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
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

Downloads:

Reference manual: HDCI.pdf
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
OS X binaries: r-release: HDCI_1.0-2.tgz, r-oldrel: HDCI_1.0-2.tgz

Reverse dependencies:

Reverse imports: tensorsparse

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