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Another bias correction for asymmetric kernel density estimation with a parametric start

Masayuki Hirukawa and Mari Sakudo

Statistics & Probability Letters, 2019, vol. 145, issue C, 158-165

Abstract: This paper studies yet another semiparametric bias-corrected density estimation using asymmetric kernels. The estimator can be obtained by making a multiplicative bias correction for the initial parametric model twice, and it is shown to establish rate improvement when best implemented.

Keywords: Asymmetric kernel; Bias reduction; Boundary effect; Semiparametric density estimation; Smoothing (search for similar items in EconPapers)
Date: 2019
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Handle: RePEc:eee:stapro:v:145:y:2019:i:c:p:158-165