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dc.contributor.authorMwanga, Mohamed
dc.contributor.authorTchuenche, Jean
dc.contributor.authorMirau, Silas
dc.contributor.authorMbalawata, Isambi
dc.date.accessioned2023-11-14T11:50:36Z
dc.date.available2023-11-14T11:50:36Z
dc.date.issued2023-03-30
dc.identifier.urihttps://papers.ssrn.com/sol3/Delivery.cfm/1187502a-943b-4ffd-9ffc-bc0255e7ddcc-MECA.pdf?abstractid=4411393&mirid=1
dc.identifier.urihttps://dspace.nm-aist.ac.tz/handle/20.500.12479/2436
dc.descriptionA research article was submitted to SSRN 4411393en_US
dc.description.abstractUnder-five mortality rate is one of the most essential indicator of acountry’s socio-economic well-being and public health status. Poissondistribution under different priors such as conjugate/Gamma prior,uniform and Jeffrey’s prior is used to obtain posterior distribution ofthe unknown parameter with an application to under-five mortalitydata in six East Africa countries from 1960 to 2020. The estimatesare examined through a Bayesian analysis while all the calculationsare carried out the R-statistical software and MS Excel. Among allpriors used in this study, conjugate prior was found to be compatiblefor the unknown parameters of the Poisson distribution. The casesof under-five mortality are found to reduce over time. East Africacountries through East Africa Community (EAC) should build strongand resilient health systems, identify and prioritize interventions tomitigate under-five mortality among Member States.en_US
dc.language.isoenen_US
dc.publisherSSRNen_US
dc.subjectPosterior distributionen_US
dc.subjectUnder-five Mortalityen_US
dc.subjectPoisson Disributionen_US
dc.subjectBayesianen_US
dc.titlePosterior Distribution of the Unknown Parameter of Poisson Distribution Under Different Priors: An Application to Under-Fivemortality Dataen_US
dc.typeArticleen_US


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