A General Kernel Functional Estimator with Generalized Bandwidth: Strong Consistency and Applications

Rafael Weißbach

No 2004,22, Technical Reports from Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen

Abstract: We consider the problem of uniform asymptotics in kernel functional estimation where the bandwidth can depend on the data. In a unified approach we investigate kernel estimates of the density and the hazard rate for uncensored and right-censored observations. The model allows for the fixed bandwidth as well as for various variable bandwidths, e.g. the nearest neighbor bandwidth. An elementary proof for the strong consistency of the generalized estimator is given that builds on the local convergence of the empirical process against the cumulative distribution function and the Nelson-Aalen estimator against the cumulative hazard rate, respectively.

Keywords: Functional estimation; Density; Hazard rate; Kernel smoothing; Uniform consistency; Empirical process; Nearest neighbor bandwidth (search for similar items in EconPapers)
Date: 2004
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb475:200422

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