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Córdoba Sánchez, Irene and Varando, Gherardo and Bielza Lozoya, María Concepción and Larrañaga Múgica, Pedro María (2018). A fast Metropolis-Hastings method for generating random correlation matrices. In: "19th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2018)", 21-23 Nov 2018, Madrid, España. ISBN 978-3-030-03492-4. pp. 117-124. https://doi.org/10.1007/978-3-030-03493-1_13.
Title: | A fast Metropolis-Hastings method for generating random correlation matrices |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | 19th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2018) |
Event Dates: | 21-23 Nov 2018 |
Event Location: | Madrid, España |
Title of Book: | Intelligent Data Engineering and Automated Learning (IDEAL 2018) |
Date: | 2018 |
ISBN: | 978-3-030-03492-4 |
Volume: | 1 |
Subjects: | |
Freetext Keywords: | Correlation matrices; Random sampling; Metroplis-Hastings |
Faculty: | E.T.S. de Ingenieros Informáticos (UPM) |
Department: | Inteligencia Artificial |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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We propose a novel Metropolis-Hastings algorithm to sample uniformly from the space of correlation matrices. Existing methods in the literature are based on elaborated representations of a correlation matrix, or on complex parametrizations of it. By contrast, our method is intuitive and simple, based the classical Cholesky factorization of a positive definite matrix and Markov chain Monte Carlo theory. We perform a detailed convergence analysis of the resulting Markov chain, and show how it benefits from fast convergence, both theoretically and empirically. Furthermore, in numerical experiments our algorithm is shown to be significantly faster than the current alternative approaches, thanks to its simple yet principled approach.
Item ID: | 54634 |
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DC Identifier: | https://oa.upm.es/54634/ |
OAI Identifier: | oai:oa.upm.es:54634 |
DOI: | 10.1007/978-3-030-03493-1_13 |
Official URL: | https://link.springer.com/chapter/10.1007/978-3-03... |
Deposited by: | Memoria Investigacion |
Deposited on: | 29 Apr 2019 10:40 |
Last Modified: | 30 Nov 2022 09:00 |