SplitKnockoff
Split Knockoffs for Structural Sparsity
Split Knockoff is a data adaptive variable selection framework for controlling the (directional) false discovery rate (FDR) in structural sparsity, where variable selection on linear transformation of parameters is of concern. This proposed scheme relaxes the linear subspace constraint to its neighborhood, often known as variable splitting in optimization. Simulation experiments can be reproduced following the Vignette. 'Split Knockoffs' is first defined in Cao et al. (2021) <doi:10.48550/arXiv.2103.16159>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.1 |
rolling linux/jammy R-4.5 | SplitKnockoff_2.1.tar.gz |
81.6 KiB |
2.1 |
rolling linux/noble R-4.5 | SplitKnockoff_2.1.tar.gz |
81.4 KiB |
2.1 |
rolling source/ R- | SplitKnockoff_2.1.tar.gz |
31.4 KiB |
2.1 |
latest linux/jammy R-4.5 | SplitKnockoff_2.1.tar.gz |
81.6 KiB |
2.1 |
latest linux/noble R-4.5 | SplitKnockoff_2.1.tar.gz |
81.4 KiB |
2.1 |
latest source/ R- | SplitKnockoff_2.1.tar.gz |
31.4 KiB |
2.1 |
2026-04-26 source/ R- | SplitKnockoff_2.1.tar.gz |
31.4 KiB |
2.1 |
2026-04-23 source/ R- | SplitKnockoff_2.1.tar.gz |
31.4 KiB |
2.1 |
2026-04-09 windows/windows R-4.5 | SplitKnockoff_2.1.zip |
84.3 KiB |
2.1 |
2025-04-20 source/ R- | SplitKnockoff_2.1.tar.gz |
31.4 KiB |