The Features of Statistical Decision Making in Environmental Monitoring Systems

This article develops statistical decision-making methods for classical and sequential procedures under conditions of limited observation volume based on remote and contact measurement data. A comparative analysis is conducted for classical and sequential statistical decision-making procedures. Based on this analysis, the possibilities of their application under conditions of fragmentary in time and fragmentary in space measurement data are determined. Algorithms and computational procedures for classical and sequential analysis are considered. A unified automated statistical decision-making system for both procedures is developed, which has a wide range of functions and uses a hierarchical menu.