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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.
- Version0.2-2
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release05/25/2022
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Team
Yining Chen
Richard Samworth
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