  Asg is a Python package that solves penalized linear regression and quantile
regression models for simultaneous variable selection and prediction, for both
high and low dimensional frameworks. It makes very easy to set up and solve
different types of lasso-based penalizations among which the asgl (adaptive
sparse group lasso, that gives name to the package) is remarked. This package
is built on top of cvxpy, a Python-embedded modeling language for convex
optimization problems and makes extensive use of multiprocessing, a Python
module for parallel computing that significantly reduces computation times of
asgl.
