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:	1.2-12
Depends:	R (≥ 2.15.0), mgcv (≥ 1.8-2)
Imports:	methods, stats, graphics, Matrix, splines
Suggests:	nlme
Published:	2021-08-10
Author:	Natalya Pya
Maintainer:	Natalya Pya <nat.pya at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
Materials:	ChangeLog
CRAN checks:	scam results

Documentation:

Reference manual:

scam.pdf

Downloads:

Package source:	scam_1.2-12.tar.gz
Windows binaries:	r-devel: scam_1.2-12.zip, r-release: scam_1.2-12.zip, r-oldrel: scam_1.2-12.zip
macOS binaries:	r-release (arm64): scam_1.2-12.tgz, r-oldrel (arm64): scam_1.2-12.tgz, r-release (x86_64): scam_1.2-12.tgz, r-oldrel (x86_64): scam_1.2-12.tgz
Old sources:	scam archive

Reverse dependencies:

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

Linking:

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