Gaussian Markov Random fields over graphs of paths and high relative accuracy
Resumen: The present paper presents some results that allow us to perform with High Relative Accuracy linear algebra operations with correlation and covariance matrices of Gaussian Markov Random Fields over graphs of paths. Some numerical experiments are carried out showing the computational benefits of this approach.
Idioma: Inglés
DOI: 10.1016/j.cam.2024.116142
Año: 2024
Publicado en: Journal of Computational and Applied Mathematics 453 (2024), 116142 [12 pp.]
ISSN: 0377-0427

Factor impacto JCR: 2.6 (2024)
Categ. JCR: MATHEMATICS, APPLIED rank: 35 / 343 = 0.102 (2024) - Q1 - T1
Factor impacto CITESCORE: 4.8 - Computational Mathematics (Q1) - Applied Mathematics (Q1)

Factor impacto SCIMAGO: 0.688 - Computational Mathematics (Q2) - Applied Mathematics (Q2)

Financiación: info:eu-repo/grantAgreement/ES/MCIU/PID2022-138569NB-I00
Financiación: info:eu-repo/grantAgreement/ES/MCIU/PID2022-139886NB-I00
Financiación: info:eu-repo/grantAgreement/ES/MCIU/PID2022-140585NB-I00
Financiación: info:eu-repo/grantAgreement/ES/MCIU/RED2022-134176-T
Tipo y forma: Article (Published version)
Área (Departamento): Área Matemática Aplicada (Dpto. Matemática Aplicada)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.


Exportado de SIDERAL (2026-01-12-12:52:02)


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 Record created 2024-08-29, last modified 2026-01-12


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