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Adaptive LASSO estimation for ARDL models with GARCH innovations
(Taylor & Francis Inc, 2017)
In this paper, we show the validity of the adaptive least absolute shrinkage and selection operator (LASSO) procedure in estimating stationary autoregressive distributed lag(p,q) models with innovations in a broad class ...
L(1)-regularization of high-dimensional time-series models with non-gaussian and heteroskedastic errors
(Elsevier Science Sa, 2016-03)
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. The adaLASSO is a one-step implementation of the family of folded concave penalized least-squares. ...
LAGRIME DI SAN PIETRO BY ORLANDO DI LASSO: AN ANALYSIS ON ITS PERFORMANCE
(Univ Federal GoiasGoiania GoBrasil, 2011)
ℓ1-regularization of high-dimensional time-series models with non-Gaussian and heteroskedastic errors
(Elsevier Ltd, 2016)
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. The adaLASSO is a one-step implementation of the family of folded concave penalized least-squares. ...
An Unwelcomed Deja-Vu: Ecuadorian Politics in 2021
(2022)
This paper explains the configuration of the political scenario in Ecuador after the 2021 general elections. The pandemic left a challenging economic and social aftermath that created policy challenges for the new government. ...
Forecasting large covariance matrices: comparing autometrics and LASSOVAR
(2019)
This study aims to compare the performance of two well known automatic model selection algorithms, Autometrics (Hendry and Krolzig, 1999; Doornik, 2009), LASSOVAR and adaptive LASSOVAR (Callot et al., 2017) for modelling ...