Two-sample test of high dimensional means under dependence
Two-sample test of high dimensional means under dependence
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相关性下高维均值的两样本检验
DOI：
10.1111/rssb.12034
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发表时间：
2014-03-01
影响因子：
5.8
通讯作者：
Xia, Yin
中科院分区：
文献类型：
--
作者：
Cai, T. Tony;Liu, Weidong;Xia, Yin
本文在高维设置中考虑了多元分析中的典型测试问题，即测试两个均值向量的相等性。我们引入了一种新的检验统计量，该统计量基于精度矩阵对数据的线性变换，其中包含变量之间的相关性。分析了检验统计量的极限零分布和检验功效。结果表明，该测试对于稀疏替代方案特别有效，并且具有一定的最优性。进行模拟研究以检查测试的数值性能并将其与文献中给出的其他测试进行比较。结果表明，所提出的测试在一系列设置中显着优于那些测试。
The paper considers in the high dimensional setting a canonical testing problem in multivariate analysis, namely testing the equality of two mean vectors. We introduce a new test statistic that is based on a linear transformation of the data by the precision matrix which incorporates the correlations between the variables. The limiting null distribution of the test statistic and the power of the test are analysed. It is shown that the test is particularly powerful against sparse alternatives and enjoys certain optimality. A simulation study is carried out to examine the numerical performance of the test and to compare it with other tests given in the literature. The results show that the test proposed significantly outperforms those tests in a range of settings.