GPM: Gaussian Process Modeling of Multi-Response Datasets

Provides a general and efficient tool for fitting a response surface to datasets via Gaussian processes. The dataset can have multiple responses. The package is based on the work of Bostanabad, R., Kearney, T., Tao, S., Apley, D. W. & Chen, W. Leveraging the nugget parameter for efficient Gaussian process modeling (2017) <doi:10.1002/nme.5751>.

Version: 1.0
Depends: R (≥ 3.2.5), stats (≥ 3.2.5)
Imports: lhs (≥ 0.14), randtoolbox (≥ 1.17), lattice (≥ 0.20-34)
Published: 2018-01-05
Author: Ramin Bostanabad
Maintainer: Ramin Bostanabad <bostanabad at u.northwestern.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: GPM results

Downloads:

Reference manual: GPM.pdf
Package source: GPM_1.0.tar.gz
Windows binaries: r-devel: GPM_1.0.zip, r-release: GPM_1.0.zip, r-oldrel: GPM_1.0.zip
OS X El Capitan binaries: r-release: GPM_1.0.tgz
OS X Mavericks binaries: r-oldrel: GPM_1.0.tgz

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