ABSTRACT
In the previous chapter, we considered some generalizations of the lasso obtained by varying the loss function. In this chapter, we turn to some useful variations of the basic lasso `1-penalty itself, which expand the scope of the basic model. They all inherit the two essential features of the standard lasso, namely the shrinkage and selection of variables, or groups of variables.
