Package: TAG 0.7.1

Li-Hsiang Lin

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.

Authors:Li-Hsiang Lin [aut, cre], V. Roshan Joseph [aut]

TAG_0.7.1.tar.gz
TAG_0.7.1.tar.gz(r-4.7-arm64)TAG_0.7.1.tar.gz(r-4.7-x86_64)TAG_0.7.1.tar.gz(r-4.6-arm64)TAG_0.7.1.tar.gz(r-4.6-x86_64)
TAG_0.7.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
TAG/json (API)

# Install 'TAG' in R:
install.packages('TAG', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

3.16 score 145 scripts 499 downloads 66 mentions 9 exports 17 dependencies

Last updated from:8be27154a5. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK167
linux-devel-x86_64OK169
source / vignettesOK180
linux-release-arm64OK172
linux-release-x86_64OK142
wasm-releaseOK111

Exports:check.TAAGcv.TAAGinitial.TAGplotTAGpred.TAAGpred.TAGTAAGTAGTAG1step

Dependencies:codetoolsDiceKrigingFastGPforeachiteratorslatticeMASSMatrixmgcvmlegpmvtnormnlmerandtoolboxRcppRcppArmadilloRcppEigenrngWELL