ALHAMZAWI, R.; YU, K.; BENOIT, D. F. - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2011
Recently, variable selection by penalized likelihood has attracted much research interest. In this paper, we propose adaptive Lasso quantile regression (BALQR) from a Bayesian perspective. The method extends the Bayesian Lasso quantile regression by allowing different penalization parameters for...