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 …

selected by first-step penalized estimators, typically LASSO. It is well known that LASSO can estimate the regression function … at nearly the oracle rate, and is thus hard to improve upon. We show that post-LASSO performs at least as well as LASSO … the LASSO-based model selection fails” in the sense of missing some components of the true” regression model. By the true …

continuum of target parameters is of interest and the Lasso-type or post-Lasso type methods are used to estimate a continuum of … establish rate and consistency results for continua of Lasso or post-Lasso type methods for estimating continua of the (nuisance …

In this paper we show the validity of the adaptive LASSO procedure in estimating stationary ARDL(p,q) models with GARCH … innovations. We show that, given a set of initial weights, the adaptive Lasso selects the relevant variables with probability … variables beforehand. Finally, we show that the LASSO estimator can be used to construct the initial weights. The performance of …

for a continuum of target parameters and for Lasso-type or Post-Lasso type methods to be used as estimators of a continuum … continua of Lasso or Post-Lasso type estimators for continua of (nuisance) regression functions and provide practical …