r-scam

condav1.2_18

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.

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[email protected]_18 is safe to use (health: 59/100)

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First published · 2021-11-02 09:46:13.507000+00:00

Last updated · 2026-03-20 02:35:51.909000+00:00