Implementable MSE-optimal dynamic partial-overlapping batch means estimators for steady-state simulations

Estimating the variance of the sample mean from a stochastic process is essential in assessing the quality of using the sample mean to estimate the population mean which is the fundamental question in simulation experiments. Most existing studies for estimating the variance of the sample mean from simulation output assume simulation run length is known in advance. This paper proposes an implementable batch-size selection procedure for estimating the variance of the sample mean without requiring that the sample size or simulation run length a priori.