Reducing the mean squared error in kernel density estimation

被引：0

作者：

Jinmi Kim

Choongrak Kim

机构：

[1] Pusan National University,Department of Statistics

来源：

Journal of the Korean Statistical Society | 2013年 / 42卷

关键词：

primary 62G07; secondary 62G20; Bias reduction; Higher-order kernel; Skewing method; Variance reduction;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In this article, we propose a version of a kernel density estimator which reduces the mean squared error of the existing kernel density estimator by combining bias reduction and variance reduction techniques. Its theoretical properties are investigated, and a Monte Carlo simulation study supporting theoretical results on the proposed estimator is given.

引用

页码：387 / 397

页数：10

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