DocumentCode
402121
Title
Quasi-Monte Carlo methods for simulation
Author
Ecuyer, Pierre L.
Author_Institution
Departement d´´Informatique et de Recherche Operationnelle, Montreal Univ., Que., Canada
Volume
1
fYear
2003
fDate
7-10 Dec. 2003
Firstpage
81
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.
Keywords
Monte Carlo methods; random number generation; simulation; stochastic processes; QMC methods; broad perspective; digital nets; large-dimensional integrals; lattice rules; mathematical expectation; numerical techniques; pseudorandomness; quasiMonte Carlo methods; random number generation; stochastic simulation; unit hypercube; Application software; Computational modeling; Computer simulation; Convergence; Hypercubes; Lattices; Monte Carlo methods; Random number generation; Random variables; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference, 2003. Proceedings of the 2003 Winter
Print_ISBN
0-7803-8131-9
Type
conf
DOI
10.1109/WSC.2003.1261411
Filename
1261411
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