کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
503611 | 863787 | 2006 | 8 صفحه PDF | دانلود رایگان |
With increasing requirements from particle physics for effective multi-variate discrimination techniques, a number of alternative probability density estimate (PDE) methods have appeared in recent years. These relatively advanced methods attempt to form effective PDEs in the presence of low statistics where a simple histogramming method does not perform well.In this paper a multi-variate histogrammed PDE method is presented. The method incorporates a simple Laplace smoothing procedure and χ2χ2-triggered optimisation that results in the automatic selection of near-optimal binning and greatly improved PDE performance at low statistics.The performance of the smoothed histogrammed PDE is compared to a theoretically ideal PDE, and to results from a kernel PDE and a neural network.
Journal: Computer Physics Communications - Volume 175, Issues 11–12, 1–15 December 2006, Pages 700–707