Rare events, splitting, and quasi-Monte Carlo

@article{LEcuyer2007RareES,
  title={Rare events, splitting, and quasi-Monte Carlo},
  author={Pierre L'Ecuyer and Val{\'e}rie Demers and Bruno Tuffin},
  journal={ACM Trans. Model. Comput. Simul.},
  year={2007},
  volume={17},
  pages={9}
}
In the context of rare-event simulation, splitting and importance sampling (IS) are the primary approaches to make important rare events happen more frequently in a simulation and yet recover an unbiased estimator of the target performance measure, with much smaller variance than a straightforward Monte Carlo (MC) estimator. Randomized quasi-Monte Carlo (RQMC) is another class of methods for reducing the noise of simulation estimators, by sampling more evenly than with standard MC. It typically… CONTINUE READING
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On the importance function in splitting simulation

  • M.J.J. GARVELS, D. P. KROESE, VAN OMMEREN, J.-K.C.W.
  • Euro. Trans. Telecomm. 13, 4, 363–371.
  • 2002
Highly Influential
5 Excerpts

Feynman-Kac Formulae

  • P. DEL MORAL
  • Genealogical and Interacting Particle Systems…
  • 2004
Highly Influential
5 Excerpts

Large deviations in rare events simulation: Examples, counterexamples, and alternatives

  • S. ASMUSSEN
  • Monte Carlo and Quasi-Monte Carlo Methods 2000, K…
  • 2002
Highly Influential
4 Excerpts

Automatic importance estimation in forward Monte Carlo calculations

  • T. E. BOOTH
  • Trans. Amer. Nuc. Soc. 41, 308–309.
  • 1982
Highly Influential
4 Excerpts

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