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MAXENTROPIC RECONSTRUCTION OF SOME PROBABILITY DISTRIBUTIONS WITH LINEAR INEQUALITY CONSTRAINTS

Abstract The maxentropic reconstruction is a technique for finding an unknown probability distribution from some known information. In this paper we obtain the maxentropic reconstruction of some probability distributions from the knowledge of a prior distribution and of some lower and upper bounds for the mean values of some random variables. For this we use the Csiszár’s I-projection theorems and the geometric programming method. If some average values of the prior distribution are computed, we obtain a refined form of our solution. Finally, we give several examples for this approach.