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.
|Author||Shan Ba and V. Roshan Joseph|
|Date of publication||2014-09-21 07:43:39|
|Maintainer||Shan Ba <email@example.com>|
CGP: Composite Gaussian process models
CGP.default: Default method for the CGP class
CGPEst: Estimate composite Gaussian process models
CGP-package: The composite Gaussian process model package
plotCGP: Jackknife (leave-one-out) actual by predicted diagnostic plot
predict.CGP: Predict from the composite Gaussian process model
print.CGP: CGP model summary information
summary.CGP: CGP model summary information
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