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Quasi-monte carlo methods in practice: quasi-monte carlo methods for simulation
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Proceedings of the 35th conference on Winter simulation: driving innovation table of contents
New Orleans, Louisiana
SESSION: Advanced tutorials table of contents
Pages: 81 - 89  
Year of Publication: 2003
ISBN:0-7803-8132-7
Author
Pierre L'Ecuyer  Université de Montréal, Montréal (Québec), Canada
Sponsors
INFORMS/CS : Institute for Operations Research and the Management Sciences/College on Simulation
NIST : National Institute of Standards and Technology
IEEE/SMCS : Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
ACM: Association for Computing Machinery
(SCS) : The Society for Modeling and Simulation International
SIGSIM: ACM Special Interest Group on Simulation and Modeling
IIE : Institute of Industrial Engineers
IEEE/CS : Institute of Electrical and Electronics Engineers/Computer Society
ASA : American Statistical Association
Publisher
Winter Simulation Conference 
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ABSTRACT

Quasi-Monte Carlo (QMC) methods are numerical techniques for estimating large-dimensional integrals, usually over the unit hypercube. They can be applied, at least in principle, to any simulation whose aim is to estimate a mathematical expectation. This covers a very wide range of applications.

In this paper, we review some of the key ideas of quasi-Monte Carlo methods from a broad perspective, with emphasis on some recent results. We visit lattice rules in different types of spaces and make the connections between these rules and digital nets, thus covering the two most widely used QMC methods.


REFERENCES

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