Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/174536
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorMárquez, David (Márquez Carreras)-
dc.contributor.authorAmazian, Sana-
dc.date.accessioned2021-03-02T11:04:31Z-
dc.date.available2021-03-02T11:04:31Z-
dc.date.issued2020-01-19-
dc.identifier.urihttp://hdl.handle.net/2445/174536-
dc.descriptionTreballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2020, Director: David Márquez Carrerasca
dc.description.abstract[en] The aim of this project is to be able to identify, understand and describe the main properties of a time-homogeneous Markov chain. A discrete stochastic process which the future only depends on the present and not the past is called Markov chain. If, in addition, it is satisfied that the probabilities that determine the chain are time independent, then we talk about time-homogeneous Markov chains. We will focus on these ones, introducing the most relevant concepts and related results. The theoretical concepts will be completed with some examples to ease the comprehension.ca
dc.format.extent54 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isocatca
dc.rightscc-by-nc-nd (c) Sana Amazian, 2020-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Matemàtiques-
dc.subject.classificationProcessos estocàsticsca
dc.subject.classificationTreballs de fi de grau-
dc.subject.classificationProcessos de Markovca
dc.subject.otherStochastic processesen
dc.subject.otherBachelor's theses-
dc.subject.otherMarkov processesen
dc.titlePassejada a l’atzar: estudi de les cadenes de Markov homogèniesca
dc.typeinfo:eu-repo/semantics/bachelorThesisca
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Treballs Finals de Grau (TFG) - Matemàtiques

Files in This Item:
File Description SizeFormat 
174536.pdfMemòria1.11 MBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons