A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the annual income of a person based on their sex, age, State where they live and ...

The application of the lasso is espoused in high dimensional settings where only a small number of the regression coefficients are believed to be non-zero (i.e. the solution is sparse). Moreover, ...

We study the asymptotic properties of the adaptive Lasso estimators in sparse, high-dimensional, linear regression models when the number of covariates may increase with the sample size. We consider ...