Package: GEMSS 0.1.1

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:Sheng-Zhan Hua [aut, cre]

GEMSS_0.1.1.tar.gz
GEMSS_0.1.1.zip(r-4.7-x86_64)GEMSS_0.1.1.zip(r-4.7-arm64)GEMSS_0.1.1.zip(r-4.6-x86_64)GEMSS_0.1.1.zip(r-4.6-arm64)GEMSS_0.1.1.zip(r-4.5-x86_64)
GEMSS_0.1.1.tgz(r-4.6-x86_64)GEMSS_0.1.1.tgz(r-4.6-arm64)GEMSS_0.1.1.tgz(r-4.5-x86_64)GEMSS_0.1.1.tgz(r-4.5-arm64)
GEMSS_0.1.1.tar.gz(r-4.7-arm64)GEMSS_0.1.1.tar.gz(r-4.7-x86_64)GEMSS_0.1.1.tar.gz(r-4.6-arm64)GEMSS_0.1.1.tar.gz(r-4.6-x86_64)
GEMSS_0.1.1.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://szhua-stat.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/szhua-stat/gemss/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

3.65 score 200 downloads 4 exports 8 dependencies

Last updated from:9531810e69. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK106
linux-devel-x86_64OK125
source / vignettesOK190
linux-release-arm64OK141
linux-release-x86_64OK121
macos-release-arm64OK138
macos-release-x86_64OK368
macos-oldrel-arm64OK120
macos-oldrel-x86_64OK462
windows-devel-arm64OK353
windows-devel-x86_64OK146
windows-release-arm64OK340
windows-release-x86_64OK106
windows-oldrel-x86_64OK110
wasm-releaseOK97

Exports:compute_kernelgemss_removegemss_selectgp_predict

Dependencies:DiceDesignhetGPMASSmcoquadprogRcppRcppArmadillotwinning