References in zbMATH (referenced in 29 articles )

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  1. Champagne, Clara; Gerhards, Maximilian; Lana, Justin; García Espinosa, Bernardo; Bradley, Christina; González, Oscar; Cohen, Justin M.; Le Menach, Arnaud; White, Michael T.; Pothin, Emilie: Using observed incidence to calibrate the transmission level of a mathematical model for \textitPlasmodiumvivax dynamics including case management and importation (2022)
  2. Reyné, Bastien; Richard, Quentin; Selinger, Christian; Sofonea, Mircea T.; Djidjou-Demasse, Ramsès; Alizon, Samuel: Non-Markovian modelling highlights the importance of age structure on Covid-19 epidemiological dynamics (2022)
  3. Gerber, Florian; Nychka, Douglas W.: Parallel cross-validation: a scalable fitting method for Gaussian process models (2021)
  4. Huang, Chaofan; Joseph, V. Roshan; Ray, Douglas M.: Constrained minimum energy designs (2021)
  5. Jakob A. Dambon, Fabio Sigrist, Reinhard Furrer: varycoef: An R Package for Gaussian Process-based Spatially Varying Coefficient Models (2021) arXiv
  6. Martin, Olivier; Fernandez-Diclo, Yasmil; Coville, Jérôme; Soubeyrand, Samuel: Equilibrium and sensitivity analysis of a spatio-temporal host-vector epidemic model (2021)
  7. Mickael Binois, Robert B. Gramacy: hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R (2021) not zbMATH
  8. Gladish, Daniel W.; Darnell, Ross; Thorburn, Peter J.; Haldankar, Bhakti: Emulated multivariate global sensitivity analysis for complex computer models applied to agricultural simulators (2019)
  9. Gu, Mengyang: Jointly robust prior for Gaussian stochastic process in emulation, calibration and variable selection (2019)
  10. Mickaël Binois and Victor Picheny: GPareto: An R Package for Gaussian-Process-Based Multi-Objective Optimization and Analysis (2019) not zbMATH
  11. Sambakhé, Diariétou; Rouan, Lauriane; Bacro, Jean-Noël; Gozé, Eric: Conditional optimization of a noisy function using a kriging metamodel (2019)
  12. Wang, Bo; Zhang, Qiong; Xie, Wei: Bayesian sequential data collection for stochastic simulation calibration (2019)
  13. Zhang, Ru; Lin, C. Devon; Ranjan, Pritam: A sequential design approach for calibrating dynamic computer simulators (2019)
  14. Antony Overstall, David Woods, Maria Adamou: acebayes: An R Package for Bayesian Optimal Design of Experiments via Approximate Coordinate Exchange (2017) arXiv
  15. Gan, Guojun; Lin, X. Sheldon: Efficient Greek calculation of variable annuity portfolios for dynamic hedging: a two-level metamodeling approach (2017)
  16. Wahl, François; Mercadier, Cécile; Helbert, Céline: A standardized distance-based index to assess the quality of space-filling designs (2017)
  17. Pieter Schoonees and Niël le Roux and Roelof Coetzer: Flexible Graphical Assessment of Experimental Designs in R: The vdg Package (2016) not zbMATH
  18. Robert Gramacy: laGP: Large-Scale Spatial Modeling via Local Approximate Gaussian Processes in R (2016) not zbMATH
  19. Blake MacDonald; Pritam Ranjan; Hugh Chipman: GPfit: An R Package for Fitting a Gaussian Process Model to Deterministic Simulator Outputs (2015) not zbMATH
  20. Delphine Dupuy; Céline Helbert; Jessica Franco: DiceDesign and DiceEval: Two R Packages for Design and Analysis of Computer Experiments (2015) not zbMATH

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