 Lava estimator

The Lava estimator minimizes $\Vert Y-X(\delta +\beta ){\Vert }_2^2/(2n)+{\lambda }_1\Vert \delta {\Vert }_1+{\lambda }_2\Vert \beta {\Vert }_2^2$. It combines a component selected by Lasso with a component shrunk by ridge regression. Profiling the latter yields a transformed Lasso problem; this is not the same coefficient penalty as elastic net regularization.