Package: GEMSS 0.1.2
Sheng-Zhan Hua
GEMSS: Generalization Error Minimization in SubSampling for Gaussian Processes
Implements the GEMSS algorithm for sequential subdata selection in large-scale Gaussian process modeling (Chang, Hua, and Wu, 2026) <doi:10.1080/00401706.2026.2670596>. The method selects data points by a criterion consisting of predictive and space-filling parts, enabling efficient surrogate modeling for massive datasets.
Authors:
GEMSS_0.1.2.tar.gz
GEMSS_0.1.2.zip(r-4.7-x86_64)GEMSS_0.1.2.zip(r-4.7-arm64)GEMSS_0.1.2.zip(r-4.6-x86_64)GEMSS_0.1.2.zip(r-4.6-arm64)
GEMSS_0.1.2.tar.gz(r-4.7-arm64)GEMSS_0.1.2.tar.gz(r-4.7-x86_64)GEMSS_0.1.2.tar.gz(r-4.6-arm64)GEMSS_0.1.2.tar.gz(r-4.6-x86_64)
GEMSS_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
GEMSS/json (API)
| # Install 'GEMSS' in R: |
| install.packages('GEMSS', 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 from:86cf2ad35e. Checks:10 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 130 | ||
| linux-devel-x86_64 | OK | 118 | ||
| source / vignettes | OK | 168 | ||
| linux-release-arm64 | OK | 144 | ||
| linux-release-x86_64 | OK | 118 | ||
| windows-devel-arm64 | OK | 222 | ||
| windows-devel-x86_64 | OK | 150 | ||
| windows-release-arm64 | OK | 191 | ||
| windows-release-x86_64 | OK | 124 | ||
| wasm-release | OK | 124 |
Exports:compute_kernelgemss_removegemss_selectgp_predict
Dependencies:DiceDesignhetGPMASSmcoquadprogRcppRcppArmadillotwinning
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compute the Correlation Matrix for Specified Kernels | compute_kernel |
| Redundant Data Removal via GEMSS | gemss_remove |
| Subdata Selection via GEMSS | gemss_select |
| Gaussian Process Prediction | gp_predict |