scam: Shape Constrained Additive Models

Generalized additive models under shape constraints on the component functions of the linear predictor. Models can include multiple shape-constrained (univariate and bivariate) and unconstrained terms. Routines of the package 'mgcv' are used to set up the model matrix, print, and plot the results. Multiple smoothing parameter estimation by the Generalized Cross Validation or similar. See Pya and Wood (2015) <doi:10.1007/s11222-013-9448-7> for an overview. A broad selection of shape-constrained smoothers, linear functionals of smooths with shape constraints, and Gaussian models with AR1 residuals.

Version: 1.2-17
Depends: R (≥ 2.15.0), mgcv (≥ 1.8-2)
Imports: methods, stats, graphics, Matrix, splines
Suggests: nlme
Published: 2024-06-19
DOI: 10.32614/CRAN.package.scam
Author: Natalya Pya
Maintainer: Natalya Pya <nat.pya at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: ChangeLog
CRAN checks: scam results


Reference manual: scam.pdf


Package source: scam_1.2-17.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): scam_1.2-17.tgz, r-oldrel (arm64): scam_1.2-17.tgz, r-release (x86_64): scam_1.2-17.tgz, r-oldrel (x86_64): scam_1.2-17.tgz
Old sources: scam archive

Reverse dependencies:

Reverse depends: zetadiv
Reverse imports: cgaim, FlexGAM, GJRM, IRon, reReg, spicyR, sspse, trackeR
Reverse suggests: CAST, gratia, marginaleffects, riskRegression, scar, schumaker


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