On classifying observations when one population is a mixture of normals
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Some simple models for the mixture of distribution problems are considered. Two possible alternatives to the rather complex optimal discriminant function rule are mentioned. The performance of the BC method is never as satisfactory as the QDF method and in some cases it is far worse than the QDF method. The QDF can be used whenever sufficient numbers of observations are available to provide reasonably good estimates of means and covariances.
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