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SUMMARY:Custom Orthogonal Weight functions (COWs) - an improved event weig
 hting procedure for removing background from signal. - Matt Kenzie (Univer
 sity of Warwick)
DTSTART:20230124T110000Z
DTEND:20230124T120000Z
UID:TALK192911@talks.cam.ac.uk
CONTACT:William Fawcett
DESCRIPTION:A common problem in data analysis is the separation of signal 
 and background. This talk is based on https://arxiv.org/abs/2112.04574 whe
 re we revisit and generalise the so-called sWeights method\, which allows 
 one to calculate an empirical estimate of the signal density of a control 
 variable using a fit of a mixed signal and background model to a discrimin
 ating variable. We show that sWeights are a special case of a larger class
  of\nCustom Orthogonal Weight functions (COWs)\, which can be applied to a
  more general class of problems in which the discriminating and control va
 riables are not necessarily independent and still achieve close to optimal
  performance. We also investigate the properties of parameters estimated f
 rom fits of statistical models to sWeighted data and provide closed formul
 as for the asymptotic covariance matrix of the fitted parameters. To illus
 trate our findings\, we discuss several practical applications of these te
 chniques.
LOCATION:Ryle Seminar Room
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