A Comparison of Various Non-Parametric Discriminating Procedures When the Populations Are Bivariate Exponentials
Lieberman, Jay Edward
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A comparison of the error probabilities for various discriminating rules is performed in the two population cases when nothing is known of the populations other than they are bivariate negative exponential. In most cases, the absolute difference between the error probabilities for each function was very small. However, the Euclidean distance function consistently performed as well as, and sometimes superior to any of the others studied in the this thesis.
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