
Accession Number : ADA139315
Title : Estimating Time Averages via RandomlySpaced Observations.
Descriptive Note : Technical summary rept.,
Corporate Author : WISCONSIN UNIVMADISON MATHEMATICS RESEARCH CENTER
Personal Author(s) : Fox,B L ; Glynn,P W
PDF Url : ADA139315
Report Date : Jan 1984
Pagination or Media Count : 24
Abstract : In many stochastic systems, one is interested in estimating steadystate expected values. When Monte Carlo simulation is used to estimate such parameters, an assessment of accuracy, in the form of confidence intervals, is often required. Most procedures for producing such confidence intervals require that the simulation be sampled so that the time increments between observations are all equal. This is difficult to accomplish in a discreteevent simulation, since the clock which drives the simulation is incremented in a random fashion. To estimate continuoustime averages via randomlyspaced observations of discreteevent systems, the authors develop a pointprocess framework and use it to generalize both regenerative and stationaryprocess oriented simulation methodologies. They give consistent estimators, central limit theorems, and an effective biasreducing jackknife. The impact of indirect estimation of transaction (customer) averages is discussed.
Descriptors : *Numerical methods and procedures, *Estimates, *Time intervals, *Confidence limits, Simulation, Theorems, Observation, Accuracy
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE