pkmon: Least-Squares Estimator under k-Monotony Constraint for Discrete
Functions
We implement two least-squares estimators under k-monotony constraint using a method based on the Support Reduction Algorithm from Groeneboom et al (2008) <doi:10.1111/j.1467-9469.2007.00588.x>. The first one is a projection estimator on the set of k-monotone discrete functions. The second one is a projection on the set of k-monotone discrete probabilities. This package provides functions to generate samples from the spline basis from Lefevre and Loisel (2013) <doi:10.1239/jap/1378401239>, and from mixtures of splines.
| Version: |
1.0 |
| Published: |
2018-10-22 |
| Author: |
Jade Giguelay |
| Maintainer: |
Francois Deslandes <francois.deslandes at inra.fr> |
| License: |
CC BY 4.0 |
| NeedsCompilation: |
no |
| CRAN checks: |
pkmon results |
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