Separating a mixture of two normals with proportional covariances |
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Authors: | Salem S. Reyen John J. Miller Edward J. Wegman |
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Affiliation: | 1.Department of Applied and Engineering Statistics, MSN 4A7,George Mason University,Fairfax,USA |
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Abstract: | We propose a simple affine equivariant clustering method, based on the idea of best linear classification, for samples from a mixture of two multivariate normal distributions with different mean vectors but proportional covariance matrices. To ameliorate the curse of dimensionality, a non-parametric approach to find candidates for a best linear discriminant function is presented. By using simulation studies and a real example, we show that for large samples in high dimensions, the proposed method can be a useful supplement to general-purpose multivariate outlier detection methods. |
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