In this paper, we compare two different variable selection approaches for linear regression models: Autometrics … (automatic general-to-specific selection) and LASSO (?1-norm regularization). In a simulation study, we show 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 …

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 …

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

of large-scale regressions with LASSO is applied to reduce the dimensionality, and an overall penalty level is carefully …