Doubly penalized likelihood estimator in heteroscedastic regression
AbstractA penalized likelihood estimation procedure is developed for heteroscedastic regression. A distinguishing feature of the new methodology is that it estimates both the mean and variance functions simultaneously without parametric assumption for either. An efficient implementation of the estimating procedure is also provided. The procedure is illustrated by a Monte Carlo example. A potential generalization, and application to the covariance modeling problem in numerical weather prediction is noted.
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 Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 69 (2004)
Issue (Month): 1 (August)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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.:
- Gallant, A. Ronald & Tauchen, George, 1997.
"Estimation Of Continuous-Time Models For Stock Returns And Interest Rates,"
Cambridge University Press, vol. 1(01), pages 135-168, January.
- Tauchen, George E. & Gallant, A. Ronald, 1995. "Estimation of Continuous Time Models for Stock Returns and Interest Rates," Working Papers 95-53, Duke University, Department of Economics.
- Jianqing Fan & Qiwei Yao, 1998. "Efficient estimation of conditional variance functions in stochastic regression," LSE Research Online Documents on Economics 6635, London School of Economics and Political Science, LSE Library.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If references are entirely missing, you can add them using this form.