There has been a great interest in the use of variance reduction techniques VRTs in simulation output analysis for the purpose of improving accuracy when the performance measurements of complex production and service systems are estimated. Therefore, a simulation output analysis to improve the accuracy and reliability of the output is required. The performance measurements are required to have ...

We present an algorithm GRAND for generating normally distributed pseudo-random numbers, assuming the existence of a source of uniform random numbers. The method is exact, apart from the effect of rounding errors. The idea of using a rejection technique to avoid any elementary function evaluations is due to Von Neumann [4] and Forsythe [3], but our implementation requires less uniform samples p...

We consider the use of the Fisher–Snedecor F distribution, which is defined as the ratio of two chi-squared variates, to model composite fading channels. In this context, the root-mean-square power of a Nakagami-m signal is assumed to be subject to variations induced by an inverse Nakagamim random variable. Comparisons with physical channel data demonstrate that the proposed composite fading mo...

This paper details a new control-variate splitting scheme yielding an unbiased esti-mator of the mean response and an unbiased estimator of the variance of the first estimator. This scheme also yields an asymptotically exact confidence interval for the mean response. We present analytical and empirical performance comparisons of this scheme versus other control-variate procedures.

The method of control variates has been intensively used for reducing the variance of estimated (linear) regression metamodels in simulation experiments. In contrast to previous studies, this paper presents a procedure for applying multiple control variates when the objective is to estimate and validate a nonlinear regression metamodel for a single response, in terms of selected decision variab...

We apply a simple queuing-experiment using parallel streams of random numbers to exhibit shortcomings of the OMNeT++ random number generator. As an improvement we implement more modern generators.

These sums appear in various branches of mathematics: Number Theory, Algebraic Geometry, and Topology; they have consequently been studied extensively in various contexts. These include the quadratic reciprocity law ([13]), random number generators ([12]), group actions on complex manifolds ([9]), and lattice point problems ([14], [5]). Dedekind was the first to show the following reciprocity l...