The use of variance reduction, relative error and bias in testing the performance of M/G/1 retrial queues estimators in Monte Carlo simulation

Abstract

This paper deals with Monte Carlo simulation and focuses on the use of the concepts of variance reduction, relative error and bias in testing the performance of stationary M/G/1 retrial queues estimators using either Random Sampling (RS) or Refined Descriptive Sampling (RDS) to generate input samples. For this purpose, a software under Linux system using the C compiler was designed and realized providing the performance measures of such system and the statistical concepts of bias, relative error and accuracy using both sampling methods. As a conclusion, it has been shown that the performance of stationary M/G/1 retrial queues estimators is better using RDS than RS and sometimes by a substantial variance reduction factor.