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arXiv · hep-ex/0011057

Kernel Estimation in High-Energy Physics

Kyle S. Cranmer
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Abstract

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.

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Kyle S. Cranmer. 2000-11-17. Kernel Estimation in High-Energy Physics. https://doi.org/10.1016/s0010-4655(00)00243-5

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