Routines for generalized additive modelling under shape constraints on the component functions of the linear predictor (Pya and Wood, 2015) <doi:10.1007/s1122201394487>. 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 NewtonRaphson method is used to fit a model with multiple smoothing parameter selection by GCV or UBRE/AIC.
Package details 


Author  Natalya Pya <nat.pya@gmail.com> 
Maintainer  Natalya Pya <nat.pya@gmail.com> 
License  GPL (>= 2) 
Version  1.211 
Package repository  View on CRAN 
Installation 
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