Simulation of Input Data Flows for Stochastic Models of Discrete Systems

A problem of simulation of random-valued input data is considered for stochastic models of discrete systems. For simulation of a steady random process, ARTA (Auto-Regressive-To-Anything) processes with arbitrary unconditional distribution of probability and self-correction structure are chosen. Algorithms of estimation of parameters of an ARTA-process using the realization of the random process and generation of the ARTA-process are presented.