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

Peter W. Glynn and Donald L. Iglehart

Stochastic Processes and their Applications, 1988, vol. 28, issue 1, 71-80

Abstract: The principal problem associated with steady-state simulation is the estimation of the variance term in an associated central limit theorem. This paper develops several strongly consistent estimates for this term using the strong approximations available for Brownian motion. A comparison of rates of convergence is given for a variety of estimators.

Keywords: Brownian; motion; confidence; intervals; rates; of; convergence; regenerative; simulation; simulation; output; analysis; steady-state; simulation; strong; approximation; laws; strongly; consistent; estimation (search for similar items in EconPapers)
Date: 1988
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