http://www.tinbergen.nl
Kernel density estimator; Maximum likelihood estimator; Minimum description length; Nonlinear regression; Semiparametric model;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-06-21 (All new papers)
- NEP-ECM-2008-06-21 (Econometrics)
- NEP-ORE-2008-06-21 (Operations Research)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Harry Joe, 1989. "Estimation of entropy and other functionals of a multivariate density," Annals of the Institute of Statistical Mathematics, Springer, vol. 41(4), pages 683-697, December.
- Ao Yuan & Jan G. De Gooijer, 2006.
"Semiparametric Regression with Kernel Error Model,"
Tinbergen Institute Discussion Papers
06-058/4, Tinbergen Institute.
- Hall, Peter, 1986. "On powerful distributional tests based on sample spacings," Journal of Multivariate Analysis, Elsevier, vol. 19(2), pages 201-224, August.
- Hansen M. H & Yu B., 2001. "Model Selection and the Principle of Minimum Description Length," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 746-774, June.
- Peter Hall & Sally Morton, 1993. "On the estimation of entropy," Annals of the Institute of Statistical Mathematics, Springer, vol. 45(1), pages 69-88, March.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Antoine Maartens (+31 626 - 160 892)).
If references are entirely missing, you can add them using this form.