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
mgcv(gam) package 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: |
1.1-8 |
| Depends: |
R (≥ 2.15.0), mgcv (≥ 1.7-27) |
| Imports: |
methods, stats, graphics, Matrix, splines |
| Suggests: |
nlme |
| Published: |
2014-09-24 |
| Author: |
Natalya Pya |
| Maintainer: |
Natalya Pya <nat.pya at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| Materials: |
ChangeLog |
| CRAN checks: |
scam results |