Based solely on the dengue confirmed-cases of six densely populated urban areas in Brazil, distributed along the country, we propose in this paper regularized linear and nonlinear autoregressive models for one-week ahead ...

One of the main challenges researchers face is to identify the most relevant features in a prediction model. As a consequence, many regularized methods seeking sparsity have flourished. Although sparse, their solutions may ...

Processos não lineares frequentemente aparecem na indústria e representam um desafio para estimação e controle. Para lidar com eles, usualmente é necessário usar técnicas não lineares que levam a teorias mais avançadas, ...

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. ...

Background: Even with the addition of dermoscopy, a significant morphologic overlap exists between irritated seborrheic keratosis (ISK) and squamous cell carcinoma (SCC). Objective: The aim of this study was to investigate ...

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. ...

The Brazilian energy matrix is predominantly composed of hydroelectric plants. In this way, it is important to ensure maximum efficiency in the operation of these plants since the direct consequence is a significant impact ...