Generation of non-uniform low-discrepancy sequences in the multidimensional case

In this paper we extend the results we obtained in an earlier paper, from the one-dimensional case to the \(s\)-dimensional case. We propose two inversion type methods for generating \(G\)-distributed low-discrepancy sequences in \([0,1]^{s}\), where \(G\) is an arbitrary distribution function. Our...

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Main Author: Natalia Roşca
Format: Article
Language:English
Published: Publishing House of the Romanian Academy 2006-08-01
Series:Journal of Numerical Analysis and Approximation Theory
Subjects:
Online Access:https://ictp.acad.ro/jnaat/journal/article/view/847
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author Natalia Roşca
author_facet Natalia Roşca
author_sort Natalia Roşca
collection DOAJ
description In this paper we extend the results we obtained in an earlier paper, from the one-dimensional case to the \(s\)-dimensional case. We propose two inversion type methods for generating \(G\)-distributed low-discrepancy sequences in \([0,1]^{s}\), where \(G\) is an arbitrary distribution function. Our methods are based on the approximation of the inverses of the marginal distribution functions using linear Lagrange interpolation or cubic Hermite interpolation. We also determine upper bounds for the \(G\)-discrepancy of the sequences we generate using the proposed methods.
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spelling doaj.art-bb15f9488a314e9b834e0fc0cab3a7792022-12-22T00:57:43ZengPublishing House of the Romanian AcademyJournal of Numerical Analysis and Approximation Theory2457-67942501-059X2006-08-01352Generation of non-uniform low-discrepancy sequences in the multidimensional caseNatalia Roşca0“Babes-Bolyai” University, RomaniaIn this paper we extend the results we obtained in an earlier paper, from the one-dimensional case to the \(s\)-dimensional case. We propose two inversion type methods for generating \(G\)-distributed low-discrepancy sequences in \([0,1]^{s}\), where \(G\) is an arbitrary distribution function. Our methods are based on the approximation of the inverses of the marginal distribution functions using linear Lagrange interpolation or cubic Hermite interpolation. We also determine upper bounds for the \(G\)-discrepancy of the sequences we generate using the proposed methods.https://ictp.acad.ro/jnaat/journal/article/view/847discrepancyuniformly distributed sequences\(G\)-discrepancy\(G\)-distributed sequenceslow-discrepancy sequencesquasi-Monte Carlo integration
spellingShingle Natalia Roşca
Generation of non-uniform low-discrepancy sequences in the multidimensional case
Journal of Numerical Analysis and Approximation Theory
discrepancy
uniformly distributed sequences
\(G\)-discrepancy
\(G\)-distributed sequences
low-discrepancy sequences
quasi-Monte Carlo integration
title Generation of non-uniform low-discrepancy sequences in the multidimensional case
title_full Generation of non-uniform low-discrepancy sequences in the multidimensional case
title_fullStr Generation of non-uniform low-discrepancy sequences in the multidimensional case
title_full_unstemmed Generation of non-uniform low-discrepancy sequences in the multidimensional case
title_short Generation of non-uniform low-discrepancy sequences in the multidimensional case
title_sort generation of non uniform low discrepancy sequences in the multidimensional case
topic discrepancy
uniformly distributed sequences
\(G\)-discrepancy
\(G\)-distributed sequences
low-discrepancy sequences
quasi-Monte Carlo integration
url https://ictp.acad.ro/jnaat/journal/article/view/847
work_keys_str_mv AT nataliarosca generationofnonuniformlowdiscrepancysequencesinthemultidimensionalcase