THIS LIBRARY IS NO LONGER MAINTAINED. It will be integrated into SHOGUN: ( and future progress will be found there. The Krylov statistics library (KRYLSTAT) is free C++ software under the LGPL license. It is designed to facilitate sampling from high dimensional Gaussian distributions using rational approximations and Krylov methods and computing log-determinants using the same methods with the addition of graph colouring.

References in zbMATH (referenced in 18 articles )

Showing results 1 to 18 of 18.
Sorted by year (citations)

  1. Li, Hanyu; Zhu, Yuanyang: Randomized block Krylov subspace methods for trace and log-determinant estimators (2021)
  2. Chae, Minwoo; Walker, Stephen G.: An EM-based iterative method for solving large sparse linear systems (2020)
  3. Zammit-Mangion, Andrew; Rougier, Jonathan: Multi-scale process modelling and distributed computation for spatial data (2020)
  4. Bolin, David; Wallin, Jonas; Lindgren, Finn: Latent Gaussian random field mixture models (2019)
  5. Kahalé, Nabil: Efficient simulation of high dimensional Gaussian vectors (2019)
  6. Parker, Albert E.; Pitts, Betsey; Lorenz, Lindsey; Stewart, Philip S.: Polynomial accelerated solutions to a large Gaussian model for imaging biofilms: in theory and finite precision (2018)
  7. Peng, Wei; Wang, Hongxia: A general scheme for log-determinant computation of matrices via stochastic polynomial approximation (2018)
  8. Han, Insu; Malioutov, Dmitry; Avron, Haim; Shin, Jinwoo: Approximating spectral sums of large-scale matrices using stochastic Chebyshev approximations (2017)
  9. Minden, Victor; Damle, Anil; Ho, Kenneth L.; Ying, Lexing: Fast spatial Gaussian process maximum likelihood estimation via skeletonization factorizations (2017)
  10. Schmidt, Paul; Mühlau, Mark; Schmid, Volker: Fitting large-scale structured additive regression models using Krylov subspace methods (2017)
  11. Ubaru, Shashanka; Chen, Jie; Saad, Yousef: Fast estimation of (\mathrmtr(f(A))) via stochastic Lanczos quadrature (2017)
  12. Benzi, Michele: Localization in matrix computations: theory and applications (2016)
  13. Fallaize, Christopher J.; Kypraios, Theodore: Exact Bayesian inference for the Bingham distribution (2016)
  14. Benzi, Michele; Simoncini, Valeria: Decay bounds for functions of Hermitian matrices with banded or Kronecker structure (2015)
  15. Lindgren, Finn: Comments on: “Comparing and selecting spatial predictors using local criteria” (2015)
  16. Aune, Erlend; Simpson, Daniel P.; Eidsvik, Jo: Parameter estimation in high dimensional Gaussian distributions (2014)
  17. Aune, Erlend; Eidsvik, Jo; Pokern, Yvo: Iterative numerical methods for sampling from high dimensional Gaussian distributions (2013)
  18. Stein, Michael L.; Chen, Jie; Anitescu, Mihai: Stochastic approximation of score functions for Gaussian processes (2013)