Moderate deviations and large deviations for a test of symmetry based on kernel density estimator
被引:0
|
作者:
He Xiaoxia
论文数: 0引用数: 0
h-index: 0
机构:
Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China
Wuhan Univ Sci & Technol, Coll Sci, Wuhan 430081, Peoples R ChinaWuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China
He Xiaoxia
[1
,2
]
Gao Fuqing
论文数: 0引用数: 0
h-index: 0
机构:
Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R ChinaWuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China
Gao Fuqing
[1
]
机构:
[1] Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China
[2] Wuhan Univ Sci & Technol, Coll Sci, Wuhan 430081, Peoples R China
symmetry test;
kernel estimator;
moderate deviations;
large deviations;
D O I:
暂无
中图分类号:
O1 [数学];
学科分类号:
0701 ;
070101 ;
摘要:
Let f(n) 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(x is an element of R) vertical bar f(n)(x) - f(n) (-x)vertical bar.