Analysing steady-state simulation output using vector autoregressive processes with exogenous variables

J Martens (), R Peeters () and F Put
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J Martens: Katholieke Universiteit Leuven
R Peeters: Katholieke Universiteit Leuven
F Put: Katholieke Universiteit Leuven

Journal of the Operational Research Society, 2009, vol. 60, issue 5, 696-705

Abstract: Abstract A simulation study often requires computation of a point estimate and confidence region for the steady-state mean of a stochastic output process. The literature offers a variety of statistical techniques, including replication/deletion, the batch-means method, and spectrum analysis. We present a new multivariate output-analysis technique that is based on the general autoregressive time-series model with exogenous variables to set up a joint confidence region for the steady-state mean. We demonstrate our technique by an extensive computational experiment, and show that it performs at least as well as other output-analysis techniques, without having some of their drawbacks.

Keywords: simulation; output analysis; multivariate time-series analysis (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1057/palgrave.jors.2602595

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