Package: LVGP
Type: Package
Title: Latent Variable Gaussian Process Modeling with Qualitative and
        Quantitative Input Variables
Version: 2.1.3
Author: Siyu Tao, Yichi Zhang
Maintainer: Siyu Tao <siyutao2020@u.northwestern.edu>
Description: Fit response surfaces for datasets with latent-variable Gaussian process modeling, predict responses for new inputs, and plot latent variables locations in the latent space (1D or 2D).
    The input variables of the datasets can be quantitative, qualitative/categorical or mixed.
    The output variable of the datasets is a scalar (quantitative).
    The method is published in "A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors"
    by Yichi Zhang, Siyu Tao, Wei Chen, and Daniel W. Apley (2018) <arXiv:1806.07504>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: lhs(>= 0.14), randtoolbox(>= 1.17), lattice(>= 0.20-34)
Depends: R (>= 3.5.0), stats (>= 3.2.5), parallel (>= 3.2.5)
Repository: CRAN
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-07-30 22:42:42 UTC; SiyuTao
Date/Publication: 2018-07-31 10:20:10 UTC
