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In many social, economical, biological and medical studies, one objective is to classify a subject into one of several classes based on a set of variables observed from the subject. Because the prob...
We show that scale-adjusted versions of the centroid-based classi- fier enjoys optimal properties when used to discriminate between two very high-dimensional populations where the principal differen...
We propose a two-sample test for the means of high-dimensional data when the data dimension is much larger than the sample size. Hotelling’s classical T 2 test does not work for this large p, small...
In this paper, we study inference for high-dimensional data characterized by small sample sizes relative to the dimension of the data. In particular, we provide an infinite-dimensional framework to ...
The estimation of Bayesian networks given high-dimensional data sets, in particular given gene expression data sets, has been the focus of much recent research. While there are many methods availabl...
Student's t statistic is nding applications today that were never envisaged when it was introduced more than a century ago. Many of these applications rely on properties, for example robustness aga...

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