GSLIB is an acronym for Geostatistical Software LIBrary. This name was originally used for a collection of geostatistical programs developed at Stanford University over the last 15 years. The original GSLIB inspired the writing of GSLIB: Geostatistical Software Library and User’s Guide by Clayton Deutsch and André Journel, 1992, 340 pp. during 1990 - 1992. The second edition was completed in 1997. Both editions were published by Oxford University Press.

References in zbMATH (referenced in 129 articles )

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  1. Ibrahima, Fayadhoi; Tchelepi, Hamdi A.: Multipoint distribution of saturation for stochastic nonlinear two-phase transport (2017)
  2. van den Boogaart, K.Gerald; Mueller, Ute; Tolosana-Delgado, Raimon: An affine equivariant multivariate normal score transform for compositional data (2017)
  3. Vigsnes, Maria; Kolbjørnsen, Odd; Hauge, Vera Louise; Dahle, Pål; Abrahamsen, Petter: Fast and accurate approximation to Kriging using common data neighborhoods (2017)
  4. Chatterjee, Snehamoy; Sethi, Manas Ranjan; Asad, Mohammad Waqar Ali: Production phase and ultimate pit limit design under commodity price uncertainty (2016)
  5. Goovaerts, Pierre; Albuquerque, M.T.D.; Antunes, I.M.H.R.: A multivariate geostatistical methodology to delineate areas of potential interest for future sedimentary gold exploration (2016)
  6. Tarrahi, Mohammadali; Elahi, Siavash Hakim; Jafarpour, Behnam: Fast linearized forecasts for subsurface flow data assimilation with ensemble Kalman filter (2016)
  7. Zagayevskiy, Yevgeniy; Deutsch, Clayton V.: Multivariate geostatistical grid-free simulation of natural phenomena (2016)
  8. Barnett, Ryan M.; Deutsch, Clayton V.: Multivariate imputation of unequally sampled geological variables (2015)
  9. Kim, Hyoung-Moon; Yoon, Young Joo; Kim, Hea-Jung: Optimal classifier for multivariate rectangle-screened normal data classification (2015)
  10. Li, Weidong; Zhang, Chuanrong; Willig, Michael R.; Dey, Dipak K.; Wang, Guiling; You, Liangzhi: Bayesian Markov chain random field cosimulation for improving land cover classification accuracy (2015)
  11. Nejadi, Siavash; Leung, Juliana; Trivedi, Japan: Characterization of non-Gaussian geologic facies distribution using ensemble Kalman filter with probability weighted re-sampling (2015)
  12. Skou Cordua, Knud; Mejer Hansen, Thomas; Mosegaard, Klaus: Improving the pattern reproducibility of multiple-point-based prior models using frequency matching (2015)
  13. Barnett, Ryan M.; Manchuk, John G.; Deutsch, Clayton V.: Projection pursuit multivariate transform (2014)
  14. Bourgault, Gilles: Revisiting multi-Gaussian kriging with the Nataf transformation or the Bayes’ rule for the estimation of spatial distributions (2014)
  15. Gardet, Caroline; Le Ravalec, Mickaele; Gloaguen, Erwan: Multiscale parameterization of petrophysical properties for efficient history-matching (2014)
  16. Harris, Paul; Brunsdon, Chris; Charlton, Martin; Juggins, Steve; Clarke, Annemarie: Multivariate spatial outlier detection using robust geographically weighted methods (2014)
  17. Kaveh, Marjan; Khaledi, Majid Jafari: Estimation in truncated GLG model for ordered categorical spatial data using the SAEM algorithm (2014)
  18. Silva, Daniel A.; Deutsch, Clayton V.: A multiple training image approach for spatial modeling of geologic domains (2014)
  19. Strebelle, Sebastien; Cavelius, Claude: Solving speed and memory issues in multiple-point statistics simulation program SNESIM (2014)
  20. Bivand, Roger S.; Pebesma, Edzer J.; Gómez-Rubio, Virgilio: Applied spatial data analysis with R (2013)

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