A Kolmogorov-type test for monotonicity of regression

被引：25
|
作者：
Durot, C [1 ]
机构：
[1] Univ Paris 11, Lab Probabilites Stat & Modelisat, F-91405 Orsay, France
来源：
STATISTICS & PROBABILITY LETTERS | 2003年 / 63卷 / 04期
关键词：
test for monotonicity; least concave majorant; local alternative; power; nonparametric test;
D O I：
10.1016/S0167-7152(03)00122-6
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：
A new nonparametric procedure for testing monotonicity of a regression mean is proposed. The test is shown to have prescribed asymptotic level and good asymptotic power. It is based on the supremum distance from an empirical process to its least concave majorant and is very easily implementable. A simulation study is reported to demonstrate finite sample behavior of the procedure. (C) 2003 Elsevier B.V. All rights reserved.
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页码：425 / 433
页数：9
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