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HistFitter software framework for statistical data analysis

We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical...

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Detalles Bibliográficos
Autores principales: Baak, M., Besjes, G.J., Côte, D., Koutsman, A., Lorenz, J., Short, D.
Lenguaje:eng
Publicado: 2014
Materias:
Acceso en línea:https://dx.doi.org/10.1140/epjc/s10052-015-3327-7
http://cds.cern.ch/record/1953093
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author Baak, M.
Besjes, G.J.
Côte, D.
Koutsman, A.
Lorenz, J.
Short, D.
author_facet Baak, M.
Besjes, G.J.
Côte, D.
Koutsman, A.
Lorenz, J.
Short, D.
author_sort Baak, M.
collection CERN
description We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fitted to data and interpreted with statistical tests. A key innovation of HistFitter is its design, which is rooted in core analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its very fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple data models at once, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication-quality style through a simple command-line interface.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2014
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spelling cern-19530932022-08-10T12:58:49Zdoi:10.1140/epjc/s10052-015-3327-7http://cds.cern.ch/record/1953093engBaak, M.Besjes, G.J.Côte, D.Koutsman, A.Lorenz, J.Short, D.HistFitter software framework for statistical data analysisParticle Physics - ExperimentWe present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fitted to data and interpreted with statistical tests. A key innovation of HistFitter is its design, which is rooted in core analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its very fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple data models at once, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication-quality style through a simple command-line interface.We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton–proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fit to data and interpreted with statistical tests. Internally HistFitter uses the statistics packages RooStats and HistFactory. A key innovation of HistFitter is its design, which is rooted in analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple models at once that describe the data, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication quality style through a simple command-line interface.We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fitted to data and interpreted with statistical tests. A key innovation of HistFitter is its design, which is rooted in core analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its very fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple data models at once, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication-quality style through a simple command-line interface.arXiv:1410.1280oai:cds.cern.ch:19530932014-10-06
spellingShingle Particle Physics - Experiment
Baak, M.
Besjes, G.J.
Côte, D.
Koutsman, A.
Lorenz, J.
Short, D.
HistFitter software framework for statistical data analysis
title HistFitter software framework for statistical data analysis
title_full HistFitter software framework for statistical data analysis
title_fullStr HistFitter software framework for statistical data analysis
title_full_unstemmed HistFitter software framework for statistical data analysis
title_short HistFitter software framework for statistical data analysis
title_sort histfitter software framework for statistical data analysis
topic Particle Physics - Experiment
url https://dx.doi.org/10.1140/epjc/s10052-015-3327-7
http://cds.cern.ch/record/1953093
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AT lorenzj histfittersoftwareframeworkforstatisticaldataanalysis
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