Estimation of a discrete probability under constraint of κ-monotonicity
Résumé
We propose two least-squares estimators of a discrete probability under the constraint of k-monotonicity 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.
MSC 2010 subject classifications: Least squares, non-parametric estimation, k-monotone discrete probability, shape constraint, Support Reduction Algorithm.
Domaines
Sciences du Vivant [q-bio]
Origine : Fichiers éditeurs autorisés sur une archive ouverte
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