A new class of strongly consistent variance estimators for steady-state simulations

DOI10.1016/0304-4149(88)90065-8zbMath0656.62096OpenAlexW2030827464MaRDI QIDQ1110224

Peter W. Glynn, Donald L. Iglehart

Publication date: 1988

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(88)90065-8

zbMATH Keywords

convergence ratesweak convergencestrong approximationstrong consistencysteady-state simulationconsistent estimatorsvariance estimatorsasymptotic confidence intervalincrements of Wiener processesregenerative method of simulation

Mathematics Subject Classification ID

Non-Markovian processes: estimation (62M09) Strong limit theorems (60F15) Sample path properties (60G17) Functional limit theorems; invariance principles (60F17)

Related Items (2)

On extreme value asymptotics for increments of renewal processes ⋮ Variance Estimation Based on Invariance Principles

Cites Work

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