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

被引：4
|
作者：
Hirukawa, Masayuki [1 ]
Sakudo, Mari [2 ,3 ,4 ,5 ,6 ,7 ]
机构：
[1] Ryukoku Univ, Kyoto, Japan
[2] Dev Bank Japan, Tokyo, Japan
[3] Waseda Univ, Tokyo, Japan
[4] Japan Econ Res Inst, Tokyo, Japan
[5] Dev Bank Japan, Res Inst Capital Format, Chiyoda Ku, 9-7,Otemachi 1 Chome, Tokyo 1008178, Japan
[6] Waseda Univ, Waseda Inst Polit Econ, Shinjuku Ku, 6-1 Nishiwaseda 1 Chome, Tokyo 1698050, Japan
[7] Japan Econ Res Inst, Chiyoda Ku, 9-2,Otemachi 1 Chome, Tokyo 1000004, Japan
来源：
STATISTICS & PROBABILITY LETTERS | 2019年 / 145卷
基金：
日本学术振兴会;
关键词：
Asymmetric kernel; Bias reduction; Boundary effect; Semiparametric density estimation; Smoothing;
D O I：
10.1016/j.spl.2018.09.002
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
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. (C) 2018 Elsevier B.V. All rights reserved.
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页码：158 / 165
页数：8
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