A guide to simulation (2nd ed.)
A guide to simulation (2nd ed.)
Correlation among estimators of the variance of the sample mean
WSC '87 Proceedings of the 19th conference on Winter simulation
Large and small sample comparisons of various variance estimators
WSC '86 Proceedings of the 18th conference on Winter simulation
Principles of Discrete Event Simulation
Principles of Discrete Event Simulation
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Overlapping batch means: something for nothing?
WSC '84 Proceedings of the 16th conference on Winter simulation
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A classical problem of stochastic simulation is how to estimate the variance of point estimators, the prototype problem being the sample mean from a steady-state autocorrelated process. A variety of estimators for the variance of the sample mean have been proposed, all designed to provide robustness to violations of assumptions, small variance, and reasonable computing requirements. Evaluation and comparison of such estimators depend on the ability to calculate their variances. A numerical approach is developed here to calculate the dispersion matrix of a set of estimators expressible as quadratic forms of the data. The approach separates the analysis of the estimator type from the analysis of the data type. The analysis for overlapping-batch-means estimators is developed, as is the analysis for steady-state first-order autoregressive and moving-average data. Closed-form expressions for overlapping-batch-means estimators and independently distributed data are obtained.