Statistical Challenges of Global SUSY Fits

We present recent results aiming at assessing the coverage properties of Bayesian and frequentist inference methods, as applied to the reconstruction of supersymmetric parameters from simulated LHC data. We discuss the statistical challenges of the reconstruction procedure, and highlight the algorit...

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Detalles Bibliográficos
Autores principales: Trotta, Roberto, Cranmer, Kyle
Lenguaje:eng
Publicado: 2011
Materias:
Particle Physics - Phenomenology
Acceso en línea:https://dx.doi.org/10.5170/CERN-2011-006.170
http://cds.cern.ch/record/1354055
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author Trotta, Roberto
Cranmer, Kyle
author_facet Trotta, Roberto
Cranmer, Kyle
author_sort Trotta, Roberto
collection CERN
description We present recent results aiming at assessing the coverage properties of Bayesian and frequentist inference methods, as applied to the reconstruction of supersymmetric parameters from simulated LHC data. We discuss the statistical challenges of the reconstruction procedure, and highlight the algorithmic difficulties of obtaining accurate profile likelihood estimates.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2011
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spelling cern-13540552019-09-30T06:29:59Zdoi:10.5170/CERN-2011-006.170http://cds.cern.ch/record/1354055engTrotta, RobertoCranmer, KyleStatistical Challenges of Global SUSY FitsParticle Physics - PhenomenologyWe present recent results aiming at assessing the coverage properties of Bayesian and frequentist inference methods, as applied to the reconstruction of supersymmetric parameters from simulated LHC data. We discuss the statistical challenges of the reconstruction procedure, and highlight the algorithmic difficulties of obtaining accurate profile likelihood estimates.We present recent results aiming at assessing the coverage properties of Bayesian and frequentist inference methods, as applied to the reconstruction of supersymmetric parameters from simulated LHC data. We discuss the statistical challenges of the reconstruction procedure, and highlight the algorithmic difficulties of obtaining accurate profile likelihood estimates.arXiv:1105.5244oai:cds.cern.ch:13540552011-05-27
spellingShingle Particle Physics - Phenomenology
Trotta, Roberto
Cranmer, Kyle
Statistical Challenges of Global SUSY Fits
title Statistical Challenges of Global SUSY Fits
title_full Statistical Challenges of Global SUSY Fits
title_fullStr Statistical Challenges of Global SUSY Fits
title_full_unstemmed Statistical Challenges of Global SUSY Fits
title_short Statistical Challenges of Global SUSY Fits
title_sort statistical challenges of global susy fits
topic Particle Physics - Phenomenology
url https://dx.doi.org/10.5170/CERN-2011-006.170
http://cds.cern.ch/record/1354055
work_keys_str_mv AT trottaroberto statisticalchallengesofglobalsusyfits
AT cranmerkyle statisticalchallengesofglobalsusyfits

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