Quasi-Monte Carlo and ε-truncation dimension in ANOVA spaces

G. W. Wasilkowski

doi:10.1016/j.jco.2020.101500

Quasi-Monte Carlo and ε-truncation dimension in ANOVA spaces

G. W. Wasilkowski

Computer Science

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

We explain the efficiency of quasi-Monte Carlo methods for high dimensional integration by proving that the worst case ε-truncation dimension of the error functional on γ-weighted ANOVA spaces is small for modest error demands.

Original language	English
Article number	101500
Journal	Journal of Complexity
Volume	62
DOIs	https://doi.org/10.1016/j.jco.2020.101500
State	Published - Feb 2021

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Inc.

Keywords

ANOVA spaces
Multivariate integration
Quasi-Monte Carlo

ASJC Scopus subject areas

Algebra and Number Theory
Statistics and Probability
Numerical Analysis
General Mathematics
Control and Optimization
Applied Mathematics

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10.1016/j.jco.2020.101500

Cite this

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abstract = "We explain the efficiency of quasi-Monte Carlo methods for high dimensional integration by proving that the worst case ε-truncation dimension of the error functional on γ-weighted ANOVA spaces is small for modest error demands.",

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Quasi-Monte Carlo and ε-truncation dimension in ANOVA spaces

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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