Integration Of Prior Information In Kaplan Meier Estimator Using Bayesian Approach

dc.contributor.authorPempie, Pascal
dc.contributor.authorHamimes, Ahmed
dc.contributor.authorBenamirouche, Rachid
dc.date.accessioned2023-03-05T10:46:54Z
dc.date.available2023-03-05T10:46:54Z
dc.date.issued2020-12-31
dc.description.abstractAs part of this contribution, we will illustrate the effectiveness of the Bayesian approach in estimating durations; we suggest a new definition of the Kaplan Meier Bayesian estimator based on a stochastic approximation under an informative prior. For this reason, based on the lognormal distribution, we have unconjugated a priori distributions. This method of processing makes it possible to assume that the use of the a priori data with the various suggested methods is sensitive to the choices of the parameters added.en_US
dc.identifier.citationPempie, Pascal . Hamimes, Ahmed . Benamirouche, Rachid. Integration Of Prior Information In Kaplan Meier Estimator Using Bayesian Approach . Vol 01. N 02. 31/12/2020. University of Eloued [Write down the date][Copy the download link]en_US
dc.identifier.issn2773-2916
dc.identifier.urihttps://dspace.univ-eloued.dz/handle/123456789/15305
dc.language.isoenen_US
dc.publisherجامعة الوادي - University of Eloueden_US
dc.subjectBayesian approach; nonparametric survival; Kaplan Meier; Bayesian estimator.en_US
dc.titleIntegration Of Prior Information In Kaplan Meier Estimator Using Bayesian Approachen_US
dc.typeArticleen_US

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