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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 gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: LassoSIR results

Documentation:

Reference manual: LassoSIR.pdf

Downloads:

Package source: LassoSIR_0.1.1.tar.gz
Windows binaries: r-devel: LassoSIR_0.1.1.zip, r-release: LassoSIR_0.1.1.zip, r-oldrel: LassoSIR_0.1.1.zip
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

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.