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
UBRE/AIC.
| Version: |
1.2-13 |
| Depends: |
R (≥ 2.15.0), mgcv (≥ 1.8-2) |
| Imports: |
methods, stats, graphics, Matrix, splines |
| Suggests: |
nlme |
| Published: |
2022-09-09 |
| Author: |
Natalya Pya |
| 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, FlexGAM, GJRM, IRon, reReg, spicyR, sspse, trackeR |
| Reverse suggests: |
CAST, gratia, marginaleffects, riskRegression, scar, schumaker |
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