Methods for estimating proportions of convex combinations of normals using linear feature selection |
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Authors: | LF Guseman Jr Jay R Walton |
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Institution: | 1. Department of Mathematics , Texas A&2. M University , College Station, Texas, 77843 |
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Abstract: | Let X be a random n-vector whose density function is given by a mixtur.e of two density functions, h1 and h2 with unknown mixture proportions, Y1 and Y2 We assume that each of h1 and h2 is a convex combination of known multivariate normal density functions whose corresponding mixture proportions are also unknown. We present three numerically tractable methods for estimating Y1 and Y2 related to the technique of Guseman and Walton (1977), and based on the linear feature selection technique of Guseman, Peters and Walker (1975). |
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Keywords: | multivariate normal populations bayesian classification probability of misclassification unbaised estimates constrained least squares |
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