METHODS OF MATHEMATICAL STATISTICS AND ECONOMETRY UNDER UNCERTAINTY ON THE BASIS OF REGULARIZING BAYESIAN APPROACH

Authors

S.V. SMOKE

Abstract

A brief history of Bayesian statistics and econometrics is given. The requirements to the mathematical methods of statistics and econometrics are determined to solve modern technical and socio-economic problems in the conditions of information uncertainty. A regularizing Bayesian approach and Bayesian intelligent technologies are proposed that fully meet the set requirements. The concept of Bayesian statistics and Bayesian econometrics is given under conditions of significant uncertainty based on the BPO. Examples of solving statistical and econometric problems based on the proposed methodology and technologies are given.

Keywords

mathematical statistics, econometrics, regularizing Bayesian approach, information uncertainty, intelligent technologies.