期刊
ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION
卷 25, 期 4, 页码 -出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2699718
关键词
Variance reduction; regenerative method
资金
- National Science Foundation [DMI-9624469, DMI-9900117, CMMI-0926949, CMMI-1200065, DMS-1331010]
- Div Of Civil, Mechanical, & Manufact Inn
- Directorate For Engineering [1200065] Funding Source: National Science Foundation
We discuss some estimators for simulations of processes having multiple regenerative sequences. The estimators are obtained by resampling trajectories without and with replacement, which correspond to a type of U-statistic and a type of V-statistic, respectively. The U-statistic estimator turns out to be equivalent to the permuted regenerative estimator, which we previously proposed, but the V-statistic estimator is new. We compare analytically some properties of these estimators and the semiregenerative estimator. We show that when estimating the second moment of a cycle reward, the semiregenerative estimator has positive bias, which is strictly larger than the (positive) bias of the V-statistic estimator. The permuted estimator is unbiased. All of the estimators have the same asymptotic central limit behavior, with reduced asymptotic variance compared to the standard regenerative estimator. Some numerical results are included.
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