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 (2017) <doi:10.48550/arXiv.1611.06655>. The Lasso-SIR is consistent and achieve the optimal convergence rate under certain sparsity conditions for the multiple index models.

Version: 0.1.1
Imports: glmnet, graphics, stats
Published: 2017-12-06
DOI: 10.32614/CRAN.package.LassoSIR
Author: Zhigen Zhao, Qian Lin, Jun Liu
Maintainer: Zhigen Zhao <zhigen.zhao at>
License: GPL-3
NeedsCompilation: no
CRAN checks: LassoSIR results


Reference manual: LassoSIR.pdf


Package source: LassoSIR_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): LassoSIR_0.1.1.tgz, r-oldrel (arm64): LassoSIR_0.1.1.tgz, r-release (x86_64): LassoSIR_0.1.1.tgz, r-oldrel (x86_64): LassoSIR_0.1.1.tgz
Old sources: LassoSIR archive


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