Package: EzGP
Title: Easy-to-Interpret Gaussian Process Models for Computer
        Experiments
Version: 0.1.0
Authors@R: c(
    person("Jiayi", "Li", email = "jiayili0123@outlook.com", role = c("cre", "aut")),
    person("Qian", "Xiao", email = "QIAN.XIAO@uga.edu", role = "aut"),
    person("Abhyuday", "Mandal", email = "abhyuday@uga.edu", role = "aut"),
    person("C. Devon", "Lin", email = "devon.lin@queensu.ca", role = "aut"),
    person("Xinwei", "Deng", email = "xdeng@vt.edu", role = "aut"))
Description: Fit model for datasets with easy-to-interpret Gaussian process modeling, predict responses for new inputs.
    The input variables of the datasets can be quantitative, qualitative/categorical or mixed.
    The output variable of the datasets is a scalar (quantitative).
    The optimization of the likelihood function can be chosen by the users (see the documentation of EzGP_fit()).
    The modeling method is published in "EzGP: Easy-to-Interpret Gaussian Process Models for Computer Experiments with Both Quantitative and Qualitative Factors" 
    by Qian Xiao, Abhyuday Mandal, C. Devon Lin, and Xinwei Deng (2022) <doi:10.1137/19M1288462>. 
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.0
Depends: R (>= 4.2.0), stats (>= 4.2.0)
Imports: methods (>= 4.2.0), nloptr (>= 2.0.3)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2023-07-05 20:20:10 UTC; 93421
Author: Jiayi Li [cre, aut],
  Qian Xiao [aut],
  Abhyuday Mandal [aut],
  C. Devon Lin [aut],
  Xinwei Deng [aut]
Maintainer: Jiayi Li <jiayili0123@outlook.com>
Repository: CRAN
Date/Publication: 2023-07-06 18:40:08 UTC
Built: R 4.3.3; ; 2025-01-24 07:20:15 UTC; unix
