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Objective bayesian analysis for the gompertz distribution under doudly type II cesored data

T.N. Sindhu, M. Aslam

Abstract


Trimmed samples are widely utilized in several areas ofstatistical practice, especially when some sample values at either or bothextremes might have been adulterated. In this article, the problem ofestimating the parameter of Gompertz distribution based on trimmed samplesunder informative and non-informative priors has been addressed. The problemdiscussed using Bayesian approach to estimate the parameter of Gompertzdistribution. We have examined Bayes estimates under symmetric and asymmetricloss functions. The explicit expressions for estimator and risk are developedunder all loss functions. Elicitation of hyperparameter through priorpredictive approach is also discussed. Posterior Predictive distributions andCredible Intervals are also derived under different priors. The influence ofparametric value on the estimate and risk is also discussed. Finally, to assessthe performance of the estimators, numerical results using Monte Carlosimulation study were reported.

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