Comparison of Discrimination Methods for High Dimensional Data

M. S. Srivastava and Tatsuya Kubokawa
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M. S. Srivastava: Department of Statistics, University of Toronto
Tatsuya Kubokawa: Faculty of Economics, University of Tokyo

No CIRJE-F-324, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: In microarray experiments, the dimension p of the data is very large but there are only few observations N on the subjects/patients. In this article, the problem of classifying a subject into one of the two groups, when p is large, is considered. Three procedures based on Moore-Penrose inverse of the sample covariance matrix and an empirical Bayes estimate of the precision matrix are proposed and compared with the DLDA procedure.

Pages: 17 pages
Date: 2005-03
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Persistent link: https://EconPapers.repec.org/RePEc:tky:fseres:2005cf324

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