Robust hybrid tests for the two-sample location problem

被引:6
|
作者
Weichert, M [1 ]
Hothorn, LA [1 ]
机构
[1] Leibniz Univ Hannover, Unit Bioinformat, D-30419 Hannover, Germany
关键词
hybrid test; robust test; trimming; m-estimator;
D O I
10.1081/SAC-120003333
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 t-test is uniformly most powerful for comparing the location parameters of two normal distributed populations. For non-normal data, robust tests can be more powerful than the t-test. We introduce a new parametric test statistic combining the p-values of the t-test and robust tests. In the normal distribution situation, this new test has a very small power loss compared to the t-test, but in the non-normal situation higher power than the t-test. The Pitman efficiency of 3pi(-1) = 0.955 gives an upper bound on the efficiency of nonparametric tests in the normal situation. Our new test (which is parametric) exceeds the Pitman bound when the sample sizes are small.
引用
收藏
页码:175 / 187
页数:13
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