Two sample mean vectors comparison hypothesis testing problems often emerge in modern biostatistics. Many tests are proposed for detecting relatively dense signals with somewhat dense nonzero components in mean vectors differences. One kind of these tests is based on some quadratic forms about two sample mean vectors differences. Another kind of these tests is based on some quadratic forms about studentized version of two sample mean vectors differences. In this article, we propose a bootstrap test by adopting stationary bootstrap scheme to calculate p value of a typical test which is based on a quadratic form about studentized version of two sample mean vectors differences. Extensive simulations are conducted to compare performances of the bootstrap test with other existing typical tests. We also apply the bootstrap test to a real genetic data analysis about breast cancer.

在现代生物统计学中经常出现两个样本均值向量比较假设检验问题。提出了许多测试来检测相对密度较高的信号，这些信号在平均矢量差中具有一定密度的非零分量。这些测试中的一种是基于关于两个样本均值向量差的一些二次形式。这些测试的另一种是基于关于两个样本均值向量差的学生化版本的一些二次形式。在本文中，我们提出了一种采用固定引导程序来计算p的引导测试。基于关于两个样本均值向量差的学生化版本的二次形式的典型检验的值。进行了广泛的仿真，以比较自举测试与其他现有典型测试的性能。我们还将Bootstrap测试应用于关于乳腺癌的真实遗传数据分析。