Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/189600
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dc.contributor.advisorFlorit i Selma, Carmen-
dc.contributor.authorCastellà Camps, Xènia-
dc.date.accessioned2022-10-04T08:10:44Z-
dc.date.available2022-10-04T08:10:44Z-
dc.date.issued2022-06-13-
dc.identifier.urihttp://hdl.handle.net/2445/189600-
dc.descriptionTreballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Carmen Florit i Selmaca
dc.description.abstract[en] Markov chains are stochastic processes characterized by the fact that the outcome in a given state depends only on the previous state. In this work we will study this notion assuming time is discrete, as well as the properties that derive from it and how they can be classified in an environment where time does not intervene in its evolution. Finally, we will analyze a specific case, along with simulations on R and C.ca
dc.format.extent44 p.-
dc.format.mimetypeapplication/pdf-
dc.language.isocatca
dc.rightscc-by-nc-nd (c) Xènia Castellà Camps, 2022-
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.titleCadenes de Markov a temps discret i la seva simulacióca
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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