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  1. Transactions on Modeling and Computer Simulation (TOMACS)
  2. ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 8
  3. Issue 1(Special issue on uniform random number generation), Jan 1998
  4. Latin supercube sampling for very high-dimensional simulations
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ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 27
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 26
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 25
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 24
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 23
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 22
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 21
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 20
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 19
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 18
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 17
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 16
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 15
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 14
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 13
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 12
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 11
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 10
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 9
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 8
Issue 4(Special issue on Web-based modeling and simulation), Oct 1998
Issue 3, July 1998
Issue 2(Special issue on modeling and analysis of stochastic systems), April 1998
Issue 1(Special issue on uniform random number generation), Jan 1998
Guest editors' introduction: special issue on uniform random number generation
Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator
Simple cellular automata as pseudorandom m-sequence generators for built-in self-test
The weighted spectral test: diaphony
Bad subsequences of well-known linear congruential pseudorandom number generators
Latin supercube sampling for very high-dimensional simulations
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 7
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 6
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 5
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 4
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 3
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 2
ACM Transactions on Modeling and Computer Simulation (TOMACS) : Volume 1

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Latin supercube sampling for very high-dimensional simulations

Content Provider ACM Digital Library
Author Owen, Art B.
Copyright Year 1998
Abstract This article introduces Latin supercube sampling (LSS) for very high-dimensional simulations such as arise in particle transport, finance, and queueing. LSS is developed as a combination of two widely used methods: Latin hypercube sampling (LHS) and quasi-Monte Carlo (QMC). In LSS, the input variables are grouped into subsets, and a lower-dimensional QMC method is used within each subset. The QMC points are presented in random order within subsets. QMC methods have been observed to lose effectiveness in high-dimensional problems. This article shows that LSS can extend the benefits of QMC to much higher dimensions, when one can make a good grouping of input variables. Some suggestions for grouping variables are given for the motivating examples. Even a poor grouping can still be expected to do as well as LHS. The article also extends LHS and LSS to infinite-dimensional problems. The paper includes a survey of QMC methods, randomized versions of them (RQMC), and previous methods for extending QMC to higher dimensions. Furthermore it shows that LSS applied with RQMC is more reliable than LSS with QMC.
Starting Page 71
Ending Page 102
Page Count 32
File Format PDF
ISSN 10493301
e-ISSN 15581195
DOI 10.1145/272991.273010
Volume Number 8
Issue Number 1
Journal ACM Transactions on Modeling and Computer Simulation (TOMACS)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 1998-01-01
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword $(\textit{t,m,s})-nets$ Latin hypercube Integration Lattice methodss Low discrepancy sequences Orthogonal array sampling Quasi-Monte Carlo
Content Type Text
Resource Type Article
Subject Computer Science Applications Modeling and Simulation
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