Universal Algorithm for Estimating the Measured Value by the Data of a Repeated Experiment and Its Simplification
A universal solution of the problem of estimating parameters of an a priori given arbitrary distribution by the data of a repeated experiment is presented. The properties of the solution with the structure of the uncertainty function have been analyzed. The algorithm converting data of an n-fold experiment and a priori information given in the form of a standardized distribution into estimates of the measured parameter value given as an uncertainty function has been investigated. Variants of simplifying the algorithm in conformity with practical requirements have been considered.
Keywordsrank measure estimation of parameters repeated experiment
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