Bayesian Analysis Toolkit in Searches

The Bayesian Analysis Toolkit, a software package for data analysis based onBayes' theorem, is introduced. This toolkit takes advantage of Markov ChainMonte Carlo to find the full posterior probability distributions. The tool caneasily be used for parameter estimation, limit setting and error p...

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Detalles Bibliográficos
Autores principales: Beaujean, Frederik, Caldwell, Allen, Kollár, Daniel, Kröninger, Kevin, Pashapour, Shabnaz
Lenguaje:eng
Publicado: CERN 2011
Materias:
Particle Physics - Experiment
Detectors and Experimental Techniques
Acceso en línea:https://dx.doi.org/10.5170/CERN-2011-006.209
http://cds.cern.ch/record/2203253
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author Beaujean, Frederik
Caldwell, Allen
Kollár, Daniel
Kröninger, Kevin
Pashapour, Shabnaz
author_facet Beaujean, Frederik
Caldwell, Allen
Kollár, Daniel
Kröninger, Kevin
Pashapour, Shabnaz
author_sort Beaujean, Frederik
collection CERN
description The Bayesian Analysis Toolkit, a software package for data analysis based onBayes' theorem, is introduced. This toolkit takes advantage of Markov ChainMonte Carlo to find the full posterior probability distributions. The tool caneasily be used for parameter estimation, limit setting and error propagation.Model comparison and goodness-of-fit estimation are realized in the packagethrough well-established methods. In addition to a brief description of theBayesian Analysis Toolkit, the use of this tool in searches is described in theexample of Banff Challenge 2a problem 1.
id oai-inspirehep.net-1478288
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2011
publisher CERN
record_format invenio
spelling oai-inspirehep.net-14782882019-09-30T06:29:59Zdoi:10.5170/CERN-2011-006.209http://cds.cern.ch/record/2203253engBeaujean, FrederikCaldwell, AllenKollár, DanielKröninger, KevinPashapour, ShabnazBayesian Analysis Toolkit in SearchesParticle Physics - ExperimentDetectors and Experimental TechniquesThe Bayesian Analysis Toolkit, a software package for data analysis based onBayes' theorem, is introduced. This toolkit takes advantage of Markov ChainMonte Carlo to find the full posterior probability distributions. The tool caneasily be used for parameter estimation, limit setting and error propagation.Model comparison and goodness-of-fit estimation are realized in the packagethrough well-established methods. In addition to a brief description of theBayesian Analysis Toolkit, the use of this tool in searches is described in theexample of Banff Challenge 2a problem 1.CERNoai:inspirehep.net:14782882011
spellingShingle Particle Physics - Experiment
Detectors and Experimental Techniques
Beaujean, Frederik
Caldwell, Allen
Kollár, Daniel
Kröninger, Kevin
Pashapour, Shabnaz
Bayesian Analysis Toolkit in Searches
title Bayesian Analysis Toolkit in Searches
title_full Bayesian Analysis Toolkit in Searches
title_fullStr Bayesian Analysis Toolkit in Searches
title_full_unstemmed Bayesian Analysis Toolkit in Searches
title_short Bayesian Analysis Toolkit in Searches
title_sort bayesian analysis toolkit in searches
topic Particle Physics - Experiment
Detectors and Experimental Techniques
url https://dx.doi.org/10.5170/CERN-2011-006.209
http://cds.cern.ch/record/2203253
work_keys_str_mv AT beaujeanfrederik bayesiananalysistoolkitinsearches
AT caldwellallen bayesiananalysistoolkitinsearches
AT kollardaniel bayesiananalysistoolkitinsearches
AT kroningerkevin bayesiananalysistoolkitinsearches
AT pashapourshabnaz bayesiananalysistoolkitinsearches

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