The method of selecting the best distribution law for continuous random variables on the basis of inverse mapping

The article describes a new method of identification of the law of distribution of a continuous random variable. The method is based on the selection from a given set of models of the distributions of such law distribution, which would be most consistent with the experimental data sample. The idea of the method is a continuous mapping of an empirical sampling distribution into the standard line. For each distribution model the functional value is determined. It is equal to the RMS error value is displayed into standard line. As a result, as the most probable law for initial sampling researchers select the law for which the corresponding value of the functional will be minimum. The examples of the method implementation using statistical tests based on a Monte-Carlo technique are given.