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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.
| Version: | 2.1-1 |
| Published: | 2018-06-12 |
| DOI: | 10.32614/CRAN.package.CGP |
| Author: | Shan Ba and V. Roshan Joseph |
| Maintainer: | Shan Ba <shanbatr at gmail.com> |
| License: | LGPL-2.1 |
| NeedsCompilation: | no |
| CRAN checks: | CGP results |
| Reference manual: | CGP.pdf |
| Package source: | CGP_2.1-1.tar.gz |
| Windows binaries: | r-devel: CGP_2.1-1.zip, r-release: CGP_2.1-1.zip, r-oldrel: CGP_2.1-1.zip |
| macOS binaries: | r-release (arm64): CGP_2.1-1.tgz, r-oldrel (arm64): CGP_2.1-1.tgz, r-release (x86_64): CGP_2.1-1.tgz, r-oldrel (x86_64): CGP_2.1-1.tgz |
| Old sources: | CGP archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.