Improved Batching for Confidence Interval Construction in Steady-State Simulation
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1999-03-10
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Abstract
The primary objectives of this research are formulation and evaluation of an improved batch-means procedure for steady-state simulation output analysis. The new procedure yields a confidence interval for a steady-state expected response that is centered on the sample mean of a portion of the series ofsimulation-generated responses and satisfies a user-specified absolute or relative precision requirement. We concentrate on the method of nonoverlapping batch means (NOBM), which requires the sample means computed from adjacent batches of observations to be independent and identically distributed normal random variables. For increasing batch sizes and a fixed number of batches computed from a weakly dependent (phi-mixing) output process, we establish key asymptotic distributional properties of the vector of batch means and of the numerator and squared denominator of the NOBM -ratio, where the terms of the expansion are estimated via an autoregressive--moving average time series model of the batch means. An extensive experimental performance evaluation demonstrates the advantages of ASAP versus other widely used batch-means procedures.
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PhD
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Industrial Engineering
