Package: GPM
Type: Package
Title: Gaussian Process Modeling of Multi-Response Datasets
Version: 1.0.2
Date: 2018-07-23
Author: Ramin Bostanabad, Wei Chen (IDEAL)
Maintainer: Ramin Bostanabad <bostanabad@u.northwestern.edu>
Description: Provides a general and efficient tool for fitting a response surface to datasets via Gaussian processes. The dataset can have multiple responses and the fitted GP model can predict the gradient as well. The package is based on the work of Bostanabad, R., Kearney, T., Tao, S. Y., Apley, D. W. & Chen, W. (2018) Leveraging the nugget parameter for efficient Gaussian process modeling. International Journal for Numerical Methods in Engineering, 114, 501-516.
License: GPL-2
LazyData: FALSE
Imports: lhs(>= 0.14), randtoolbox(>= 1.17), lattice(>= 0.20-34),
        grDevices, graphics
Depends: R (>= 3.2.5), stats (>= 3.2.5)
Repository: CRAN
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-07-23 18:12:50 UTC; ramin
Date/Publication: 2018-07-23 18:30:07 UTC
