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TAG: Transformed Additive Gaussian Processes

Implement the transformed additive Gaussian (TAG) process and the transformed 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.

Version:0.5.1
Depends:R (≥ 3.5.0)
Imports:Rcpp,DiceKriging,Matrix,mgcv,FastGP,mlegp,randtoolbox,foreach
LinkingTo:Rcpp,RcppArmadillo
Published:2021-06-07
DOI:10.32614/CRAN.package.TAG
Author:Li-Hsiang Lin and V. Roshan Joseph
Maintainer:Li-Hsiang Lin <llin79 at gatech.edu>
License:GPL-2
NeedsCompilation:yes
CRAN checks:TAG results[issues need fixing before 2025-12-18]

Documentation:

Reference manual:TAG.html ,TAG.pdf

Downloads:

Package source: TAG_0.5.1.tar.gz
Windows binaries: r-devel:TAG_0.5.1.zip, r-release:TAG_0.5.1.zip, r-oldrel:TAG_0.5.1.zip
macOS binaries: r-release (arm64):TAG_0.5.1.tgz, r-oldrel (arm64):TAG_0.5.1.tgz, r-release (x86_64):TAG_0.5.1.tgz, r-oldrel (x86_64):TAG_0.5.1.tgz
Old sources: TAG archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=TAGto link to this page.


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