%0 Journal Article
%T Least angle and  1 penalized regression: A review
%A Tim Hesterberg
%A Nam Hee Choi
%A Lukas Meier
%A Chris Fraley
%J Statistics Surveys
%D 2008
%I Statistics Surveys
%X Least Angle Regression is a promising technique for variable selection applications, offering a nice alternative to stepwise regression. It provides an explanation for the similar behavior of LASSO ( 1-penalized regression) and forward stagewise regression, and provides a fast implementation of both. The idea has caught on rapidly, and sparked a great deal of research interest. In this paper, we give an overview of Least Angle Regression and the current state of related research.
%K Lasso
%K Regression
%K Regularization
%K 1 penalty
%K Variable selection
%U http://projecteuclid.org/euclid.ssu/1211317636