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) <arxiv:1611.06655>. The Lasso-SIR is consistent and achieve the optimal convergence rate under certain sparsity conditions for the multiple index models.

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Description file content

Package
LassoSIR
Type
Package
Title
Sparsed Sliced Inverse Regression via Lasso
Version
0.1.1
Date
2017-12-06
Author
Zhigen Zhao, Qian Lin, Jun Liu
Maintainer
Zhigen Zhao
Description
Estimate the sufficient dimension reduction space using sparsed sliced inverse regression via Lasso (Lasso-SIR) introduced in Lin, Zhao, and Liu (2017) . The Lasso-SIR is consistent and achieve the optimal convergence rate under certain sparsity conditions for the multiple index models.
License
GPL-3
Imports
glmnet, graphics, stats
NeedsCompilation
no
Packaged
2017-12-06 16:40:52 UTC; zhaozhg
Repository
CRAN
Date/Publication
2017-12-06 16:55:39 UTC

install.packages('LassoSIR')

0.1.1

7 days ago

Zhigen Zhao

GPL-3

Imports

glmnet, graphics, stats

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