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Classification with multiple independent measurements under separate sampling scheme
by
Subhash Bagui
Department of Mathematics and Statistics, University of West Florida
Coauthors: Sikha Bagui, A. Chatterjee, and K.L. Mehra
In this article, we consider the problem of classifying independent repeated (multiple) observations coming from the same population under a separate sampling scheme. We derive the asymptotic risk of the proposed NN type classification rule and obtain upper and lower bounds for it in specific cases in terms of Bayes risk. Using a monte carlo simulation study, we show that, as increases, the classification risk decreases.
Date received: September 23, 2005
Copyright © 2005 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # caqt-89.