Efficient algorithms for fitting the regularization path of linear regression, GLM, and Cox regression models with grouped penalties. This includes group selection methods such as group lasso, group MCP, and group SCAD as well as bilevel selection methods such as the group exponential lasso, the composite MCP, and the group bridge. For more information, see Breheny and Huang (2009) <doi:10.4310/sii.2009.v2.n3.a10>, Huang, Breheny, and Ma (2012) <doi:10.1214/12sts392>, Breheny and Huang (2015) <doi:10.1007/s1122201394242>, and Breheny (2015) <doi:10.1111/biom.12300>, or visit the package homepage <https://pbreheny.github.io/grpreg/>.
Package details 


Maintainer  
License  GPL3 
Version  3.4.0.1 
URL  https://pbreheny.github.io/grpreg/ https://github.com/pbreheny/grpreg 
Package repository  View on GitHub 
Installation 
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