Linear multiple output using sparse group lasso
sglOptim, Rcpp, RcppProgress, RcppArmadillo, BH
'lsgl_fit.R' 'lsgl_cv.R' 'lsgl_predict.R' 'lsgl_config.R'
'lsgl_navigate.R'

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 multiple processors for cross validation and subsampling is supported through OpenMP. Development version is on github.

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 multiple
processors for cross validation and subsampling is supported through OpenMP.
Development version is on github.

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.

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.

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.