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HLIBCov

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification.

Keywords for this software

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  • spatial statistics
  • Matérn covariance
  • Matern covariance
  • Cholesky
  • random fields
  • hierarchical matrix
  • Bayesian update
  • low-rank tensor approximation
  • Kriging
  • parallel hierarchical matrices
  • loglikelihood surrogate
  • Hilbert tensor
  • random field
  • large datasets
  • Kalman filter
  • geostatistical optimal design
  • computational statistics
  • Fourier transform
  • large dataset
  • HLIB
  • Computational statistics
  • matrix determinant
  • HLIBpro

  • URL: github.com/litvinen/HL...
  • Code
  • InternetArchive
  • Authors: Alexander Litvinenko

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  • Related software:
  • GitHub
  • FRK
  • BRENT
  • ICALAB
  • ExaGeoStat
  • HLIBpro
  • GMRFLib
  • QUIC
  • George
  • SGLib

References in zbMATH (referenced in 3 articles )

Showing results 1 to 3 of 3.
y Sorted by year (citations)

  1. Litvinenko, Alexander; Keyes, David; Khoromskaia, Venera; Khoromskij, Boris N.; Matthies, Hermann G.: Tucker tensor analysis of Matérn functions in spatial statistics (2019)
  2. Litvinenko, Alexander; Sun, Ying; Genton, Marc G.; Keyes, David E.: Likelihood approximation with hierarchical matrices for large spatial datasets (2019)
  3. Alexander Litvinenko: HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification (2017) arXiv

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  • MSC classification / top
    • Top MSC classes
      • 60 Probability theory and...
      • 62 Statistics
      • 65 Numerical analysis

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