Correlated Random Variables in Probabilistic Simulation

A new efficient technique to impose the statistical correlation when using Monte Carlo type method for statistical analysis of computational problems is proposed. The technique is based on stochastic optimization method called Simulated Annealing. The comparison with other techniques presently used and intensive numerical testing showed the superiority and robustness of the method. No significant obstacles have been found working also with large problems (large number of random variables). Advantages and limitations of the approach will be discussed. Remarks on positive definiteness of target correlation matrix will be made. Numerical examples show the efficiency of the method