Resource title

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

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Resource description

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.

Resource author

Rafael WeiƟbach

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Resource publish date

Resource language

eng

Resource content type

text/html

Resource resource URL

http://hdl.handle.net/10419/22534

Resource license

Adapt according to the presented license agreement and reference the original author.