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 …

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

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

We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time …

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 …

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 …

We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time …