Asymptotic minimaxity of chi-square tests

被引：6
|
作者：
Ermakov, MS [1 ]
机构：
[1] Russian Acad Sci, Inst Mech Engn Problems, St Petersburg 199178, Russia
来源：
THEORY OF PROBABILITY AND ITS APPLICATIONS | 1998年 / 42卷 / 04期
关键词：
chi-square tests; asymptotic efficiency; asymptotic normality; asymptotically minimax approach; goodness-of-fit testing;
D O I：
10.1137/S0040585X97976441
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：
We consider the asymptotic behavior of chi-square tests when a number k(n) of cells increases as the sample size n grows. For such a setting we show that a sequence of chi-square tests is asymptotically minimax if k(n) = o(n(2)) as n --> infinity. The proof makes use of a theorem about asymptotic normality of chi-square test statistics obtained under new assumptions.
引用
收藏
页码：589 / 610
页数：22
相关论文
共 50 条
12345