Statistical homogeneity tests applied to large data sets from high energy physics experiments

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F17%3A00315815" target="_blank" >RIV/68407700:21340/17:00315815 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1088/1742-6596/936/1/012046" target="_blank" >http://dx.doi.org/10.1088/1742-6596/936/1/012046</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1088/1742-6596/936/1/012046" target="_blank" >10.1088/1742-6596/936/1/012046</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Statistical homogeneity tests applied to large data sets from high energy physics experiments

Popis výsledku v původním jazyce

Homogeneity tests are used in high energy physics for the verification of simulated Monte Carlo samples, it means if they have the same distribution as a measured data from particle detector. Kolmogorov-Smirnov, chi^2, and Anderson-Darling tests are the most used techniques to assess the samples' homogeneity. Since MC generators produce plenty of entries from different models, each entry has to be re-weighted to obtain the same sample size as the measured data has. One way of the homogeneity testing is through the binning. If we do not want to lose any information, we can apply generalized tests based on weighted empirical distribution functions. In this paper, we propose such generalized weighted homogeneity tests and introduce some of their asymptotic properties. We present the results based on numerical analysis which focuses on estimations of the type-I error and power of the test. Finally, we present application of our homogeneity tests to data from the experiment DO in Fermilab.

Název v anglickém jazyce

Statistical homogeneity tests applied to large data sets from high energy physics experiments

Popis výsledku anglicky

Homogeneity tests are used in high energy physics for the verification of simulated Monte Carlo samples, it means if they have the same distribution as a measured data from particle detector. Kolmogorov-Smirnov, chi^2, and Anderson-Darling tests are the most used techniques to assess the samples' homogeneity. Since MC generators produce plenty of entries from different models, each entry has to be re-weighted to obtain the same sample size as the measured data has. One way of the homogeneity testing is through the binning. If we do not want to lose any information, we can apply generalized tests based on weighted empirical distribution functions. In this paper, we propose such generalized weighted homogeneity tests and introduce some of their asymptotic properties. We present the results based on numerical analysis which focuses on estimations of the type-I error and power of the test. Finally, we present application of our homogeneity tests to data from the experiment DO in Fermilab.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Physics: Conference Series

ISSN

1742-6588

e-ISSN

—

Svazek periodika

936

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

6

Strana od-do

—

Kód UT WoS článku

000428194400046

EID výsledku v databázi Scopus

2-s2.0-85041199947