popular approaches in this research field is given by Lasso-type methods. An alternative approach is based on information … criteria. In contrast to the Lasso, these methods also work well in the case of highly correlated predictors. However, this …

We use lasso methods to shrink, select and estimate the network linking the publicly-traded subset of the world's top …

Summary This study presents a first comparative analysis of Lasso-type (Lasso, adaptive Lasso, elastic net) and … heuristic subset selection methods. Although the Lasso has shown success in many situations, it has some limitations. In … particular, inconsistent results are obtained for pairwise highly correlated predictors. An alternative to the Lasso is …

This paper establishes non-asymptotic oracle inequalities for the prediction error and estimation accuracy of the LASSO … in stationary vector autoregressive models. These inequalities are used to establish consistency of the LASSO even when … excluded. Next, non-asymptotic probabilities are given for the Adaptive LASSO to select the correct sign pattern (and hence the …

individual specific variables that all could potentially impact the retirement decision.We use variants of the Lasso and the … adaptive Lasso applied to logistic regression in order to uncover determinants of the retirement decision. To the best of our …

the estimation error of the Lasso under two different sets of conditions on the covariates as well as the error terms … constants. These results are then used to show that the Lasso can be consistent in even very large models where the number of … regressors increases at an exponential rate in the sample size. Conditions under which the Lasso does not discard any relevant …