Shape constrained additive models Routines for generalized additive modelling under shape constraints on the component functions of the linear predictor. Models can contain multiple shape constrained (univariate and/or bivariate) and unconstrained terms. The routines of mgcv(gam) package 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. Software Depends: R (>= 2.3.0) Imports: mgcv, graphics, stats Suggests: mgcv, splines, Matrix Natalya Pya <n.y.pya@bath.ac.uk> Natalya Pya GPL (>= 2) 2012-01-28 application/tgz http://CRAN.R-project.org/package=scam