Data Typology Using Technologies for Separating Mixtures of Probability Distributions

Abstract

The authors studied heterogeneous samples (for a number of statistical populations) taken from finite mixtures of probability distribu- tions, which reflect a number of socio-economic characteristics of the Russian society, using the information resources of the Federal State Statistics Service; in this case the number of mixing distributions (components), as well as their corresponding weights and parameters, may be unknown. In terms of content, the problem of separation (decomposition) of mixtures can be reduced to estimating unknown parameters of mixing distributions and their weights.The article considers and discusses methods for solving this problem, their advantages and disadvantages, conditions and areas of application. In the study the decomposition of mixtures of probability distributions on the population of subjects of the RussianFederation was carried out according to three interrelated statistical indicators – the unemployment rate, the poverty rate, the level of violence. These indicators can be considered as statistical measure of achieving sustainable development goals at the regional level and, at the same time, measures of socio-economic «health» of territory. Typologies of subjects of the Russian Federation were carried out according to the listed indicators. A cross-comparison of the results of the obtained typological groupings was performed, which also made it possible to identify the subjects of the Russian Federation that differ in both negative and positive trends in the context of the indicators under consideration.The authors underline that the results of the study can be used by the authorities to develop specific measures for the socio-economic development of Russia and its regions.