The comparison of two samples is a problem very frequently encountered in practice. There is active interest in researching for tests that are powerful also when the data are not compatible with the assumptions of normality and equal variances – as it is common in many fields – while controlling their type-one error rate. The Yuen test is a familiar method based on trimmed means. There is no agreement in the literature about the preferable rate of trimming. This paper has two aims: to study the power of many Yuen tests with different trimming rates and propose a bootstrap test based on the combination of Yuen tests with different trimming rates. It is shown that the various Yuen tests have very different power for different distributions because the best rate of trimming depends on distribution tailweight. Conversely, the combined test is powerful irrespective to the underlying distribution.

中文翻译：

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两个样本位置问题的组合引导测试

两个样本的比较是实践中经常遇到的问题。当数据与正态性和等方差的假设不兼容时（这在许多领域很常见），同时控制它们的第一类错误率，人们对研究强大的测试也很感兴趣。Yuen 检验是一种常见的基于修整均值的方法。文献中没有关于最佳修剪率的一致意见。本文有两个目的：研究多个不同修整率的 Yuen 检验的功效，并提出一种基于不同修整率的 Yuen 检验组合的 bootstrap 检验。结果表明，各种 Yuen 检验对不同分布具有非常不同的功效，因为最佳微调率取决于分布尾重。反过来，