Penalized regression, standard errors, and Bayesian lassos
Penalized regression, standard errors, and Bayesian lassos
Penalized regression methods for simultaneous variable selection and coefficient estimation, especially those based on the lasso of Tibshirani (1996), have received a great deal of attention in recent years, mostly through frequentist models. Properties such as consistency have been studied, and are achieved by different lasso variations. Here we look …