A stochastic estimation algorithm with observation averaging

An algorithm for the constrained problem of estimating the regression coefficients is presented. The algorithm is based on the idea of direct averaging of the observations in order to estimate the search direction. It is shown that if the true parameter belongs to the permitted set, then the algorithm delivers asymptotically optimal estimates of the parameter. Finite convergence of the method is proved when the true parameter lies outside the permitted set.<
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