Cited by 6,474Markov Chains and Monte Carlo MethodsMathematical Approximation and IntegrationTheoretical and Computational Physics

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The Monte Carlo Method

Metropolis, Nicholas, Ulam, S.·1949·Journal of the American Statistical Association

DOI 10.1080/01621459.1949.10483310

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Abstract

We shall present here the motivation and a general description of a method dealing with a class of problems in mathematical physics. The method is, essentially, a statistical approach to the study of differential equations, or more generally, of integro-differential equations that occur in various branches of the natural sciences.

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Gillis, J. M., & Morsi, W. G. (2016) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2016.2532885 · Cited by 109

Authors: Metropolis, N., & Ulam, S.
Affiliations: Los Alamos National Laboratory (US)
Venue: Journal of the American Statistical Association
Publisher: Informa UK Limited
Published: 1949-09
Volume: 44
Issue: 247
Pages: 335-341
ISSN: 0162-1459 (ISSN-L)
1537-274X
DOI: 10.1080/01621459.1949.10483310
OpenAlex: W2051203581
Cited by: 6,474
References: 0
Citations by year: 2026: 368 · 2025: 419 · 2024: 327 · 2023: 345 · 2022: 333 · 2021: 343 · 2020: 318 · 2019: 304 · 2018: 270 · 2017: 252 · 2016: 258 · 2015: 249 · 2014: 254 · 2013: 283 · 2012: 262
FWCI: 8.97
Type: journal article
Language: en
Open access: closed
Locations: Journal of the American Statistical Association (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Markov Chains and Monte Carlo Methods
Physical Sciences › Mathematics › Numerical Analysis › Mathematical Approximation and Integration
Physical Sciences › Physics and Astronomy › Condensed Matter Physics › Theoretical and Computational Physics
Keywords: Monte Carlo methods, integro-differential equations, mathematical physics, numerical solution of partial differential equations
MeSH terms: Biometry, Humans, Monte Carlo Method, Statistics as Topic

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