Noninverse correlation induction: guidelines for algorithm development

摘要

We propose guidelines for future development of random-variate generators that are capable of inducing statistical dependence between simulation replications without incurring the computational burden of numerically inverting the distribution function. Two examples are given: an exponential generator using the inverse transformation and a generic acceptance—rejection generator based on an existing beta generator. A driver program and illustrative Monte Carlo results are discussed.