The moment of inertia and the linear discriminant function
AbstractIn this note, we show that the characteristic vector of the moment of inertia matrix associated with the first or last characteristic root corresponds to the best linear discriminant function in the situation where the data is a mixture of two multivariate normal distributions with proportional covariance matrices. This result may prove useful as a part of many outlier detection methods. We also describe a small simulation study which illustrates the computational efficiency of the new method.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 71 (2005)
Issue (Month): 1 (January)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Salem Reyen & John Miller & Edward Wegman, 2009. "Separating a mixture of two normals with proportional covariances," Metrika, Springer, vol. 70(3), pages 297-314, November.
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