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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

Documentation:

Reference manual: 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 form https://CRAN.R-project.org/package=TAG to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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