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A semiparametric method of boundary correction for kernel density estimation

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  • Alberts, T.
  • Karunamuni, R. J.

Abstract

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 reflection 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.

Suggested Citation

  • Alberts, T. & Karunamuni, R. J., 2003. "A semiparametric method of boundary correction for kernel density estimation," Statistics & Probability Letters, Elsevier, vol. 61(3), pages 287-298, February.
    • Handle: RePEc:eee:stapro:v:61:y:2003:i:3:p:287-298
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    References listed on IDEAS

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    1. Stephen T. Buckland, 1992. "Fitting Density Functions with Polynomials," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(1), pages 63-76, March.
    2. Song Xi Chen, 1996. "A Kernel Estimate for the Density of a Biological Population by Using Line Transect Sampling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(2), pages 135-150, June.
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    Cited by:

    1. Mohsen Arefi & Reinhard Viertl & S. Taheri, 2012. "Fuzzy density estimation," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(1), pages 5-22, January.

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