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: 0.7.1
Depends: R (≥ 3.5.0)
Imports: Rcpp, DiceKriging, Matrix, mgcv, FastGP, mlegp, randtoolbox, foreach
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (≥ 3.0.0)
Published: 2026-04-10
DOI: 10.32614/CRAN.package.TAG
Author: Li-Hsiang Lin [aut, cre], V. Roshan Joseph [aut]
Maintainer: Li-Hsiang Lin <lhlin at gsu.edu>
License: GPL-2
NeedsCompilation: yes
CRAN checks: TAG results

Documentation:

Reference manual: TAG.html , TAG.pdf

Downloads:

Package source: TAG_0.7.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): TAG_0.7.1.tgz, r-oldrel (x86_64): TAG_0.7.1.tgz
Old sources: TAG archive

Linking:

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