Simulating Stable Stochastic Systems, I: General Multiserver Queues
Journal of the ACM (JACM)
Analysis of Performability for Stochastic Models of Fault-Tolerant Systems
IEEE Transactions on Computers
Control procedures for slotted Aloha systems that achieve stability
SIGCOMM '86 Proceedings of the ACM SIGCOMM conference on Communications architectures & protocols
Disk arm movement in anticipation of future requests
ACM Transactions on Computer Systems (TOCS)
A review of advanced methods for simulation output analysis
WSC '94 Proceedings of the 26th conference on Winter simulation
Advanced methods for simulation output analysis
WSC '95 Proceedings of the 27th conference on Winter simulation
Advanced simulation output analysis for a single system
WSC '93 Proceedings of the 25th conference on Winter simulation
On the efficiency of the splitting and roulette approach for sensitivity analysis
Proceedings of the 29th conference on Winter simulation
Advanced methods for simulation output analysi8
Proceedings of the 30th conference on Winter simulation
Simulating Stable Stochastic Systems, VI: Quantile Estimation
Journal of the ACM (JACM)
Estimating the Mean of a Correlated Binary Sequence with an Application to Discrete Event Simulation
Journal of the ACM (JACM)
Regenerative Simulation with Internal Controls
Journal of the ACM (JACM)
Achieving specific accuracy in simulation output analysis
Communications of the ACM
Output analysis: output analysis for simulations
Proceedings of the 32nd conference on Winter simulation
Output analysis: output data analysis for simulations
Proceedings of the 33nd conference on Winter simulation
WSC '83 Proceedings of the 15th conference on Winter simulation - Volume 1
Confidence intervals in discrete event simulation: A state-of-the-art survey
WSC '76 Proceedings of the 76 Bicentennial conference on Winter simulation
Simulation of merge junctions in a dynamically entrained automated guideway transit system
WSC '79 Proceedings of the 11th conference on Winter simulation - Volume 2
Statistical analysis of simulation output data
ANSS '76 Proceedings of the 4th symposium on Simulation of computer systems
When to stop a simulation run: A case study
ANSS '76 Proceedings of the 4th symposium on Simulation of computer systems
Literature review bibliography of simulation optimitation
WSC '77 Proceedings of the 9th conference on Winter simulation - Volume 1
Variance reduction techniques for simulating Markov chains
WSC '77 Proceedings of the 9th conference on Winter simulation - Volume 1
A critical overview of computer performance evaluation
ICSE '76 Proceedings of the 2nd international conference on Software engineering
A tutorial on statistical analysis of simulation output data
WSC '80 Proceedings of the 12th conference on Winter simulation
ACM '75 Proceedings of the 1975 annual conference
Statistical analysis of discrete—event simulations
WSC '74 Proceedings of the 7th conference on Winter simulation - Volume 2
Statistical analysis of simulation output: output data analysis for simulations
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
A comparison on two techniques for collecting statistics in simulation
ACM SIGSIM Simulation Digest
Statistical analysis of simulation output data
ACM SIGSIM Simulation Digest
VLDB '77 Proceedings of the third international conference on Very large data bases - Volume 3
RESQ: a package for solution of generalized queueing networks
AFIPS '77 Proceedings of the June 13-16, 1977, national computer conference
Variance reduction techniques for the simulation of Markov processes, I: multiple estimates
IBM Journal of Research and Development
Sequential stopping rules for the regenerative method of simulation
IBM Journal of Research and Development
Approximate analysis of central server models
IBM Journal of Research and Development
A brief history of simulation revisited
Proceedings of the Winter Simulation Conference
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A technique for simulating GI/G/s queues is shown to apply to simulations of discrete and continuous-time Markov chains. It is possible to address questions of simulation run duration and of starting and stopping simulations because of the existence of a random grouping of observations which produces independent identically distributed blocks from the start of the simulation. This grouping allows confidence intervals to be obtained for a general function of the steady-state distribution of the Markov chain. The technique is illustrated with simulation of an (s, S) inventory model in discrete time and the classical repairman problem in continuous time. Consideration is also given to determining system sensitivity to errors and uncertainty in the input parameters.