(automatic general-to-specific selection) and LASSO (?1-norm regularization). In a simulation study, we show the performance of …

(automatic general-to-specific selection) and LASSO (ℓ1-norm regularization). In a simulation study, we show the performance of …

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 …

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 strongly correlated predictors. An alternative to the Lasso is constituted by model …

options are provided: the conventional least absolute shrinkage and selection operator (LASSO) for metric covariates, and both … group and fused LASSO for categorical predictors. The methods are investigated both for simulated data and for two real data …

LASSO, adaptive LASSO, and hard-thresholding are analyzed. It is shown that symmetric intervals are the shortest. The length … based on the adaptive LASSO, which is larger than the length of the shortest interval based on the LASSO, which in turn is …