Process Simulation Using Randomized Markov Chain and Truncated Marginal Distribution

Journal of Supercomputing, 22, pp. 69-85, May 2002 (SCI)

Alexei S. Rodionov, Hyunseung Choo, and Hee Y. Youn

Abstract

Generating pseudo random objects is one of the key issues in computer simulation of complex systems. Most earlier simulation systems include procedures for the generation of independent and identically distributed random variables or some classical random processes, such as white noise. In this paper we propose a new approach to the generation of wide ranges of processes that are characterized by marginal distribution and autocorrelation function that are significant in many cases. The proposed algorithm is based on the use of truncated distribution that gives more simplicity and efficiency in comparison with the previous one. The effectiveness of the proposed algorithm is verified using computer simulation of various real examples.

 

Keyword

Autocorrelation, Newton optimization, Random process, Randomized Markov chain, simulation

 

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