Mathematical methods based on statistics have been used in sociology for a long time. The functioning of socio-economic and socio-politic systems is a complex process, which is caused by a number of various factors. Thus, the construction of models of socio-economic and socio-politic processes requires solving problems of both the decomposition of structures and processes, and their integration into a single system model, taking into account the changing conditions of the external environment. Mathematical modeling of such problems can be carried out by methods of network analysis or game theory, which allows finding optimal strategies for the behavior of competitive parties. Asymptotic formulations have a central role in game theory, since, due to the complex strategic nature, explicit solutions can be found only in very rare cases. A large number of models created to study complex social processes that occur in society are dynamical systems, or non-autonomous differential equations, or difference equations with a large number of parameters in any cases. In this situation, it is important to choose an appropriate tool for studying the behavior of such systems. In this paper, generalized Poisson delta operators are considered as approximating aggregates, since periodic processes, which are subdivided into harmonic and polyharmonic, provide the internal integrity of complex systems and their dynamic functioning. Questions of the asymptotic behavior of the exact upper bounds for approximations by generalized Poisson delta operators on classes of periodic functions that satisfy the Lipschitz condition are also studied. The received formulas provide a solution to the Kolmogorov-Nikol’ski problem for generalized Poisson delta operators and Lipschitz classes. The proof is based on the use of formulas that give integral representations of the deviations of linear methods generated by linear processes of summation of Fourier series on sets of periodic functions in the uniform metric obtained in the works of L.I. Bausov. The results can be an effective tool for modeling the processes of social dynamics.
Goodness-of-Fit Tests for Bivariate Time Series of Counts
