Simulation optimization and correlation with multistage Monte Carlo optimization

The importance of simulation in our complex computer laden 21st century cannot be overstated. Also optimization is of vital concern in business, industry, engineering and science. These fields frequently require analyzing sets of data to see whether variables are correlated or can be used in forecasting. Presented here is an attempt to combine these three areas with a new correlation statistic for single or multivariate, linear or nonlinear work that can be calculated using the multistage Monte Carlo optimization algorithm in our computer age. Several examples will be presented along with an explanation of how to simulate the sampling distributions for subsequent testing of correlation hypotheses.