IRCcheck: Irrepresentable Condition Check

Check the irrepresentable condition (IRC) in both L1-regularized regression <doi:10.1109/TIT.2006.883611> and Gaussian graphical models. The IRC requires that the important and unimportant variables are not correlated, at least not all that much, and it is necessary for consistent model selection. Exploring the IRC as a function of the number of variables, assumed sparsity, and effect size can provide valuable insights into the model selection properties of L1-regularization.

Version:	1.0.0
Imports:	glmnet, MASS, Rdpack, GGMncv, corpcor, parallel
Published:	2021-04-09
Author:	Donald Williams [aut, cre]
Maintainer:	Donald Williams <drwwilliams at ucdavis.edu>
License:	MIT + file LICENSE
NeedsCompilation:	no
Materials:	README
CRAN checks:	IRCcheck results

Documentation:

Reference manual:

IRCcheck.pdf

Downloads:

Package source:	IRCcheck_1.0.0.tar.gz
Windows binaries:	r-devel: IRCcheck_1.0.0.zip, r-release: IRCcheck_1.0.0.zip, r-oldrel: IRCcheck_1.0.0.zip
macOS binaries:	r-release (arm64): IRCcheck_1.0.0.tgz, r-oldrel (arm64): IRCcheck_1.0.0.tgz, r-release (x86_64): IRCcheck_1.0.0.tgz, r-oldrel (x86_64): IRCcheck_1.0.0.tgz

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