Selections

Abstract

In this talk, we will commence by discussing a general paradigm of selections. Subsequently, we will focus on the extension of the Akaike information criterion to mixture regression models, before moving on to simultaneously study regression coefficient and autoregressive order shrinkage via Lasso. In conclusion, we will address regularization parameter selection issues for the SCAD estimator of regression models.