A survey of current methods for the elimination of initialization bias in digital simulation

Abstract

Initialization bias in digital simulation typically arises in estimating a steady-state statistic from replicated data. While methods have been developed to avoid this bias, such as batch means, the problem remains in some simulation contexts. This report surveys current methods for dealing with this bias and assesses their effectiveness and usefulness.