Sparse Group Lasso
Regularization paths for sparse group-lasso models
Extract coefficients from a cv.sparsegl object.
Extract model coefficients from a sparsegl object.
Cross-validation for a sparsegl object.
Calculate information criteria.
Calculate common norms
Create starting values for iterative reweighted least squares
Pipe operator
Plot cross-validation curves produced from a cv.sparsegl object.
Plot solution paths from a sparsegl object.
Make predictions from a cv.sparsegl object.
Make predictions from a sparsegl object.
sparsegl: Sparse Group Lasso
Efficient implementation of sparse group lasso with optional bound constraints on the coefficients; see <doi:10.18637/jss.v110.i06>. It supports the use of a sparse design matrix as well as returning coefficient estimates in a sparse matrix. Furthermore, it correctly calculates the degrees of freedom to allow for information criteria rather than cross-validation with very large data. Finally, the interface to compiled code avoids unnecessary copies and allows for the use of long integers.
Useful links