Coverage Properties of Confidence Intervals for Generalized Additive Model Components
Coverage Properties of Confidence Intervals for Generalized Additive Model Components
Abstract. We study the coverage properties of Bayesian confidence intervals for the smooth component functions of generalized additive models (GAMs) represented using any penalized regression spline approach. The intervals are the usual generalization of the intervals first proposed by Wahba and Silverman in 1983 and 1985, respectively, to the GAM …