The GAMMOD Procedure

The GAMMOD procedure fits generalized additive models that are based on low-rank regression splines (Wood 2006) in SAS Viya.

Generalized additive models are extensions of generalized linear models. They relax the generalized linear models’ assumption of linearity by allowing spline terms that characterize nonlinear dependency structures. Each spline term is constructed by the thin-plate regression spline technique (Wood 2003). A roughness penalty is applied to each spline term by a smoothing parameter that controls the balance between goodness of fit and the roughness of the spline curve. PROC GAMMOD fits models for standard distributions in the exponential family, such as the normal, Poisson, gamma, and Tweedie distributions.