DISSERTATION
A theory based, data driven selection for the regularization parameter for LASSO
Advisor: Marcelo Medeiros
Examiners: Ricardo Masini, Anders Kock.We provide a new way to select the regularization parameter for the LASSO and adaLASSO. It is based on the theory and incorporates an estimate of the variance of the noise. We show theoretical properties of the procedure and Monte Carlo simulations showing that it is able to handle more variables in the active set than other popular options for the regularization parameter.
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