Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/122442
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dc.contributor.advisorMárquez, David (Márquez Carreras)-
dc.contributor.authorSouto Abad, Mónica-
dc.date.accessioned2018-05-18T07:59:47Z-
dc.date.available2018-05-18T07:59:47Z-
dc.date.issued2017-06-29-
dc.identifier.urihttps://hdl.handle.net/2445/122442-
dc.descriptionTreballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2017, Director: David Márquez Carrerasca
dc.description.abstract[en] Bayesian statistics is that statistic that is based on the Bayes theorem, therefore, in the information we have before observe the data. As a result, we have the a priori distribution and a posteriori distribution, which we make inference. In this work we will study the process of estimation from Bayesian inference and simulation methods of a posteriori distribution. In addition, we will see this knowledge applied to practical examples.ca
dc.format.extent74 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isocatca
dc.rightscc-by-nc-nd (c) Mónica Souto Abad, 2017-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es-
dc.sourceTreballs Finals de Grau (TFG) - Matemàtiques-
dc.subject.classificationEstadística bayesiana-
dc.subject.classificationTreballs de fi de grau-
dc.subject.classificationInferènciaca
dc.subject.classificationMètode de Montecarloca
dc.subject.classificationDistribució (Teoria de la probabilitat)ca
dc.subject.otherBayesian statistical decision-
dc.subject.otherBachelor's theses-
dc.subject.otherInferenceen
dc.subject.otherMonte Carlo methoden
dc.subject.otherDistribution (Probability theory)en
dc.titleIntroducció a l'estadística bayesianaca
dc.typeinfo:eu-repo/semantics/bachelorThesisca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Treballs Finals de Grau (TFG) - Matemàtiques

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