HDCI: High Dimensional Confidence Interval Based on Lasso and Bootstrap

Fits regression models on high dimensional data to estimate coefficients and use bootstrap method to obtain confidence intervals. Choices for regression models are Lasso, Lasso+OLS, Lasso partial ridge, Lasso+OLS partial ridge.

Version:	1.0-2
Imports:	glmnet, slam, parallel, foreach, iterators, doParallel, lattice, Matrix, mvtnorm
Published:	2017-06-06
DOI:	10.32614/CRAN.package.HDCI
Author:	Hanzhong Liu, Xin Xu, Jingyi Jessica Li
Maintainer:	Xin Xu <xin.xu at yale.edu>
License:	GNU General Public License version 2
NeedsCompilation:	no
CRAN checks:	HDCI results

Documentation:

Reference manual:

HDCI.html , HDCI.pdf

Downloads:

Package source:	HDCI_1.0-2.tar.gz
Windows binaries:	r-devel: HDCI_1.0-2.zip, r-release: HDCI_1.0-2.zip, r-oldrel: HDCI_1.0-2.zip
macOS binaries:	r-release (arm64): HDCI_1.0-2.tgz, r-oldrel (arm64): HDCI_1.0-2.tgz, r-release (x86_64): HDCI_1.0-2.tgz, r-oldrel (x86_64): HDCI_1.0-2.tgz

Reverse dependencies:

Reverse imports:

ACSSpack, IFAA

Linking:

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