Stochastic Data Analysis

Simulation and emulation. Structure and construction of simulation models. Production of random numbers and random variables. Time flow mechanisms. Stochastic interactive simulation models. Simulation of events, simulation of activities. Simulation languages. Development of simulation programs, specialized simulation languages. Analysis of results, validation and verification of results. Techniques for determining mathematical models from data-measurements of critical system / process quantities. Dynamic systems models, modeling as a black box, retrospective model parameterization algorithms, model evaluation, data preprocessing, practical systems recognition issues.