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EzGP  

Easy-to-Interpret Gaussian Process Models for Computer Experiments
View on CRAN: Click here


Download and install EzGP package within the R console
Install from CRAN:
install.packages("EzGP")

Install from Github:
library("remotes")
install_github("cran/EzGP")

Install by package version:
library("remotes")
install_version("EzGP", "0.1.0")



Attach the package and use:
library("EzGP")
Maintained by
Jiayi Li
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-07-06
Latest Update: 2023-07-06
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) .
How to cite:
Jiayi Li (2023). EzGP: Easy-to-Interpret Gaussian Process Models for Computer Experiments. R package version 0.1.0, https://cran.r-project.org/web/packages/EzGP. Accessed 18 Feb. 2025.
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Complete documentation for EzGP
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Full EzGP package functions and examples
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