PKMON


Least-squares estimator under k-monotony constraint for discrete functions

We propose two least-squares estimators of a discrete probability under the constraint of k-monotony and study their statistical properties. We give a characterization of these estimators based on the decomposition on a spline basis of k-monotone sequences. We develop an algorithm derived from the Support Reduction Algorithm and we finally present a simulation study to illustrate their properties.


Informations générales
Suivi
Maintenu
Informations spécifiques
Langage(s) de développement
R
Langage(s) d'interface
R
N° de version courante
V1
Date de la version courante
OS supporté


Porteur(s)
Unité
MaIAGE
Equipe
StatInfOmics
Auteur(s)
Giguelay Jade
Contact
jade.giguelay@inra.fr
Publication de référence


 

 

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