Structural Modeling by using Overlapped Group Penalty

Fits a linear non-penalized phenotype (demographic) variables and penalized groups of prognostic effect and predictive effect, by satisfying such hierarchy structures that if a predictive effect exists, its prognostic effect must also exist. This package can deal with continuous, binomial or multinomial, and survival response variables, underlying the assumption of Gaussian, binomial (multinomial), and Cox proportional hazard models, respectively. It is implemented by combining the iterative shrinkage-thresholding algorithm and the alternating direction method of multipliers algorithms. The main method is built in C++, and the complementary methods are written in R.


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2.1.0 by Chong Ma, a month ago

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Authors: Chong Ma [aut, cre] , Kevin Galinsky [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp, foreach, doParallel, dplyr, tidyr, magrittr, ggplot2, Rdpack, rmarkdown

Suggests survival, roxygen2, pkgdown

Linking to Rcpp, RcppArmadillo

See at CRAN