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.

Author | Jade Giguelay |

Date of publication | 2016-09-24 12:40:13 |

Maintainer | Jade Giguelay <jade.giguelay@ens-paris-saclay.fr> |

License | CC BY 4.0 |

Version | 0.9 |

**BaseNorm:** Normalized spline basis

**Delta:** Discrete laplacian

**estMonotone:** Estimators of discrete probabilities under k-monotony...

**kKnot:** k-Knot

**pEmp:** Empirical estimator of a discrete function

**pkmon-package:** Least-squares estimator under k-monotony constraint for...

**Spline:** Random generation and distribution function of k-monotone...

pkmon

pkmon/NAMESPACE

pkmon/R

pkmon/R/Estim_fkmon.R
pkmon/R/Estim_pkmon.R
pkmon/R/auxiliary_functions.R
pkmon/R/Simul_kmon.R
pkmon/MD5

pkmon/DESCRIPTION

pkmon/man

pkmon/man/Spline.Rd
pkmon/man/pEmp.Rd
pkmon/man/pkmon-package.Rd
pkmon/man/estMonotone.Rd
pkmon/man/kKnot.Rd
pkmon/man/Delta.Rd
pkmon/man/BaseNorm.Rd
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