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On non-asymptotic optimal stopping criteria in Monte Carlo simulations

2013, Bayer, Christian, Hoel, Hakon, von Schwerin, Erik, Tempone, Raúl

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.