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TAG
View on CRAN: Click
here
Download and install TAG package within the R console
Install from CRAN:
install.packages("TAG")
Install from Github:
library("remotes")
install_github("cran/TAG") Install by package version:
library("remotes")
install_version("TAG", "0.7.1") Attach the package and use:
library("TAG")
Maintained by
Li-Hsiang Lin
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-09-27
Latest Update: 2021-06-07
Description:
Implement the transformed additive Gaussian (TAG) process and thetransformed approximately additive Gaussian (TAAG) process proposed in Lin and Joseph (2020) <doi:10.1080/00401706.2019.1665592>. These functions can be used to model deterministic computer experiments, obtain predictions at new inputs, and quantify the uncertainty of the predictions. This research is supported by a U.S. National Science Foundation grant DMS-1712642 and a U.S. Army Research Office grant W911NF-17-1-0007.
How to cite:
Li-Hsiang Lin (2019). TAG: Transformed Additive Gaussian Processes. R package version 0.7.1, https://cran.r-project.org/web/packages/TAG. Accessed 17 Jul. 2026.
Previous versions and publish date:
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Complete documentation for TAG
Functions, R codes and Examples using
the TAG R package
Some associated functions: Initial.TAG . TAAG . TAG . TAG1step . check.TAAG . loocv.TAAG . plot.TAG . pred.TAAG . pred.TAG .
Some associated R codes: Check.R . Initial_TAG.R . LOOCV_TAAG.R . RcppExports.R . TAAG.R . TAG.R . TAG1step.R . plot_TAG.R . pred_TAAG.R . pred_TAG.R . Full TAG package functions and examples
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