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 120 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. Chatterjee, Snehamoy; Sethi, Manas Ranjan; Asad, Mohammad Waqar Ali: Production phase and ultimate pit limit design under commodity price uncertainty (2016)
  4. Tarrahi, Mohammadali; Elahi, Siavash Hakim; Jafarpour, Behnam: Fast linearized forecasts for subsurface flow data assimilation with ensemble Kalman filter (2016)
  5. Barnett, Ryan M.; Deutsch, Clayton V.: Multivariate imputation of unequally sampled geological variables (2015)
  6. Kim, Hyoung-Moon; Yoon, Young Joo; Kim, Hea-Jung: Optimal classifier for multivariate rectangle-screened normal data classification (2015)
  7. 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)
  8. Nejadi, Siavash; Leung, Juliana; Trivedi, Japan: Characterization of non-Gaussian geologic facies distribution using ensemble Kalman filter with probability weighted re-sampling (2015)
  9. Skou Cordua, Knud; Mejer Hansen, Thomas; Mosegaard, Klaus: Improving the pattern reproducibility of multiple-point-based prior models using frequency matching (2015)
  10. Barnett, Ryan M.; Manchuk, John G.; Deutsch, Clayton V.: Projection pursuit multivariate transform (2014)
  11. Bourgault, Gilles: Revisiting multi-Gaussian kriging with the Nataf transformation or the Bayes’ rule for the estimation of spatial distributions (2014)
  12. Gardet, Caroline; Le Ravalec, Mickaele; Gloaguen, Erwan: Multiscale parameterization of petrophysical properties for efficient history-matching (2014)
  13. Harris, Paul; Brunsdon, Chris; Charlton, Martin; Juggins, Steve; Clarke, Annemarie: Multivariate spatial outlier detection using robust geographically weighted methods (2014)
  14. Silva, Daniel A.; Deutsch, Clayton V.: A multiple training image approach for spatial modeling of geologic domains (2014)
  15. Strebelle, Sebastien; Cavelius, Claude: Solving speed and memory issues in multiple-point statistics simulation program SNESIM (2014)
  16. Bivand, Roger S.; Pebesma, Edzer J.; Gómez-Rubio, Virgilio: Applied spatial data analysis with R (2013)
  17. Horta, Ana; Correia, Pedro; Pinheiro, Luís Menezes; Soares, Amílcar: Geostatistical data integration model for contamination assessment (2013)
  18. Machuca-Mory, David F.; Deutsch, Clayton V.: Non-stationary geostatistical modeling based on distance weighted statistics and distributions (2013)
  19. Sapriza Azuri, Gonzalo; Jódar, Jorge; Carrera, Jesús; Gupta, Hoshin V.: Stochastic simulation of nonstationary rainfall fields, accounting for seasonality and atmospheric circulation pattern evolution (2013)
  20. Tütmez, Bülent; Kaymak, Uzay: Regional spatial analysis combining fuzzy clustering and non-parametric correlation (2013) ioport

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