Non And Semi-Parametric Estimation In Models With Unknown Smoothness
Many asymptotic results for kernel-based estimators were established under some smoothness assumption on density. For cases where smoothness assumptions that are used to derive unbiasedness or asymptotic rate may not hold we propose a combined estimator that could lead to the best available rate without knowledge of density smoothness. A Monte Carlo example confirms good performance of the combined estimator.
|Date of creation:||Sep 2006|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (514) 398-3030
Fax: (514) 398-4938
Web page: http://www.repec.mcgill.ca
More information through EDIRC
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.:
- Zinde-Walsh, Victoria, 2002. "Asymptotic Theory For Some High Breakdown Point Estimators," Econometric Theory, Cambridge University Press, vol. 18(05), pages 1172-1196, October.
- Pagan,Adrian & Ullah,Aman, 1999.
Cambridge University Press, number 9780521586115.
- Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-31, May.
When requesting a correction, please mention this item's handle: RePEc:mcl:mclwop:2006-15. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Shama Rangwala)The email address of this maintainer does not seem to be valid anymore. Please ask Shama Rangwala to update the entry or send us the correct address
If references are entirely missing, you can add them using this form.