Package: TAG 0.5.1
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:
TAG_0.5.1.tar.gz
TAG_0.5.1.tar.gz(r-4.5-noble)TAG_0.5.1.tar.gz(r-4.4-noble)
TAG_0.5.1.tgz(r-4.4-emscripten)TAG_0.5.1.tgz(r-4.3-emscripten)
TAG.pdf |TAG.html✨
TAG/json (API)
| # Install 'TAG' in R: |
| install.packages('TAG', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:27fb769e41. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 19 2024 |
| R-4.5-linux-x86_64 | NOTE | Sep 19 2024 |
Exports:check.TAAGcv.TAAGinitial.TAGplotTAGpred.TAAGpred.TAGTAAGTAGTAG1step
Dependencies:codetoolsDiceKrigingFastGPforeachiteratorslatticeMASSMatrixmgcvmlegpmvtnormnlmerandtoolboxrbenchmarkRcppRcppArmadilloRcppEigenrngWELL
