Kernel Estimation in High-Energy Physics
摘要
Kernel Estimation provides an unbinned and non-parametric estimate of the probability density function from which a set of data is drawn. In the first section, after a brief discussion on parametric and non-parametric methods, the theory of Kernel Estimation is developed for univariate and multivariate settings. The second section discusses some of the applications of Kernel Estimation to high-energy physics. The third section provides an overview of the available univariate and multivariate packages. This paper concludes with a discussion of the inherent advantages of kernel estimation techniques and systematic errors associated with the estimation of parent distributions.
引用
@article{arxiv.hep-ex/0011057,
title = {Kernel Estimation in High-Energy Physics},
author = {Kyle S. Cranmer},
journal= {arXiv preprint arXiv:hep-ex/0011057},
year = {2009}
}
备注
17 pages, 2 ps figures. To be published in Computer Physics Communications. Uses elsart.sty and elsart.cls files