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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("cmenet")

0.1.0 by Simon Mak, 2 months ago


Browse source code at https://github.com/cran/cmenet


Authors: Simon Mak


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, MASS, glmnet, hierNet

Linking to Rcpp, RcppArmadillo


See at CRAN