数学物理学报(英文版)

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MODERATE DEVIATIONS AND LARGE DEVIATIONS FOR A TEST OF SYMMETRY#br# BASED ON KERNEL DENSITY ESTIMATOR

何晓霞; 高付清   

  1. 武汉大学数学与统计学院, 武汉 430072
  • 收稿日期:2005-09-15 修回日期:2006-10-08 出版日期:2008-07-20 发布日期:2008-07-20
  • 通讯作者: 何晓霞
  • 基金资助:

    Research supported by the National Natural Science Foundation of China (10271091)

MODERATE DEVIATIONS AND LARGE DEVIATIONS FOR A TEST OF SYMMETRY#br# BASED ON KERNEL DENSITY ESTIMATOR

He Xiaoxia; Gao Fuqing   

  1. School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China
  • Received:2005-09-15 Revised:2006-10-08 Online:2008-07-20 Published:2008-07-20
  • Contact: He Xiaoxia

摘要:

Let fn be a non-parametric kernel density estimator based on a kernel function K. and a sequence of independent and identically distributed random variables taking values in R. The goal of this article is to prove moderate deviations and large deviations for the statistic
$\sup\limits_{x\in{{\Bbb R}}}| {f_{n}(x)-f_{n}(-x)}| $.

关键词: Symmetry test, kernel estimator, moderate deviations, large deviations

Abstract:

Let fn be a non-parametric kernel density estimator based on a kernel function K. and a sequence of independent and identically distributed random variables taking values in R. The goal of this article is to prove moderate deviations and large deviations for the statistic
$\sup\limits_{x\in{{\Bbb R}}}| {f_{n}(x)-f_{n}(-x)}| $.

Key words: Symmetry test, kernel estimator, moderate deviations, large deviations

中图分类号: 

  • 60F10