On NonAsymptotic Optimal Stopping Criteria in Monte Carlo Simulations

Christian Bayer · Håkon Hoel · Erik von Schwerin · Raul F. Tempone

33 citations0/0 files storedSIAM Journal on Scientific Computing

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Simulation Techniques and Applications Markov Chains and Monte Carlo Methods Mathematical Approximation and Integration

Abstract

We consider the setting of estimating the mean of a random variable by a sequential stopping rule Monte Carlo (MC) method. The performance of a typical second moment based sequential stopping rule MC method is shown to be unreliable in such settings both by numerical examples and through analysis. By analysis and approximations, we construct a higher moment based stopping rule which is shown in numerical examples to perform more reliably and only slightly less efficiently than the second moment based stopping rule.

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1983A Guide to Simulation 1986A guide to simulation (2nd ed.)1992The Asymptotic Validity of Sequential Stopping Rules for Stochastic Simulations 1982Confidence Intervals for Steady-State Simulations II: A Survey of Sequential Procedures 1984Confidence Intervals for Steady-State Simulations: I. A Survey of Fixed Sample Size Procedures 2005Simulation in java with SSJ

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