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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. ...
Ensaios em matemática aplicada: estimação e trajetórias bootstrap de oferta de sangue e estudo de desempenho de extensões do algoritmo de Programação Dinâmica Dual Estocástica
We study two topics of applied mathematics. The first topic is devoted to the estimation of blood supply time series and the generation of simulated trajectories. The main goal is to contribute to the literature of stock ...