scam: Shape Constrained Additive Models

Routines for generalized additive modelling under shape constraints on the component functions of the linear predictor (Pya and Wood, 2015) <doi:10.1007/s11222-013-9448-7>. 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.

Version: 1.2-1
Depends: R (≥ 2.15.0), mgcv (≥ 1.8-2)
Imports: methods, stats, graphics, Matrix, splines
Suggests: nlme
Published: 2017-02-16
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_1.2-1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: scam_1.2-1.tgz, r-oldrel: scam_1.2-1.tgz
Old sources: scam archive

Reverse dependencies:

Reverse depends: zetadiv
Reverse imports: trackeR
Reverse suggests: schumaker


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