Logistic regression by the Bayesian approach and application

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dc.contributor.authorAdghar, Fatma
dc.date.accessioned2024-11-10T09:23:19Z
dc.date.available2024-11-10T09:23:19Z
dc.date.issued2021
dc.description67f.:ill.;30cm
dc.description.abstractThis dissertation is devoted to study the logistic regression using the Bayesian approach. To obtain the posterior distributions of the parameters regression, the Monte Carlo approximation methods by Markov chain (MCMC) are very powerful and indispensable and have there fore been developed in order to approximate the posterior distribution when one does not know how to do it analytically.
dc.identifier.citationProbabilités et statistiques
dc.identifier.urihttps://dspace.ummto.dz/handle/ummto/25309
dc.language.isoen
dc.publisherummto
dc.subjectRégression logistique
dc.subjectRégression logistique bayésienne
dc.subjectChaîne de Markov (MCMC)
dc.subjectDistribution a posteriori
dc.titleLogistic regression by the Bayesian approach and application
dc.typeThesis

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