Estimation of a discrete probability under constraint of k-monotony
Statistics Theory
2017-08-30 v2 Statistics Theory
Abstract
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.
Keywords
Cite
@article{arxiv.1608.06541,
title = {Estimation of a discrete probability under constraint of k-monotony},
author = {Jade Giguelay},
journal= {arXiv preprint arXiv:1608.06541},
year = {2017}
}
Comments
53 pages, 35 figures