Optimal kernel selection for density estimation
Statistics Theory
2015-11-09 v1 Statistics Theory
Abstract
We provide new general kernel selection rules thanks to penalized least-squares criteria. We derive optimal oracle inequalities using adequate concentration tools. We also investigate the problem of minimal penalty as described in [BM07].
Cite
@article{arxiv.1511.02112,
title = {Optimal kernel selection for density estimation},
author = {M Lerasle and N Magalhães and P Reynaud-Bouret},
journal= {arXiv preprint arXiv:1511.02112},
year = {2015}
}