AN EFFECTIVE GENERATION ALGORITHM OF RANDOM VARIABLES WITH PIECEWISE LINEAR DISTRIBUTION DENSITIES

Abstract

The PURPOSE of the article is to improve the efficiency of simulation modeling in various subject domains through the use of piecewise linear functions that allow high accuracy in the determination of arbitrary random variables. METHODS. It is proposed to use piecewise linear functions to specify the density of random variables under the transformation of a standard random variable to build simulation models. RESULTS. Based on the type of the random variable density specified by a piecewise linear function three algorithms of action sequence have been proposed for generating the mixture of the components that must have a defined discrete probability distribution. CONCLUSION. Due to their versatility the piecewise linear functions when applied provide sufficiently high generation accuracy of arbitrary random variables. A high simulation efficiency of piecewise-linear functions can improve the accuracy and adequacy of simulation models in different subject domains.