Abstract
The statistical analysis of simulation output has been the primary focus of recent research in simulation methodology. Methods have been developed which permit the simulator to construct confidence intervals for steady-state characteristics of the system being simulated. The principal methods in current use are autoregressive modeling, batch means, regenerative, and replication. With the exception of the replication method, all methods are bas d on just one simulation run. These methods for constructing confidence intervals are all based on central limit theorems for the underlying stochastic processes being simulated. Thus all methods are only valid asymptotically for long simulation runs.
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© 1982 Birkhäuser Boston, Inc.
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Glynn, P.W., Iglehart, D.L. (1982). Simulation Output Analysis for General State Space Markov Chains. In: Disney, R.L., Ott, T.J. (eds) Applied Probability-Computer Science: The Interface Volume 1. Progress in Computer Science, vol 2. Birkhäuser Boston. https://doi.org/10.1007/978-1-4612-5791-2_3
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DOI: https://doi.org/10.1007/978-1-4612-5791-2_3
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