SignifReg
Consistent Significance Controlled Variable Selection in Generalized Linear Regression
Provides significance controlled variable selection algorithms with different directions (forward, backward, stepwise) based on diverse criteria (AIC, BIC, adjusted r-square, PRESS, or p-value). The algorithm selects a final model with only significant variables defined as those with significant p-values after multiple testing correction such as Bonferroni, False Discovery Rate, etc. See Zambom and Kim (2018) <doi:10.1002/sta4.210>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
4.3 |
rolling linux/jammy R-4.5 | SignifReg_4.3.tar.gz |
62.9 KiB |
4.3 |
rolling linux/noble R-4.5 | SignifReg_4.3.tar.gz |
62.8 KiB |
4.3 |
rolling source/ R- | SignifReg_4.3.tar.gz |
12.4 KiB |
4.3 |
latest linux/jammy R-4.5 | SignifReg_4.3.tar.gz |
62.9 KiB |
4.3 |
latest linux/noble R-4.5 | SignifReg_4.3.tar.gz |
62.8 KiB |
4.3 |
latest source/ R- | SignifReg_4.3.tar.gz |
12.4 KiB |
4.3 |
2026-04-26 source/ R- | SignifReg_4.3.tar.gz |
12.4 KiB |
4.3 |
2026-04-23 source/ R- | SignifReg_4.3.tar.gz |
12.4 KiB |
4.3 |
2026-04-09 windows/windows R-4.5 | SignifReg_4.3.zip |
65.5 KiB |
4.3 |
2025-04-20 source/ R- | SignifReg_4.3.tar.gz |
12.4 KiB |