Efficient and adaptive nonparametric test for the two-sample problem

被引：0
|
作者：
Ducharme, GR [1 ]
Ledwina, T
机构：
[1] Univ Montpellier 2, F-34095 Montpellier 5, France
[2] Polish Acad Sci, PL-00901 Warsaw, Poland
来源：
ANNALS OF STATISTICS | 2003年 / 31卷 / 06期
关键词：
adaptive test; efficient test; model selection; nonparametric test; two-sample problem;
D O I：
暂无
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：
The notion of efficient test for a Euclidean parameter in a semiparametric model was introduced by Stein [Proc. Third Berkeley Symp. Math. Statist. Probab. 1 (1956) 187-195]. Such tests are locally most powerful for a wide class of infinite-dimensional nuisance parameters. The first formal application of this notion to a suitably parametrized two-sample problem was provided by Hajek [Ann. Math. Statist. 33 (1962) 1124-1147]. However, this and subsequent solutions appear to be not well-suited for practical applications. This article aims to show that an adaptive two-sample test introduced recently by Janic-Wroblewska and Ledwina [Scand. J Statist. 27 (2000) 281-297] is locally most powerful under a more realistic setting.
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收藏
页码：2036 / 2058
页数：23
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