Convergence Properties of the Batch Means Method for Simulation Output Analysis
INFORMS Journal on Computing
An Improved Batch Means Procedure for Simulation Output Analysis
Management Science
Output analysis: ASAP2: an improved batch means procedure for simulation output analysis
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
ASAP3: a batch means procedure for steady-state simulation analysis
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)
Skart: a skewness-and autoregression-adjusted batch-means procedure for simulation analysis
Proceedings of the 40th Conference on Winter Simulation
Performance of a Wavelet-Based Spectral Procedure for Steady-State Simulation Analysis
INFORMS Journal on Computing
A new perspective on batched quantile estimation
Proceedings of the Winter Simulation Conference
Variance estimation and sequential stopping in steady-state simulations using linear regression
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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An analysis is given for an extensive experimental performance evaluation of Skart, an automated sequential batch means procedure for constructing an asymptotically valid confidence interval (CI) on the steady-state mean of a simulation output process. Skart is designed to deliver a CI satisfying user-specified requirements on absolute or relative precision as well as coverage probability. Skart exploits separate adjustments to the half-length of the classical batch means CI so as to account for the effects on the distribution of the underlying Student's t-statistic that arise from skewness (nonnormality) and autocorrelation of the batch means. Skart also delivers a point estimator for the steady-state mean that is approximately free of initialization bias. In an experimental performance evaluation involving a wide range of test processes, Skart compared favorably with other steady-state simulation analysis methods---namely, its predecessors ASAP3, WASSP, and SBatch, as well as ABATCH, LBATCH, the Heidelberger--Welch procedure, and the Law--Carson procedure. Specifically, Skart exhibited competitive sampling efficiency and closer conformance to the given CI coverage probabilities than the other procedures, especially in the most difficult test processes.