Bi-Level Selection of Conditional Main Effects

Provides functions for implementing cmenet - a bi-level variable selection method for conditional main effects (see Mak and Wu (2018) ). CMEs are reparametrized interaction effects which capture the conditional impact of a factor at a fixed level of another factor. Compared to traditional two-factor interactions, CMEs quantify more interpretable interaction effects in many problems of interest (e.g., genomics, molecular engineering, personalized medicine). The current implementation performs variable selection on only binary CMEs, but we are working on an extension for the continuous setting. This work was supported by USARO grant W911NF-14-1-0024.


Reference manual

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0.1.0 by Simon Mak, 6 months ago

Browse source code at

Authors: Simon Mak

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp, MASS, glmnet, hierNet

Linking to Rcpp, RcppArmadillo

See at CRAN