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Empirical Bayesian classification for observations with admixture


Author: O. Sugakova
Translated by: O. I. Klesov
Original publication: Teoriya Imovirnostei ta Matematichna Statistika, tom 84 (2011).
Journal: Theor. Probability and Math. Statist. 84 (2012), 165-172
MSC (2010): Primary 62G05; Secondary 62G20
Published electronically: August 2, 2012
MathSciNet review: 2857426
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Abstract: We consider the problem of classification of an object by using observations after a numerical characteristic under the assumption that each object belongs to one of the two given classes. The distribution of the characteristic is unknown for objects of the first class but is assumed to be symmetric. The distribution for the second class is known. We construct an empirical Bayesian classifier and prove a result concerning the asymptotic behavior of the error probability.


References [Enhancements On Off] (What's this?)

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Additional Information

O. Sugakova
Affiliation: Department of Mathematics and Theoretical Radiophysics, Faculty of Radiophysics, National Taras Shevchenko University, Academician Glushkov Avenue 4E, Kyiv 03127, Ukraine
Email: sugak@univ.kiev.ua

DOI: http://dx.doi.org/10.1090/S0094-9000-2012-00858-2
Received by editor(s): June 21, 2010
Published electronically: August 2, 2012
Article copyright: © Copyright 2012 American Mathematical Society