where Y is the response, or dependent, variable, the Xs represent the p explanatory variables, and the bs are the regression coefficients. For example, suppose that you would like to model a person's ...

An example from Neter, Wasserman, and Kutner (1990) follows. An economist is investigating the relationship between the size of an insurance firm and the speed at which they implement new insurance ...

Recent research has focused on l1 penalized least squares (Lasso) estimators for high-dimensional linear regressions in which the number of covariates p is considerably larger than the sample size n.