Abstract
We revisit and update the autoregressive-output-analysis method for constructing a confidence interval for the steady-state mean of a simulated process by using Rissanen's predictive least-squares criterion to estimate the autoregressive order of the process. This order estimator is strongly consistent when the output is autoregressive. The order estimator is combined with the standard autoregressive-output-analysis method to form a confidence-interval procedure. Alternatives for estimating the degrees of freedom for the procedure are investigated. The main result is an asymptotically valid confidence-interval procedure that, empirically, has good small-sample properties.
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Yuan, M., Nelson, B.L. Autoregressive-output-analysis methods revisited. Ann Oper Res 53, 391–418 (1994). https://doi.org/10.1007/BF02136836
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DOI: https://doi.org/10.1007/BF02136836