Methods for statistical data analysis and probability modeling play an increasingly important role in learning about natural and social phenomena, especially in connection with the availability and spread of information technology. Natural, technical andeconomical sciences spawn a growing demand for statistical modeling of complex dynamically evolving systems in the presence of randomness or uncertainty and for the utilization of such models for reliable prediction and effective decision making. Among these problems are analyses of medical and epidemiological data, including longitudinal and spacial models, modeling of environmental processes, meteorological data and climate change, economical development trends with an impact of external and internalfactors, problems of reliability of complex technical systems. This project is focused on general and special regression models, as they are the most common means of dynamical statistical modeling.