Generalized logistic distribution: Bayesian estimations

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dc.contributor.authorAsgharzadeh, A.
dc.contributor.authorFallah, A.
dc.date.accessioned2024-07-12T20:56:17Z
dc.date.available2024-07-12T20:56:17Z
dc.date.issued2009en_US
dc.departmentMaltepe Üniversitesi, İnsan ve Toplum Bilimleri Fakültesien_US
dc.description.abstractIn this paper, we consider a Bayesian approach to estimate the generalized logistic parameters. The maximum likelihood (ML) and the Bayes estimates are derived for the two unknown parameters and some survival time parameters. The Bayes estimates are derived with respect to conjugate prior for the shape parameter and, discrete prior for the scale parameter of this model. Monte Carlo simulations are presented to compare the Bayes estimates and the ML estimates of the unknown parameters and the reliability function.en_US
dc.identifier.citationAsgharzadeh, A. ve Fallah, A. (2009). Generalized logistic distribution: Bayesian estimations. International Conference on Mathematical Sciences, Maltepe Üniversitesi. s. 32-33.en_US
dc.identifier.endpage33en_US
dc.identifier.isbn9.78605E+12
dc.identifier.startpage32en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12415/2959
dc.language.isoenen_US
dc.publisherMaltepe Üniversitesien_US
dc.relation.ispartofInternational Conference on Mathematical Sciencesen_US
dc.relation.publicationcategoryUluslararası Konferans Öğesi - Başka Kurum Yazarıen_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.snmzKY07896
dc.titleGeneralized logistic distribution: Bayesian estimationsen_US
dc.typeConference Object
dspace.entity.typePublication

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