Abstract
Estimating the variance of the sample mean is a lassical problem of sto hastic simulation.Traditionalbatch means estimators require that the storage space in random access memory or disk space is propor-tional to the sample size.Dynami bat h means (DNBM)estimators proposed by Yeh and S hmeiser(1999)are known to be the onlytype of estimators requiring a onstant storage space for any sample size.In this paper we propose dynamic partial batch means (DPBM)estimators requiring also a onstantstorage space for any sample size.We show that DPBMworks better than DBMwith the same storagespace for many processes in terms of the mean-squared-error riteria.1.1 Background............................1.2 Motivation.............................52 Literature Review 62.1 BatchMeansEstimators.....................62.2 DynamicNon-OverlappingBM .................92.3 DynamicPartial-OverlappingBM................113 Some Results on PBM Estimators 153.1 PBMEstimators .........................153.2 1-2-1PBM.............................153.3 Some Observation on Dynamic Batch Means Estimtors ....164 The Revision of DPBM 17.1 TheFirstRevisionofDPBM...................17.2 InterpretationofSimulationResult ...............21.3 TheSecondRevisionofDPBM .................225 Performance Comparison6 Conclusion