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
||R (≥ 2.15.0), mgcv (≥ 1.8-2)
||methods, stats, graphics, Matrix, splines
||Natalya Pya <nat.pya at gmail.com>
||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
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