Computational efficiency of batching methods
Proceedings of the 29th conference on Winter simulation
The impact of transients on simulation variance estimators
Proceedings of the 29th conference on Winter simulation
Two-stage multiple-comparison procedures for steady-state simulations
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Permuted Standardized Time Series for Steady-State Simulations
Mathematics of Operations Research
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This paper studies a class of estimators for the variance parameter of a stationary stochastic process. The estimators are based on Lp norms of standardized time series, and they generalize previously studied estimators due to Schruben. We show that the new estimators have some desirable properties: they are asymptotically unbiased and have low asymptotic variance. We also illustrate empirically the performance of the Lp-norm estimators on various stochastic processes.