BAYESIAN ESTIMATION OF POPULATION PROPORTION OF A STIGMATIZED ATTRIBUTE USING A FAMILY OF ALTERNATIVE BETA PRIORS
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Date
2015
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International Journal of Scientific & Engineering Research
Abstract
In 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 used
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Keywords
Alternative Bayes estimators (ABEs), a family of alternative beta priors (FABPs), Stigmatized attribute, Mean Square Error (MSE), Absolute Bias.