A guide to simulation (2nd ed.)
A guide to simulation (2nd ed.)
Multiple comparison procedures
Multiple comparison procedures
Simulation output analysis using standardized time series
Mathematics of Operations Research
Strong consistency and other properties of the spectral variance estimator
Management Science
Notes: conditions for the applicability of the regenerative method
Management Science
Strong consistency of the variance estimator in steady-state simulation output analysis
Mathematics of Operations Research
Two-stage stopping procedures based on standardized time series
Management Science
Two-stage multiple-comparison procedures for steady-state simulations
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Principles of Discrete Event Simulation
Principles of Discrete Event Simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Permuted Standardized Time Series for Steady-State Simulations
Mathematics of Operations Research
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We analyze the asymptotic behavior of two-stage procedures for multiple comparisons with the best (MCB) for comparing the steady-state means of alternative systems using simulation. The two procedures we consider differ in how they estimate the variance parameters of the alternatives in the first stage. One procedure uses a consistent estimator, and the other employs an estimator based on one of Schruben's standardized time series (STS) methods. While both methods lead to mean total run lengths that are of the same asymptotic order of magnitude, the limiting variability of the run lengths is strictly smaller for the method based on a consistent variance estimator. We also provide some analysis showing how to choose the first-stage run length.