Testing convex hypotheses on the mean of a Gaussian vector. Application to testing qualitative hypotheses on a regression function

被引:31
|
作者
Baraud, Y
Huet, S
Laurent, B
机构
[1] Univ Nice, Lab JA Dieudonne, CNRS, UMR 6621, F-06108 Nice, France
[2] INRA, Lab Biometrie, F-78352 Jouy En Josas, France
[3] INSA, Dept GMM, F-31077 Toulouse, France
来源
ANNALS OF STATISTICS | 2005年 / 33卷 / 01期
关键词
tests of qualitative hypotheses; nonparametric test; test of positivity; test of monotonicity; test of convexity; rate of testing; Gaussian regression;
D O I
10.1214/009053604000000896
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 propose a general methodology, based on multiple testing, for testing that the mean Of a Gaussian) vector in R(n) belongs to a convex set. We show that the test achieves its nominal level. and characterize a class of vectors over which the tests achieve a prescribed power, In the functional regression model this general methodology is applied to test some qualitative hypotheses oil the regression function. For example. we (est that the regression function is positive. increasing, convex, or more generally, satisfies a differential inequality. Uniform separation rates over classes of smooth functions are established and a comparison with other results in the literature is provided. A simulation study evaluates some of the procedures for testing monotonicity.
引用
收藏
页码:214 / 257
页数:44
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