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scam  

Shape Constrained Additive Models
View on CRAN: Click here


Download and install scam package within the R console
Install from CRAN:
install.packages("scam")

Install from Github:
library("remotes")
install_github("cran/scam")

Install by package version:
library("remotes")
install_version("scam", "1.2-22")



Attach the package and use:
library("scam")
Maintained by
Natalya Pya
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-01-20
Latest Update: 2025-05-26
Description:
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) for an overview. A broad selection of shape-constrained smoothers, linear functionals of smooths with shape constraints, and Gaussian models with AR1 residuals.
How to cite:
Natalya Pya (2012). scam: Shape Constrained Additive Models. R package version 1.2-22, https://cran.r-project.org/web/packages/scam. Accessed 07 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:01), 1.0 (2012-01-20 16:18), 1.1-1 (2012-01-28 18:08), 1.1-2 (2012-08-05 15:44), 1.1-3 (2012-09-23 20:08), 1.1-4 (2012-10-08 21:14), 1.1-5 (2013-09-14 09:06), 1.1-6 (2013-10-02 12:05), 1.1-7 (2014-05-27 17:52), 1.1-8 (2014-09-24 17:57), 1.1-9 (2015-06-19 08:51), 1.1 (2012-01-22 08:58), 1.2-0 (2016-06-02 09:43), 1.2-1 (2017-02-16 17:27), 1.2-2 (2017-09-24 15:02), 1.2-3 (2018-09-25 22:50), 1.2-4 (2019-06-14 13:40), 1.2-5 (2019-08-19 12:30), 1.2-6 (2020-06-10 12:00), 1.2-7 (2020-09-24 21:20), 1.2-8 (2020-10-23 10:20), 1.2-9 (2020-12-09 11:10), 1.2-10 (2021-02-01 14:50), 1.2-11 (2021-04-01 12:20), 1.2-12 (2021-08-10 16:40), 1.2-13 (2022-09-09 17:20), 1.2-14 (2023-04-14 12:00), 1.2-15 (2024-01-25 21:50), 1.2-16 (2024-02-23 10:40), 1.2-17 (2024-06-19 14:40), 1.2-18 (2025-01-17 16:00), 1.2-19 (2025-05-26 10:40), 1.2-20 (2025-10-14 10:00), 1.2-21 (2026-01-22 13:50)
Other packages that cited scam R package
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Other R packages that scam depends, imports, suggests or enhances
Complete documentation for scam
Functions, R codes and Examples using the scam R package
Some associated functions: Predict.matrix.mpi.smooth . anova.scam . bfgs_gcv.ubre . check.analytical . derivative.scam . formula.scam . gcv.ubre_grad . linear.functional.terms . logLik.scam . marginal.matrices.tescv.ps . marginal.matrices.tesmi1.ps . marginal.matrices.tesmi2.ps . plot.scam . predict.scam . print.scam . qq.scam . residuals.scam . scam-package . scam.check . scam.control . scam.fit . scam . shape.constrained.smooth.terms . smooth.construct.cx.smooth.spec . smooth.construct.mdcv.smooth.spec . smooth.construct.mdcx.smooth.spec . smooth.construct.micv.smooth.spec . smooth.construct.micx.smooth.spec . smooth.construct.mifo.smooth.spec . smooth.construct.miso.smooth.spec . smooth.construct.mpd.smooth.spec . smooth.construct.mpi.smooth.spec . smooth.construct.po.smooth.spec . smooth.construct.tecvcv.smooth.spec . smooth.construct.tecxcv.smooth.spec . smooth.construct.tecxcx.smooth.spec . smooth.construct.tedecv.smooth.spec . smooth.construct.tedecx.smooth.spec . smooth.construct.tedmd.smooth.spec . smooth.construct.tedmi.smooth.spec . smooth.construct.temicv.smooth.spec . smooth.construct.temicx.smooth.spec . smooth.construct.tescv.smooth.spec . smooth.construct.tescx.smooth.spec . smooth.construct.tesmd1.smooth.spec . smooth.construct.tesmd2.smooth.spec . smooth.construct.tesmi1.smooth.spec . smooth.construct.tesmi2.smooth.spec . smooth.construct.tismd.smooth.spec . smooth.construct.tismi.smooth.spec . summary.scam . vis.scam . 
Some associated R codes: bivar.smooth.const-ti.R . bivar.smooth.const.R . check.analytical.R . derivative.smooth.R . estimate.scam.R . predict.scam.R . print.scam.R . residuals.scam.R . scam.check.R . summary.scam.R .  Full scam package functions and examples
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