A Finite-Memory Algorithm for Batch Means Estimators in Simulation Output Analysis

A classic problem of stochastic simulation is estimating the variance of point estimators, the prototype estimator being the sample mean from a steady-state autocorrelated process. The traditional batch means (BM) estimator requires knowledge of the sample size a priori. This paper proposes an algorithm to implement certain BM estimators without knowing the sample size in advance. The proposed algorithm is useful when the run length is random or is extremely long in simulation models.