On Bias Reduction in Kernel Density Estimation

  • Kim Choongrak (Department of Statistics, Pusan National University) ;
  • Park Byeong-Uk (Department of Statistics, Seoul National University) ;
  • Kim Woochul (Department of Statistics, Seoul National University)
  • Published : 2000.11.01

Abstract

Kernel estimator is very popular in nonparametric density estimation. In this paper we propose an estimator which reduces the bias to the fourth power of the bandwidth, while the variance of the estimator increases only by at most moderate constant factor. The estimator is fully nonparametric in the sense of convex combination of three kernel estimators, and has good numerical properties.

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