OPTS
Optimization via Subsampling (OPTS)
Subsampling based variable selection for low dimensional generalized linear models. The methods repeatedly subsample the data minimizing an information criterion (AIC/BIC) over a sequence of nested models for each subsample. Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable selection for generalized linear models.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1 |
rolling linux/jammy R-4.5 | OPTS_0.1.tar.gz |
27.3 KiB |
0.1 |
rolling linux/noble R-4.5 | OPTS_0.1.tar.gz |
27.2 KiB |
0.1 |
rolling source/ R- | OPTS_0.1.tar.gz |
3.7 KiB |
0.1 |
latest linux/jammy R-4.5 | OPTS_0.1.tar.gz |
27.3 KiB |
0.1 |
latest linux/noble R-4.5 | OPTS_0.1.tar.gz |
27.2 KiB |
0.1 |
latest source/ R- | OPTS_0.1.tar.gz |
3.7 KiB |
0.1 |
2026-04-26 source/ R- | OPTS_0.1.tar.gz |
3.7 KiB |
0.1 |
2026-04-23 source/ R- | OPTS_0.1.tar.gz |
3.7 KiB |
0.1 |
2026-04-09 windows/windows R-4.5 | OPTS_0.1.zip |
29.8 KiB |
0.1 |
2025-04-20 source/ R- | OPTS_0.1.tar.gz |
3.7 KiB |