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zbMATH Open
Article . 2015
Data sources: zbMATH Open
DBLP
Article . 2023
Data sources: DBLP
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Resampled Regenerative Estimators

Resampled regenerative estimators
Authors: James M. Calvin; Marvin K. Nakayama;

Resampled Regenerative Estimators

Abstract

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.

Related Organizations
Keywords

central limit, variance reduction, Computational problems in statistics, Nonparametric statistical resampling methods, Central limit and other weak theorems, regenerative method

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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