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.
- Version1.0.0
- R versionunknown
- LicenseMIT
- Needs compilation?No
- Last release04/09/2021
Documentation
Team
Donald Williams
MaintainerShow author details
Insights
Last 30 days
This package has been downloaded 138 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 5 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 1,845 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jul 21, 2024 with 65 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Imports5 packages