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The RooStats Project

RooStats is a project to create advanced statistical tools required for the analysis of LHC data, with emphasis on discoveries, confidence intervals, and combined measurements. The idea is to provide the major statistical techniques as a set of C++ classes with coherent interfaces, which can be used...

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Detalles Bibliográficos
Autores principales: Moneta, Lorenzo, Belasco, Kevin, Cranmer, Kyle, Lazzaro, Alfio, Piparo, Danilo, Schott, Gregory, Verkerke, Wouter, Wolf, Matthias
Lenguaje:eng
Publicado: 2010
Materias:
Acceso en línea:https://dx.doi.org/10.22323/1.093.0057
http://cds.cern.ch/record/1289965
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author Moneta, Lorenzo
Belasco, Kevin
Cranmer, Kyle
Lazzaro, Alfio
Piparo, Danilo
Schott, Gregory
Verkerke, Wouter
Wolf, Matthias
Belasco, Kevin
Cranmer, Kyle
Piparo, Danilo
Schott, Gregory
Verkerke, Wouter
Wolf, Matthias
author_facet Moneta, Lorenzo
Belasco, Kevin
Cranmer, Kyle
Lazzaro, Alfio
Piparo, Danilo
Schott, Gregory
Verkerke, Wouter
Wolf, Matthias
Belasco, Kevin
Cranmer, Kyle
Piparo, Danilo
Schott, Gregory
Verkerke, Wouter
Wolf, Matthias
author_sort Moneta, Lorenzo
collection CERN
description RooStats is a project to create advanced statistical tools required for the analysis of LHC data, with emphasis on discoveries, confidence intervals, and combined measurements. The idea is to provide the major statistical techniques as a set of C++ classes with coherent interfaces, which can be used on arbitrary model and datasets in a common way. The classes are built on top of RooFit, which provides a very convenient functionality for modeling the probability density functions or the likelihood functions, required as inputs for any statistical technique. Furthermore, RooFit provides the functionality for easily creating models, for analysis combination and for digital publication of the likelihood function and the data. We will present in detail the design and the implementation of the different statistical methods of RooStats. These include various classes for interval estimation and for hypothesis test depending on different statistical techniques such as those based on the likelihood function, or on frequentists or bayesian statistics. These methods can be applied in complex problems, including cases with multiple parameters of interest and various nuisance parameters.
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language eng
publishDate 2010
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spelling cern-12899652019-09-30T06:29:59Zdoi:10.22323/1.093.0057http://cds.cern.ch/record/1289965engMoneta, LorenzoBelasco, KevinCranmer, KyleLazzaro, AlfioPiparo, DaniloSchott, GregoryVerkerke, WouterWolf, MatthiasBelasco, KevinCranmer, KylePiparo, DaniloSchott, GregoryVerkerke, WouterWolf, MatthiasThe RooStats ProjectOther Fields of PhysicsRooStats is a project to create advanced statistical tools required for the analysis of LHC data, with emphasis on discoveries, confidence intervals, and combined measurements. The idea is to provide the major statistical techniques as a set of C++ classes with coherent interfaces, which can be used on arbitrary model and datasets in a common way. The classes are built on top of RooFit, which provides a very convenient functionality for modeling the probability density functions or the likelihood functions, required as inputs for any statistical technique. Furthermore, RooFit provides the functionality for easily creating models, for analysis combination and for digital publication of the likelihood function and the data. We will present in detail the design and the implementation of the different statistical methods of RooStats. These include various classes for interval estimation and for hypothesis test depending on different statistical techniques such as those based on the likelihood function, or on frequentists or bayesian statistics. These methods can be applied in complex problems, including cases with multiple parameters of interest and various nuisance parameters.arXiv:1009.1003oai:cds.cern.ch:12899652010-09-07
spellingShingle Other Fields of Physics
Moneta, Lorenzo
Belasco, Kevin
Cranmer, Kyle
Lazzaro, Alfio
Piparo, Danilo
Schott, Gregory
Verkerke, Wouter
Wolf, Matthias
Belasco, Kevin
Cranmer, Kyle
Piparo, Danilo
Schott, Gregory
Verkerke, Wouter
Wolf, Matthias
The RooStats Project
title The RooStats Project
title_full The RooStats Project
title_fullStr The RooStats Project
title_full_unstemmed The RooStats Project
title_short The RooStats Project
title_sort roostats project
topic Other Fields of Physics
url https://dx.doi.org/10.22323/1.093.0057
http://cds.cern.ch/record/1289965
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