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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. ...
Algoritmos para geração da frente de Pareto da regressão Lasso
(Universidade Federal de Juiz de Fora (UFJF)BrasilICE – Instituto de Ciências ExatasMestrado Acadêmico em MatemáticaUFJF, 2023)
Avaliação do lasso e métodos alternativos em modelos de regressão logística
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus São Carlos, 2021-03-11)
Logistic regression has always been an important tool not only in the area of statistics, but also in several other areas such as economic, biological and medical. In many of these areas it is common to encounter problems ...
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. ...
Ridge, Lasso and Bayesian additive-dominance genomic models
(BMC Genetics, 2017)