We propose a new method for estimation in linear models

The ‘lasso’ minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant

Our simulation studies suggest that the lasso enjoys some of the favourable properties of both subset selection and ridge regression

The lasso idea is quite general and can be applied in a variety of statistical models: extensions to generalized regression models and tree-based models are briefly described

Need more features? Save interactive summary cards to your Scholarcy Library.