Approaching the parameter estimation quality of maximum likelihood via generalized moments

Abstract

A simple criterion is presented for a practical construction of generalized moments that allow one to approach the theoretical Rao-Cramer limit for parameter estimation while avoiding the complexity of the maximum likelihood method in the cases of complicated probability distributions and/or very large event samples.

PS 4 pages

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