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Métodos Monte Carlo basados en cadenas de Markov
dc.contributor.advisor | Pino Mejías, Rafael | es |
dc.creator | Jiménez Luna, José | es |
dc.date.accessioned | 2016-05-05T12:39:17Z | |
dc.date.available | 2016-05-05T12:39:17Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Jiménez Luna, J. (2015). Métodos Monte Carlo basados en cadenas de Markov. (Trabajo Fin de Grado Inédito). Universidad de Sevilla, Sevilla. | |
dc.identifier.uri | http://hdl.handle.net/11441/40818 | |
dc.description.abstract | Markov Chain Monte Carlo (or shortly MCMC) is a powerful method for sampling from high dimensional probability distributions. Here we present a swift introduction to the theory behind these methods as well as several applications of the Bayesian MCMC framework. These include, among others Bayesian Mixture Models, Bayesian Image Analysis or Text Mining. Implementations of solutions regarding these problems can be found in several programming languages. | es |
dc.format | application/pdf | es |
dc.language.iso | spa | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Métodos Monte Carlo basados en cadenas de Markov | es |
dc.type | info:eu-repo/semantics/bachelorThesis | es |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Estadística e Investigación Operativa | es |
dc.description.degree | Universidad de Sevilla. Grado en Estadística | es |
idus.format.extent | 80 p. | es |
dc.identifier.idus | https://idus.us.es/xmlui/handle/11441/40818 |
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Jiménez Luna José TFG.pdf | 795.9Kb | [PDF] | Ver/ | |