MULTIPLE COMPARISON PROCEDURE OF DUNNETT'S TYPE FOR MULTIVARIATE NORMAL MEANS

Robust Semiparametric Optimal Testing Procedure for Multiple Normal Means

In high-dimensional gene expression experiments such as microarray and RNA-seq experiments, the number of measured variables is huge while the number of replicates is small. As a consequence, hypothesis testing is challenging because the power of tests can be very low after controlling multiple testing error. Optimal testing procedures with high average power while controlling false discovery r...

Comparing Methods of Testing the Common Means for Several Multivariate Normal Populations

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Ensemble Minimax Estimation for Multivariate Normal Means

This article discusses estimation of a heteroscedastic multivariate normal mean in terms of the ensemble risk. We first derive the ensemble minimaxity properties of various estimators that shrink towards zero. We then generalize our results to the case where the variances are given as a common unknown but estimable chi-squared random variable scaled by different known factors. We further provid...

Multiple Comparison Methods for Means

Multiple comparison methods (MCMs) are used to investigate differences between pairs of population means or, more generally, between subsets of population means using sample data. Although several such methods are commonly available in statistical software packages, users may be poorly informed about the appropriate method(s) to use and/or the correct way to interpret the results. This paper cl...

Screening for a Multivariate Mixture Normal Distribution