A test for k sample Behrens-Fisher problem in high dimensional data

2017/10/22 by Mingxiang Cao, Junyong Park, Cao, Mingxiang +3 · 1 citation
Mathematics · Computer Science · #Stochastic processes and statistical mechanics #Random Matrices and Applications #Bayesian Methods and Mixture Models

paper · pdf · doi:10.48550/arxiv.1710.07878

Abstract

In this paper, the k sample Behrens-Fisher problem is investigated in high dimensional setting. We propose a new test statistic and demonstrate that the proposed test is expected to have more powers than some existing test especially when sample sizes are unbalanced. We provide theoretical investigation as well as numerical studies on both sizes and powers of the proposed tests and existing test. Both theoretical comparison of the asymptotic power functions and numerical studies show that the proposed test tends to have more powers than existing test in many cases of unbalanced sample sizes.

Citations

• A test for the mean vector with fewer observations than the dimension under non-normality
• A two sample test in high dimensional data
• A test for the mean vector with fewer observations than the dimension

Cited by

• A unified approach to the Behrens-Fisher problem

Related

• Two-sample Behrens--Fisher problems for high-dimensional data: a normal reference F-type test
• Finite-sample bounds for the multivariate Behrens-Fisher distribution with proportional covariances
• Te Test: A New Non-asymptotic T-test for Behrens-Fisher Problems
• A New Approach to the Nonparametric Behrens-Fisher Problem with Compatible Confidence Intervals
• A unified approach to the Behrens-Fisher problem