Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/WSC.2007.4419635 | Winter Simulation Conference |
Keywords | Field | DocType |
batch processing (industrial),parameter estimation,simulation,time series,Monte Carlo method,asymptotic bias property,batch process,folded standardized time series area variance estimation,parameter estimation,stationary simulation process | Applied mathematics,Mathematical optimization,Monte Carlo method,Computer science,Simulation,Control variates,Batch processing,Dynamic Monte Carlo method,Estimation theory,Estimator,Standard time | Conference |
ISBN | Citations | PageRank |
1-4244-1306-0 | 2 | 0.42 |
References | Authors | |
10 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Claudia Antonini | 1 | 7 | 0.84 |
| Christos Alexopoulos | 2 | 426 | 77.68 |
| David Goldsman | 3 | 904 | 159.71 |
| James R. Wilson | 4 | 840 | 143.42 |