GEMSS
Generalization Error Minimization in SubSampling for Gaussian Processes
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling linux/jammy R-4.5 | GEMSS_0.1.1.tar.gz |
162.3 KiB |
0.1.1 |
rolling linux/noble R-4.5 | GEMSS_0.1.1.tar.gz |
167.7 KiB |
0.1.1 |
rolling source/ R- | GEMSS_0.1.1.tar.gz |
15.3 KiB |
0.1.1 |
latest linux/jammy R-4.5 | GEMSS_0.1.1.tar.gz |
162.3 KiB |
0.1.1 |
latest linux/noble R-4.5 | GEMSS_0.1.1.tar.gz |
167.7 KiB |
0.1.1 |
latest source/ R- | GEMSS_0.1.1.tar.gz |
15.3 KiB |
0.1.1 |
2026-04-23 source/ R- | GEMSS_0.1.1.tar.gz |
0 B |