AS 312

Algorithm AS 312: An algorithm for simulating stationary Gaussian random fields. This paper describes a Fortran program which determines a suitable circulant embedding matrix and simulates a stationary Gaussian random field on a grid. The proposed procedure is based on the idea of circulant embedding.

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References in zbMATH (referenced in 14 articles , 1 standard article )

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  1. Cox, Sonja G.; Kirchner, Kristin: Regularity and convergence analysis in Sobolev and Hölder spaces for generalized Whittle-Matérn fields (2020)
  2. Herrmann, Lukas; Kirchner, Kristin; Schwab, Christoph: Multilevel approximation of Gaussian random fields: fast simulation (2020)
  3. Khristenko, U.; Scarabosio, L.; Swierczynski, P.; Ullmann, E.; Wohlmuth, B.: Analysis of boundary effects on PDE-based sampling of Whittle-Matérn random fields (2019)
  4. Latz, Jonas; Eisenberger, Marvin; Ullmann, Elisabeth: Fast sampling of parameterised Gaussian random fields (2019)
  5. Feischl, Michael; Kuo, Frances Y.; Sloan, Ian H.: Fast random field generation with (H)-matrices (2018)
  6. Graham, I. G.; Kuo, F. Y.; Nuyens, Dirk; Scheichl, R.; Sloan, I. H.: Analysis of circulant embedding methods for sampling stationary random fields (2018)
  7. Graham, Ivan G.; Kuo, Frances Y.; Nuyens, Dirk; Scheichl, Rob; Sloan, Ian H.: Circulant embedding with QMC: analysis for elliptic PDE with lognormal coefficients (2018)
  8. Belyaev, Mikhail; Burnaev, Evgeny; Kapushev, Y.: Computationally efficient algorithm for Gaussian process regression in case of structured samples (2016)
  9. Bock, Wolfgang; Bornales, Jinky B.; Cabahug, Cresente O.; Eleutério, Samuel; Streit, Ludwig: Scaling properties of weakly self-avoiding fractional Brownian motion in one dimension (2015)
  10. Graham, I. G.; Kuo, F. Y.; Nuyens, D.; Scheichl, R.; Sloan, I. H.: Quasi-Monte Carlo methods for elliptic PDEs with random coefficients and applications (2011)
  11. Hofer, Christoph; Papritz, Andreas: Predicting threshold exceedance by local block means in soil pollution surveys (2010)
  12. Nordman, Daniel J.: An empirical likelihood method for spatial regression (2008)
  13. Nordman, Daniel J.; Lahiri, Soumendra N.: On optimal spatial subsample size for variance estimation (2004)
  14. Chan, Grace; Wood, Andrew T. A.: An algorithm for simulating stationary Gaussian random fields (1997)