Confidence intervals based on steady-state continuous-time statistics

Authors:
Ardavan Nozari
Affiliations:
AT&T Engineering Research Center, Murray Hill, NJ 07974, USA
Venue:
Operations Research Letters
Year:
1986

Citing 3
Cited 0

Simulating Stable Stochastic Systems, I: General Multiserver Queues

Journal of the ACM (JACM)
A spectral method for confidence interval generation and run length control in simulations

Communications of the ACM - Special issue on simulation modeling and statistical computing
Principles of Discrete Event Simulation

Principles of Discrete Event Simulation

Quantified Score

Hi-index	0.00

Visualization

Abstract

In steady-state computer simulation experiments, continuous-time statistics are used to estimate a variety of systems' parameters. In this paper we present formulas for estimating confidence intervals based on such statistics. Our formulas are extensions of the work of Schruben on 'Standardized Time Series' for discrete-time observations. We conduct a Monte Carlo study to examine the behavior of our estimators. Our estimators work quite well and our results are consistent with those of Schruben for discrete-time observations.