Eduardo F. Mendes

Consistent Order Selection under Non-Identifiability and Dependence

We provide sufficient conditions for the consistency of penalized least squares procedures that select the order (dimension) of a regression model from a sequence of nested classes, allowing for dependent, martingale-difference errors. The main contribution is to relax the classical identifiability requirement: paramet...