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在高维度中使用随机投影的更强大的双样本检验

A More Powerful Two-Sample Test in High Dimensions using Random Projection

作者:Miles Lopes;Laurent Jacob;Martin Wainwright 作者单位:EECS Department, University of California, Berkeley 加工时间:2015-06-06 信息来源:EECS 索取原文[28 页]
关键词:随机投影;双样本检验;高维度
摘 要:We consider the hypothesis testing problem of detecting a shift between the means of two multivariate normal distributions in the high-dimensional setting, allowing for the data dimension p to exceed the sample size n. Specifically, we propose a new test statistic for the two-sample test of means that integrates a random projection with the classical Hotelling T-squared statistic. Working under a high-dimensional framework with (p,n) tending to infinity, we first derive an asymptotic power function for our test, and then provide sufficient conditions for it to achieve greater power than other state-of-the-art tests. Using ROC curves generated from synthetic data, we demonstrate superior performance against competing tests in the parameter regimes anticipated by our theoretical results.
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