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: 1.1-6
Depends: R (≥ 2.15.0), mgcv (≥ 1.7-27), stats, graphics
Imports: methods, Matrix
Suggests: nlme, splines
Published: 2013-10-02
Author: Natalya Pya
Maintainer: Natalya Pya <n.y.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_1.1-6.tar.gz
OS X binary: scam_1.1-6.tgz
Windows binary:
Old sources: scam archive