Bayesian Inference of Ailamujia Distribution using Different Loss Functions
We have predominantly considered the Bayes estimator of the parameter of Ailamujia distribution using Jeffrey’s prior and gamma prior supposing three different loss functions. The Jeffrey’s prior gives the prospect of covering wide continuum of priors to get Bayes estimates of the parameter. From the results, we observe that in most cases, Bayesian Estimator under Squared error Loss function has the smallest posterior risk values for both prior’s i.e, Jeffrey’s and gamma prior information.
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