R package scam. Routines for generalized additive modelling under shape constraints on the component functions of the linear predictor. 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.
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References in zbMATH (referenced in 1 article )
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- Hofner, Benjamin; Kneib, Thomas; Hothorn, Torsten: A unified framework of constrained regression (2016)