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Journal of Interdisciplinary Mathematics cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-012X·ISSN (Print): 0972-0502

Monthly Journal: Publishes the methodological and theoretical role of mathematics and mathematical applications underpinning scientific research.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
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Open Access Research Article

Monte Carlo and quasi-Monte Carlo methods for high-dimensional integration

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pp. 2227–2235Vol. 28Issue 6September 2025DOI: 10.47974/JIM-2364XML
Received:
10 Dec 2024
Published Online:
30 Sep 2025
Article type:
Research Article
Language:
EN
Article no.:
JIM-2364
Pages:
2227–2235

Abstract

Monte Carlo (MC) and Quasi-Monte Carlo (QMC) methods have become important ways to solve complex integration problems in engineering, banking, and science computing.  MC uses random sampling to get better convergence, but QMC uses organized low-discrepancy patterns to do the same thing. This work looks at the theoretical bases, error limits, and real-world uses of both methods, with a focus on variance reduction, importance sampling, and mixed randomized QMC strategies. This paper discuss about these methods side by side shows how they combine processing complexity, accuracy, and stability, which is why they are so important in current applied mathematics and computational science.

Keywords

Subject Classifications

26B1511K45

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