An improved AIC-based criterion is derived for model selection in general smoothing-basedmodeling, including semiparametric models and additive models. Examples areprovided of applications to goodness-of-fit, smoothing parameter and variable selectionin an additive model and semiparametric...

In partially linear model selection, we develop a profiled forward regression (PFR) algorithm for ultrahigh dimensional variable screening. The PFR algorithm effectively combines the ideas of nonparametric profiling and forward regression. This allows us to obtain a uniform bound for the...