Title :
Quasi-Monte Carlo methods for simulation
Author :
Ecuyer, Pierre L.
Author_Institution :
Departement d´´Informatique et de Recherche Operationnelle, Montreal Univ., Que., Canada
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;
Conference_Titel :
Simulation Conference, 2003. Proceedings of the 2003 Winter
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/WSC.2003.1261411