scam (1.2-3)

Shape Constrained Additive Models.

Routines for generalized additive modelling under shape constraints on the component functions of the linear predictor (Pya and Wood, 2015) . Models can contain multiple shape constrained (univariate and/or bivariate) and unconstrained terms. The routines of gam() in package 'mgcv' are used for setting up the model matrix, printing and plotting the results. Penalized likelihood maximization based on Newton-Raphson method is used to fit a model with multiple smoothing parameter selection by GCV or UBRE/AIC.

Maintainer: Natalya Pya
Author(s): Natalya Pya <>

License: GPL (>= 2)

Uses: Matrix, mgcv, nlme
Reverse depends: zetadiv
Reverse suggests: gratia, pammtools, schumaker, trackeR

Released over 1 year ago.