On the posterior property of the Rician distribution

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dc.contributor.authorAchire, Enrique
dc.contributor.authorRamos, Eduardo
dc.contributor.authorRamos, Pedro Luiz
dc.date.accessioned2025-01-20T16:04:31Z
dc.date.available2025-01-20T16:04:31Z
dc.date.issued2024
dc.description.abstractThe Rician distribution, a well-known statistical distribution frequently encountered in fields like magnetic resonance imaging and wireless communications, is particularly useful for describing many real phenomena such as signal process data. In this paper, we introduce objective Bayesian inference for the Rician distribution parameters, specifically the Jeffreys rule and Jeffreys prior are derived. We proved that the obtained posterior for the first priors led to an improper posterior while the Jeffreys prior led to a proper distribution. To evaluate the effectiveness of our proposed Bayesian estimation method, we perform extensive numerical simulations and compare the results with those obtained from traditional moment-based and maximum likelihood estimators. Our simulations illustrate that the Bayesian estimators derived from the Jeffreys prior provide nearly unbiased estimates, showcasing the advantages of our approach over classical techniques. Additionally, our framework incorporates the S.A.F.E. principles - Sustainable, Accurate, Fair, and Explainable - ensuring robustness, fairness, and transparency in predictive modelling.
dc.fuente.origenWOS
dc.identifier.doi10.1080/02331888.2024.2425688
dc.identifier.eissn1029-4910
dc.identifier.issn0233-1888
dc.identifier.urihttps://doi.org/10.1080/02331888.2024.2425688
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/89787
dc.identifier.wosidWOS:001353293300001
dc.language.isoen
dc.revistaStatistics
dc.rightsacceso restringido
dc.subjectObjective prior
dc.subjectJeffreys prior
dc.subjectproper posterior
dc.subjectRician distribution
dc.titleOn the posterior property of the Rician distribution
dc.typeartículo
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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