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Recently, variable selection based on penalized regression methods has received a great deal of attention, mostly through frequentist’s models. This paper investigates regularization regression from Bayesian perspective. Our new method extends the Bayesian Lasso regression (Park and Casella, 2008) through replacing the least square loss and Lasso penalty by composite quantile loss function and adaptive...
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