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Bayesian Estimation of A one Parameter Akshaya Distribution with Progressively Type II Censord Data |
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PP: 565-579 |
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doi:10.18576/jsap/110216
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Author(s) |
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Ahlam H.Tolba,
Ehab M. Almetwally,
Dina A. Ramadan,
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Abstract |
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A progressively type-II right censored sample has been examined in this paper for the inference about parameters for the one-parameter Akshaya distribution. As point estimates for the parameter, the maximum likelihood estimate (MLE), and Bayesian estimate are obtained. The asymptotic distribution of MLE is obtained. Also, the approximate confidence intervals (ACIs) and bootstraps confidence intervals for unknown parameter are obtained. Further, for symmetric loss functions such as squared error loss function, Bayesian estimates are obtained. Gibbs within Metropolis–Hasting samplers use the Monte Carlo chain (MCMC) technique to get the estimate of the unknown parameter from Bayes algorithm is used and the relevant credible interval (CRI) is obtained. Finally, the proposed methods are applied a real data set.
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