Properties of standardized time series weighted area variance estimators
Management Science
Simulation output analysis using standardized time series
Mathematics of Operations Research
Optimal mean-squared-error batch sizes
Management Science
Confidence intervals using orthonormally weighted standardized time series
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Overlapping batch means: something for nothing?
WSC '84 Proceedings of the 16th conference on Winter simulation
Folded standardized time series area variance estimators for simulation
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Overlapping Variance Estimators for Simulation
Operations Research
Efficient Computation of Overlapping Variance Estimators for Simulation
INFORMS Journal on Computing
Linear combinations of overlapping variance estimators for simulation
Operations Research Letters
Folded standardized time series area variance estimators for simulation
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Performance of folded variance estimators for simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
| Hi-index | 0.00 |
We estimate the variance parameter of a stationary simulation-generated process using "folded" versions of standardized time series area estimators. We formulate improved variance estimators based on the combination of multiple folding levels as well as the use of batching. The improved estimators preserve the asymptotic bias properties of their predecessors but have substantially lower variance. A Monte Carlo example demonstrates the efficacy of the new methodology.