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Title: Smoothed bootstrapping kernel density estimation under higher order kernel
Authors: Yi, Kun
Nishiyama, Yoshihiko
Keywords: kernel density estimation
smoothed bootstrap
bias estimation
higher order kernel
Issue Date: Sep-2022
Publisher: Institute of Economic Research, Kyoto University
Journal title: KIER Discussion Paper
Volume: 1081
Start page: 1
End page: 20
Abstract: Smoothed bootstrap method is a useful method to approximates the bias of Kernel density estimation. However, it can only be applied when the kernel function is of second order. In this study, we propose a novel method to generalize the smoothed bootstrap method to higher order kernel for estimating the bias and construct bias corrected estimator based on it. Theoretical formulation and numerical simulation demonstrate that the proposed method achieve better performance compared to the traditional bias correction method.
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Appears in Collections:KIER Discussion Paper (English)

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