The Estimation of Conditional Densities

17 Pages Posted: 21 Jul 2008

See all articles by Xiaohong Chen

Xiaohong Chen

Yale University - Cowles Foundation

Oliver B. Linton

University of Cambridge

Date Written: May 2001

Abstract

We 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.

JEL Classification: C13, C14

Suggested Citation

Chen, Xiaohong and Linton, Oliver B., The Estimation of Conditional Densities (May 2001). LSE STICERD Research Paper No. EM415, Available at SSRN: https://ssrn.com/abstract=1162597

Xiaohong Chen (Contact Author)

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States

Oliver B. Linton

University of Cambridge ( email )

Faculty of Economics
Cambridge, CB3 9DD
United Kingdom