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  4. On Nonasymptotic Optimal Stopping Criteria In Monte Carlo Simulations
 
research article

On Nonasymptotic Optimal Stopping Criteria In Monte Carlo Simulations

Bayer, Christian
•
Hoel, Hakon  
•
Von Schwerin, Erik  
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2014
Siam Journal On Scientific Computing

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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