EzGP:Easy-to-Interpret Gaussian Process Models for Computer
Experiments
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>.
