A Statistical Prescription to Estimate Properly Normalized Distributions of Different Particle Species
Data Analysis, Statistics and Probability
2011-06-16 v1
Abstract
We describe a statistical method to avoid biased estimation of the content of different particle species. We consider the case when the particle identification information strongly depends on some kinematical variables, whose distributions are unknown and different for each particles species. We show that the proposed procedure provides properly normalized and completely data-driven estimation of the unknown distributions without any a priori assumption on their functional form. Moreover, we demonstrate that the method can be generalized to any kinematical distribution of the particles.
Keywords
Cite
@article{arxiv.0910.2266,
title = {A Statistical Prescription to Estimate Properly Normalized Distributions of Different Particle Species},
author = {Massimo Casarsa and Pierluigi Catastini and Giovanni Punzi and Luciano Ristori},
journal= {arXiv preprint arXiv:0910.2266},
year = {2011}
}