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Implements the Generalization Error Minimization in SubSampling (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.
| Version: | 0.1.1 |
| Imports: | Rcpp (≥ 1.0.0), hetGP, twinning |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | ContourFunctions |
| Published: | 2026-05-27 |
| DOI: | 10.32614/CRAN.package.GEMSS |
| Author: | Sheng-Zhan Hua [aut, cre] |
| Maintainer: | Sheng-Zhan Hua <szhua at g.ucla.edu> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| Citation: | GEMSS citation info |
| Materials: | README |
| CRAN checks: | GEMSS results |
| Reference manual: | GEMSS.html , GEMSS.pdf |
| Package source: | GEMSS_0.1.1.tar.gz |
| Windows binaries: | r-devel: GEMSS_0.1.1.zip, r-release: GEMSS_0.1.1.zip, r-oldrel: GEMSS_0.1.1.zip |
| macOS binaries: | r-release (arm64): GEMSS_0.1.1.tgz, r-oldrel (arm64): GEMSS_0.1.1.tgz, r-release (x86_64): GEMSS_0.1.1.tgz, r-oldrel (x86_64): GEMSS_0.1.1.tgz |
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