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SUMMARY:Fit of weighted histograms in the ROOT framework.
DTSTART;VALUE=DATE-TIME:20090324T070000Z
DTEND;VALUE=DATE-TIME:20090324T072000Z
DTSTAMP;VALUE=DATE-TIME:20191023T045605Z
UID:indico-contribution-839765@indico.cern.ch
DESCRIPTION:Speakers: Lorenzo Moneta (CERN)\, Nikolai GAGUNASHVILI (Univer
sity of Akureyri\, Iceland)\nWeighted histograms are often used for the es
timation of a probability density functions in High Energy Physics. The
bin contents of a weighted histogram can be considered as a sum of random
variables with random number of terms. A generalization of the Pearsonâ€™
s chi-square statistics for weighted histograms and for weighted histogram
s with unknown normalization has been recently proposed by the first autho
r. The usage of these statistics provide the possibility of fitting the p
arameters of a probability density functions. A new implementation of this
statistical method has been recently realized within the ROOT statistical
framework using the MINUIT algorithm for minimization. We will describe t
his statistical method and its new implementation including some examples
of applications. A numerical investigation is presented for fitting variou
s histograms with different numbers of events. Restrictions related with t
he application of the procedure for histograms with small statistics of ev
ents are also discussed.\n\nhttps://indico.cern.ch/event/35523/contributio
ns/839765/
LOCATION:Prague
URL:https://indico.cern.ch/event/35523/contributions/839765/
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