R package CGP: Composite Gaussian Process Models. Fit composite Gaussian process (CGP) models as described in Ba and Joseph (2012) ”Composite Gaussian Process Models for Emulating Expensive Functions”, Annals of Applied Statistics. The CGP model is capable of approximating complex surfaces that are not second-order stationary. Important functions in this package are CGP, print.CGP, summary.CGP, predict.CGP and plotCGP.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Davis, Casey B.; Hans, Christopher M.; Santner, Thomas J.: Prediction of non-stationary response functions using a Bayesian composite Gaussian process (2021)
- Volodina, Victoria; Williamson, Daniel: Diagnostics-driven nonstationary emulators using kernel mixtures (2020)