LassoSIR
Sparsed Sliced Inverse Regression via Lasso
Estimate the sufficient dimension reduction space using sparsed sliced inverse regression via Lasso (Lasso-SIR) introduced in Lin, Zhao, and Liu (2019) <doi:10.1080/01621459.2018.1520115>. The Lasso-SIR is consistent and achieve the optimal convergence rate under certain sparsity conditions for the multiple index models.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling linux/jammy R-4.5 | LassoSIR_1.0.tar.gz |
28.3 KiB |
1.0 |
rolling linux/noble R-4.5 | LassoSIR_1.0.tar.gz |
28.3 KiB |
1.0 |
rolling source/ R- | LassoSIR_1.0.tar.gz |
10.6 KiB |
1.0 |
latest linux/jammy R-4.5 | LassoSIR_1.0.tar.gz |
28.3 KiB |
1.0 |
latest linux/noble R-4.5 | LassoSIR_1.0.tar.gz |
28.3 KiB |
1.0 |
latest source/ R- | LassoSIR_1.0.tar.gz |
10.6 KiB |
1.0 |
2026-04-26 source/ R- | LassoSIR_1.0.tar.gz |
10.6 KiB |
1.0 |
2026-04-23 source/ R- | LassoSIR_1.0.tar.gz |
10.6 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | LassoSIR_1.0.zip |
31.0 KiB |
1.0 |
2025-04-20 source/ R- | LassoSIR_1.0.tar.gz |
10.6 KiB |