北京科学与工程计算研究院学术报告之八十三

报告人/Speaker: 童铁军教授, 香港浸会大学


报告题目/Title: Diagonal Likelihood Ratio Test for Equality of Mean Vectors in High-Dimensional Data


时间/Date & Time: November 13, 2018, 9:40-10:40


地点/Location: M842, BISEC


报告摘要/Abstract:

We propose a likelihood ratio test framework for testing normal mean vectors in high-dimensional data under two common scenarios: the one-sample test and the two-sample test with equal covariance matrices. We derive the test statistics under the assumption that the covariance matrices follow a diagonal matrix structure. In comparison with the diagonal Hotelling’s tests, our proposed test statistics display some interesting characteristics. In particular, they are a summation of the log-transformed squared t-statistics rather than a direct summation of those components. More importantly, to derive the asymptotic normality of our test statistics under the null and local alternative hypotheses, we do not require the assumption that the covariance matrix follows a diagonal matrix structure. As a consequence, our proposed test methods are very flexible and can be widely applied in practice. Finally, simulation studies and a real data analysis are also conducted to demonstrate the advantages of our likelihood ratio test method.

报告人简介/About the speaker:

童铁军,香港浸会大学副教授,国际统计协会当选会员,主要科研方向为非参数回归,高维数据分析,Meta分析和循证医学。童教授于2005年在美国加州大学圣巴巴拉分校获得统计学博士学位,2005-2007年在美国耶鲁大学从事生物统计博士后研究,2007-2011年在科罗拉多大学博尔德分校担任助理教授,目前在香港浸会大学数学系担任终身副教授。已在国际著名的学术期刊Journal of the American Statistical Association,Biometrika,Statistical Science, Journal of Machine Learning Research等发表论文50余篇,单篇论文最高引用460次。目前主持香港研究資助局项目,香港卫生署健康与医学研究基金项目,国家自然科学基金面上项目等校内外科研项目多项。