Folded overlapping variance estimators for simulation

Folded overlapping variance estimators for simulation

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Article ID: iaor20122424
Volume: 220
Issue: 1
Start Page Number: 135
End Page Number: 146
Publication Date: Jul 2012
Journal: European Journal of Operational Research
Authors: , ,
Keywords: statistics: inference
Abstract:

We propose and analyze a new class of estimators for the variance parameter of a steady‐state simulation output process. The new estimators are computed by averaging individual estimators from ‘folded’ standardized time series based on overlapping batches composed of consecutive observations. The folding transformation on each batch can be applied more than once to produce an entire set of estimators. We establish the limiting distributions of the proposed estimators as the sample size tends to infinity while the ratio of the sample size to the batch size remains constant. We give analytical and Monte Carlo results showing that, compared to their counterparts computed from nonoverlapping batches, the new estimators have roughly the same bias but smaller variance. In addition, these estimators can be computed with order‐of‐sample‐size work.

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