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An application of linear feature selection to estimation of proportions
Authors:L. F. Guseman Jr.  Jay R. Walton
Affiliation:1. Department of Mathematics , Texas A&2. M University College Station , Texas, 77843
Abstract:
Let X be a random n-vector whose density function is given by a mixture of known multivariate normal density functions where the corresponding mixture proportions (a priori probabilities) are unknown. We present a numerically tractable method for obtaining estimates of the mixture proportions based on the linear feature selection technique of Guseman, Peters and Walker (1975).
Keywords:multivariate normal populations  Bayesian classification  probability of misclassification  unbiased estimates  constrained least squares
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