Hybrid models for parameter estimates of socially significant behavior on the base of supershort incomplete set of observations

We provide a description of the methods for socially significant behavior modeling and estimation on the base of supershort incomplete set of observations. We consider agent-based modeling, statistical approach including small samples analysis, time series analysis and their application to the described problem. Finally, we describe advantages of probabilistic graphical models for representation of socially significant behavior.