The Estimation of Conditional Densities
AbstractWe discuss a number of issues in the smoothed nonparametric estimation of kernel conditional probability density functions for stationary processes. The kernel conditional density estimate is a ratio of joint and marginal density estimates. We point out the different implications of leading choices of bandwidths in numerator and denominator for the ability of the estimate to integrate to one and to have finite moments. Again bearing in mind different bandwidth possibilities, we discuss asymptotic theory for the estimate: asymptotic bias and variance are calculated under various conditions, an extended discussion of bandwidth choice is included, and a central limit theorem is given.
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 Suntory and Toyota International Centres for Economics and Related Disciplines, LSE in its series STICERD - Econometrics Paper Series with number /2001/415.
Date of creation: May 2001
Date of revision:
Contact details of provider:
Web page: http://sticerd.lse.ac.uk/_new/publications/default.asp
Conditional density estimation; serial dependence; bandwidth choice.;
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.:
- Roussas, George G., 1991. "Recursive estimation of the transition distribution function of a Markov process: A symptotic normality," Statistics & Probability Letters, Elsevier, vol. 11(5), pages 435-447, May.
- Samanta, M., 1989. "Non-parametric estimation of conditional quantiles," Statistics & Probability Letters, Elsevier, vol. 7(5), pages 407-412, April.
- Favaro, Donata & Magrini, Stefano, 2008.
"Group versus individual discrimination among young workers: A distributional approach,"
The Journal of Socio-Economics,
Elsevier, vol. 37(5), pages 1856-1879, October.
- Donata Favaro & Stefano Magrini, 2005. "Group versus individual discrimination among young workers: a distributional approach," Labor and Demography 0506003, EconWPA.
- Amaro de Matos, Joao & Fernandes, Marcelo, 2007. "Testing the Markov property with high frequency data," Journal of Econometrics, Elsevier, vol. 141(1), pages 44-64, November.
- Buch-Kromann, Tine & Guillén, Montserrat & Linton, Oliver & Nielsen, Jens Perch, 2011. "Multivariate density estimation using dimension reducing information and tail flattening transformations," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 99-110, January.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If references are entirely missing, you can add them using this form.