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    A Two Sample Test for Mean Vectors with Unequal Covariance Matrices in High–Dimensional Data 

    Paranut Sukcharoen; Samruam Chongcharoen (NIDA, 4/4/19)

    In this paper, we proposed a new testing statistic for testing the equality of mean vectors from two multivariate normal populations when the covariance matrices are unknown and unequal in high–dimensional data. A new test is proposed based on the idea of keeping more information from the sample covariance matrices as much as possible. A proposed test is invariant under scalar transformations. We showed that the asymptotic distribution of proposed statistic is standard normal distribution when number of random variables approach infinity. We also ...