On Conditional Density Estimation

Jan G. Gooijer and Dawit Zerom (dzerom@fullerton.edu)

No 02-032/4, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: With the aim to mitigate the possibleproblem of negativity in the estimation of the conditionaldensity function, we introduce a so-called re-weightedNadaraya-Watson (RNW) estimator. The proposed RNWestimator is constructed by a slight modificationof the well-known Nadaraya-Watson smoother.Because the estimator is explicitly defined in terms ofthe data, its practical implementation is quite simple.With a detailed asymptotic analysis, we demonstratethat the RNW smoother preserves thesuperior large-sample bias property of thelocal linear smoother of the conditional densityproposed by Fan, Yao and Tong (1996).As a matter of independent statistical interest,the limit distribution of the RNW estimator is alsoderived.

Keywords: alpha-mixing; asymptotic properties; negativity; nonparametric; re-weighted (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Date: 2002-04-08
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Journal Article: On Conditional Density Estimation (2003)
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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20020032

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