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: 1.2-19 Depends: R (≥ 3.6.0) Imports: mgcv (≥ 1.8-2), methods, stats, graphics, Matrix, splines Suggests: nlme Published: 2025-05-26 DOI: 10.32614/CRAN.package.scam Author: Natalya Pya [aut, cre] 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: Downloads: Reverse dependencies: Reverse depends: zetadiv Reverse imports: cgaim, cpam, FlexGAM, funcharts, GJRM, insurancerating, IRon, MIDASim, mobr, pammtools, PoweREST, reReg, smoppix, spicyR, sspse, trackeR Reverse suggests: CAST, gratia, marginaleffects, riskRegression, scar, schumaker Linking:Please use the canonical form https://CRAN.R-project.org/package=scam to link to this page.
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