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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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Type
research article
DOI
10.1137/130911433
Web of Science ID

WOS:000335817600024

Author(s)
Bayer, Christian
Hoel, Hakon  
Von Schwerin, Erik  
Tempone, Raul
Date Issued

2014

Publisher

Siam Publications

Published in
Siam Journal On Scientific Computing
Volume

36

Issue

2

Start page

A869

End page

A885

Subjects

Monte Carlo methods

•

optimal stopping

•

sequential stopping rules

•

nonasymptotic

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CSQI  
Available on Infoscience
June 23, 2014
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/104652
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