High-dimensional Edgeworth expansion of a test statistic on independence and its error bound

被引：8

作者：

Akita, Tomoyuki ^{[1
]}

Jin, Jinghua ^{[2
]}

Wakaki, Hirofumi ^{[1
]}

机构：

[1] Hiroshima Univ, Dept Math, Hiroshima 730, Japan

[2] Daiichi Giken Co Ltd, Daiichi, Japan

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 2010年 / 101卷 / 08期

关键词：

Edgeworth expansion; Error bound; High dimension; Likelihood ratio;

D O I：

10.1016/j.jmva.2010.03.014

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：

In this paper, we calculate Edgeworth expansion of a test statistic on independence when some of the parameters are large, and simulate the goodness of fit of its approximation. We also calculate an error bound for Edgeworth expansion. Some tables of the error bound are given, which show that the derived bound is sufficiently small for practical use. (C) 2010 Elsevier Inc. All rights reserved.

引用

页码：1806 / 1813

页数：8

共 10 条

[1]

Anderson T. W., 1984, An introduction to multivariate statistical analysis, V2nd

[2] A GENERAL DISTRIBUTION THEORY FOR A CLASS OF LIKELIHOOD CRITERIA [J].