scar: Shape-Constrained Additive Regression: a Maximum Likelihood
Approach
Computes the maximum likelihood estimator of the generalised additive and index regression with shape constraints. Each additive component function is assumed to obey one of the nine possible shape restrictions: linear, increasing, decreasing, convex, convex increasing, convex decreasing, concave, concave increasing, or concave decreasing. For details, see Chen and Samworth (2016) <doi:10.1111/rssb.12137>.
Version: |
0.2-2 |
Depends: |
R (≥ 3.0.0) |
Suggests: |
gam, mgcv, scam |
Published: |
2022-05-25 |
Author: |
Yining Chen and Richard Samworth |
Maintainer: |
Yining Chen <y.chen101 at lse.ac.uk> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: |
yes |
Materials: |
NEWS |
CRAN checks: |
scar results |
Documentation:
Downloads:
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