Two Sample Problem for High-dimensional Data with Unequal Covariance Matrices(Session 3b)

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概要

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• We consider a two-sample test for the mean vectors of high-dimensional data when the dimension is large compared to the sample size. In this talk, we discuss the multivariate Behrens-Fisher problem, that is, we assume that the variance-covariance matrices are not homogeneous across groups. For these situations, we propose a Dempster type test statistic. Also, we derive asymptotic null distribution and asymptotic expansion for the upper percentiles of this statistic when both the sample size and the dimension tend to infinity. Finally, we evaluate the accuracy of approximation by Monte Carlo simulation.

• 2011-11-11

著者

• Hyodo Masashi

  Graduate School Of Economics The University Of Tokyo

• Nishiyama Takahiro

  Department Of Mathematical Information Science Tokyo University Of Science

• Nishiyama Takahiro

  Department Of Mathematical Information Science Faculty Of Science Tokyo University Of Science

関連論文

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• Two Sample Problem for High-dimensional Data with Unequal Covariance Matrices(Session 3b)
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