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:
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)
NEWS
# Install 'EzGP' in R: |
install.packages('EzGP', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- EzGP_data - Dataset for the example in function 'EzGP_fit'
- LEzGP_data - Dataset for the example in function 'LEzGP_fit'
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:b6dc0e5854. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 24 2024 |
R-4.5-linux | NOTE | Dec 24 2024 |
Exports:cov_mEEzGP_fitEEzGP_predictEzGP_fitEzGP_predictLEzGP_fitLLF_gradients
Dependencies:nloptr