Package: EzGP 0.1.0

Jiayi Li

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>.

Authors:Jiayi Li [cre, aut], Qian Xiao [aut], Abhyuday Mandal [aut], C. Devon Lin [aut], Xinwei Deng [aut]

EzGP_0.1.0.tar.gz
EzGP_0.1.0.tar.gz(r-4.5-noble)EzGP_0.1.0.tar.gz(r-4.4-noble)
EzGP_0.1.0.tgz(r-4.4-emscripten)EzGP_0.1.0.tgz(r-4.3-emscripten)
EzGP.pdf |EzGP.html✨
EzGP/json (API)
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7 exports 0.00 score 1 dependencies 122 downloads

Last updated 1 years agofrom:b6dc0e5854. Checks:OK: 1 NOTE: 1. Indexed: yes.

Exports:cov_mEEzGP_fitEEzGP_predictEzGP_fitEzGP_predictLEzGP_fitLLF_gradients

Dependencies:nloptr