An Improved Halton Sequence for Implementation in Quasi-Monte Carlo Methods

Despite possessing the low-discrepancy property, the classical d-dimensional Halton sequence is known to exhibit poorly distributed projections when <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$d$</tex> becomes even moderately large. This, in turn, often implies bad performance when implemented in quasi-Monte Carlo (QMC) methods in comparison to, for example, the Sobol’ sequence. As an attempt to eradicate this issue, we propose an adapted Halton sequence built by integer and irrational based van der Corput sequences and show empirically improved performance with respect to the accuracy of estimates in numerical integration and simulation. In addition, for the first time, a scrambling algorithm is proposed for irrational based digital sequences.

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Publication Details

Published
2024-12-15
DOI
https://doi.org/10.1109/wsc63780.2024.10838773
Citations
2
Primary Topic
Mathematical Approximation and Integration
Type
article
Field-Weighted Citation Impact
1.46
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article

An Improved Halton Sequence for Implementation in Quasi-Monte Carlo Methods

Nathan Kirk, Christiane Lemieux
2 citations
Mathematical Approximation and Integration
1.46
article

An Improved Halton Sequence for Implementation in Quasi-Monte Carlo Methods

Nathan Kirk, Christiane Lemieux
article en
2 citations

Abstract

Despite possessing the low-discrepancy property, the classical d-dimensional Halton sequence is known to exhibit poorly distributed projections when <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$d$</tex> becomes even moderately large. This, in turn, often implies bad performance when implemented in quasi-Monte Carlo (QMC) methods in comparison to, for example, the Sobol’ sequence. As an attempt to eradicate this issue, we propose an adapted Halton sequence built by integer and irrational based van der Corput sequences and show empirically improved performance with respect to the accuracy of estimates in numerical integration and simulation. In addition, for the first time, a scrambling algorithm is proposed for irrational based digital sequences.

University of Waterloo (CA), Actua (CA)
Openalex Percentile: Top 17%
Mathematical Approximation and Integration
1.46
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An Improved Halton Sequence for Implementation in Quasi-Monte Carlo Methods — Nathan Kirk, Christiane Lemieux · (2024) | TGRS Research Map | TGRS