GroupLasso INTERactionNET. Fits linear pairwiseinteraction models that satisfy strong hierarchy: if an interaction coefficient is estimated to be nonzero, then its two associated main effects also have nonzero estimated coefficients. Accommodates categorical variables (factors) with arbitrary numbers of levels, continuous variables, and combinations thereof. Implements the machinery described in the paper "Learning interactions via hierarchical grouplasso regularization" (JCGS 2015, Volume 24, Issue 3). Michael Lim & Trevor Hastie (2015)
Package details 


Author  Michael Lim, Trevor Hastie 
Date of publication  20180615 06:13:02 UTC 
Maintainer  Michael Lim <[email protected]> 
License  GPL2 
Version  1.0.8 
URL  http://web.stanford.edu/~hastie/Papers/glinternet_jcgs.pdf 
Package repository  View on CRAN 
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