BAYESIAN ESTIMATION OF POPULATION PROPORTION OF A STIGMATIZED ATTRIBUTE USING A FAMILY OF ALTERNATIVE BETA PRIORS

dc.contributor.authorAdepetun, A. O.
dc.contributor.authorAdewara, A. A.
dc.date.accessioned2023-06-13T10:05:09Z
dc.date.available2023-06-13T10:05:09Z
dc.date.issued2015
dc.description.abstractIn this study, we have developed the Bayes estimators of the population proportion of a stigmatized attribute when data were gathered through the randomized response technique (RRT) put forward by Hussain and Shabbir [9]. Using both the Kumaraswamy (KUMA) and the Generalised (GLS) beta distributions as a family of alternative beta priors, superiority of the derived Bayes estimators was established for a large interval of the values of the population proportion. We observed that for small, moderate as well as large sample sizes, the alternative Bayes estimators were better than the Bayes estimator proposed by Hussain and Shabbir [10] when a simple beta prior was useden_US
dc.description.sponsorshipselfen_US
dc.identifier.issn2229-5518
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/11124
dc.language.isoenen_US
dc.publisherInternational Journal of Scientific & Engineering Researchen_US
dc.subjectAlternative Bayes estimators (ABEs), a family of alternative beta priors (FABPs), Stigmatized attribute, Mean Square Error (MSE), Absolute Bias.en_US
dc.titleBAYESIAN ESTIMATION OF POPULATION PROPORTION OF A STIGMATIZED ATTRIBUTE USING A FAMILY OF ALTERNATIVE BETA PRIORSen_US
dc.typeArticleen_US

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