The estimation of conditional densities

Xiaohong Chen (), Oliver Linton and Peter Robinson

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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.

Keywords: Conditional density estimation; serial dependence; bandwidth choice (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Pages: 13 pages
Date: 2001-05
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Citations: View citations in EconPapers (13)

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http://eprints.lse.ac.uk/2312/ Open access version. (application/pdf)

Related works:
Working Paper: The Estimation of Conditional Densities (2001)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:2312

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