A bayes procedure for selecting the population with the largestpth quantile |
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Authors: | Khursheed Alam |
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Affiliation: | (1) Clemenson University, Clemson, USA |
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Abstract: | Summary The Bayes method is seldom applied to nonparametric statistical problems, for the reason that it is hard to find mathematically tractable prior distributions on a set of probability measures. However, it is found that the Dirichlet process generates randomly a family of probability distributions which can be taken as a family of prior distributions for an application of the Bayes method to such problems. This paper presents a Bayesian analysis of a nonparametric problem of selecting a distribution with the largestpth quantile value, fromk≧2 given distributions. It is assumed a priori that the given distributions have been generated from a Dirichlet process. This work was supported by the U.S. Office of Naval Research under Contract No. 00014-75-C-0451. |
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Keywords: | Ranking and Selection population quantile Bayes rule dirichlet process |
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