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A semiparametric method of boundary correction for kernel density estimation

✍ Scribed by T. Alberts; R.J. Karunamuni

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
226 KB
Volume
61
Category
Article
ISSN
0167-7152

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✦ Synopsis

We propose a new estimator for boundary correction for kernel density estimation. Our method is based on local Bayes techniques of Hjort (Bayesian Statist. 5 (1996) 223). The resulting estimator is semiparametric type estimator: a weighted average of an initial guess and the ordinary re ection method estimator. The proposed estimator is seen to perform quite well compared to other existing well-known estimators for densities which have the shoulder condition at the endpoints.

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