scam: 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.

Version: 1.1-8
Depends: R (≥ 2.15.0), mgcv (≥ 1.7-27)
Imports: methods, stats, graphics, Matrix, splines
Suggests: nlme
Published: 2014-09-24
Author: Natalya Pya
Maintainer: Natalya Pya <nat.pya at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: scam results


Reference manual: scam.pdf
Package source: scam_1.1-8.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: scam_1.1-8.tgz, r-oldrel: scam_1.1-8.tgz
OS X Mavericks binaries: r-release: scam_1.1-8.tgz
Old sources: scam archive