Linear Multiple Output Sparse Group Lasso

Linear multiple output using sparse group lasso. The algorithm finds the sparse group lasso penalized maximum likelihood estimator. This result in feature and parameter selection, and parameter estimation. Use of parallel computing for cross validation and subsampling is supported through the 'foreach' and 'doParallel' packages. Development version is on GitHub, please report package issues on GitHub.


Reference manual

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1.3.6 by Martin Vincent, a year ago

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Authors: Martin Vincent

Documentation:   PDF Manual  

GPL (>= 2) license

Imports methods, utils, stats

Depends on Matrix, sglOptim

Suggests knitr, rmarkdown

Linking to sglOptim, Rcpp, RcppProgress, RcppArmadillo, BH

See at CRAN