We describe a statistical method to estimate the composition of a sample of particle tracks in terms of the species of these particles. We consider the case when the particle identification information strongly depends on some kinematical variables, whose distributions are poorly known and different for each particle species. We show that the proposed procedure provides a properly normalized estimate of the unknown distributions with minimal assumption on their functional form. Moreover, we show that the method can be generalized to any kinematical distribution of the particles. Published by Elsevier B.V.

A statistical prescription to estimate properly normalized distributions of different particle species

PUNZI, GIOVANNI;
2011

Abstract

We describe a statistical method to estimate the composition of a sample of particle tracks in terms of the species of these particles. We consider the case when the particle identification information strongly depends on some kinematical variables, whose distributions are poorly known and different for each particle species. We show that the proposed procedure provides a properly normalized estimate of the unknown distributions with minimal assumption on their functional form. Moreover, we show that the method can be generalized to any kinematical distribution of the particles. Published by Elsevier B.V.
Casarsa, M.; Catastini, P.; Punzi, Giovanni; Ristori, L.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/146621
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