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In this paper, the author uses a system approach for modeling analytical laws of mortality. The article considers modeling such probabilistic characteristics as: deaths graph, survival function, mortality rate. The data tables of Russia's population mortality in 2017 are approximated by such traditional analytical laws as that of de Moivre, Gompertz, Makeham, Weibull and Еrlang. For each class of distributions the problem of estimation of unknown parameters is solved by using different methods. The quality of models fitting was tested with the help of determination coefficient. Microsoft Excel was used to find estimates of unknown parameters, calculate the value based on the resulting feature model, calculate the determination coefficient, and build selection graphs. The author draws a conclusion that distribution of population mortality is best described by Makeham model with estimated parameters.

Population Death Rate Modeling by Means of Analytical Laws Illustrated by the Example of Russia