HLIBCov: Parallel hierarchical matrix approximation of large covariance matrices and likelihoods with applications in parameter identification

We provide more technical details about the HLIBCov package, which is using parallel hierarchical (H-) matrices to: • Approximate large dense inhomogeneous covariance matrices with a log-linear computational cost and storage requirement. • Compute matrix-vector product, Cholesky factorization and in...

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Detalles Bibliográficos
Autores principales: Litvinenko, Alexander, Kriemann, Ronald, Genton, Marc G., Sun, Ying, Keyes, David E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Mathematics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6992995/
https://www.ncbi.nlm.nih.gov/pubmed/32021810
http://dx.doi.org/10.1016/j.mex.2019.07.001

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6992995/
https://www.ncbi.nlm.nih.gov/pubmed/32021810
http://dx.doi.org/10.1016/j.mex.2019.07.001

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