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A robust sparse linear approach for contaminated data
Shahriari, S; Faria, S; Manuela Gonçalves, AA challenging problem in a linear regression model is to select a parsimonious model which is robust to the presence of contamination in the data. In this paper, we present a sparse linear approach which detects outliers by using a highly robust regression method. The model with optimal predictive ability as measured by the median absolute deviation of the prediction errors on JackKnife subsets is used to detec...
Date: 2019
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Origin: Repositório Aberto da Universidade do Porto