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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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| Publicado no: | MethodsX |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Elsevier
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6992995/ https://ncbi.nlm.nih.gov/pubmed/32021810 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.mex.2019.07.001 |
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