Generalization of Bayesian Rule of Many Simple Hypotheses Testing

There are different methods of statistical hypotheses testing. 1 – 4 Among them, a special place has Bayesian approach. A generalization of Bayesian rule of many hypotheses testing is given below. It consists in increasing of decision rule dimensionality with respect to the number of tested hypoteses, which allows to make decisions more differentiated than in the classical case and to state, instead of unconstrained optimozation problem, constrained one that enables to make guaranteed decisions concerning errors of true decisions rejection, which is the key point when solving a number of practical problems. These generalizations are given both for a set of simple hypotheses, each containing one space point, and hypotheses containing a finite set of separated space points.