Estimation Using Censored Data from Exponentiated Burr Type XII Population
Essam K. AL-Hussaini, Mohamed Hussein
DOI: 10.4236/ojs.2011.12005   PDF   HTML     7,673 Downloads   16,363 Views   Citations


Maximum likelihood and Bayes estimators of the parameters, survival function (SF) and hazard rate function (HRF) are obtained for the three-parameter exponentiated Burr type XII distribution when sample is available from type II censored scheme. Bayes estimators have been developed using the standard Bayes and MCMC methods under square error and LINEX loss functions, using informative type of priors for the parameters. Simulation comparison of various estimation methods is made when n = 20, 40, 60 and censored data. The Bayes estimates are found to be, generally, better than the maximum likelihood estimates against the proposed prior, in the sense of having smaller mean square errors. This is found to be true whether the data are complete or censored. Estimates improve by increasing sample size. Analysis is also carried out for real life data.

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E. AL-Hussaini and M. Hussein, "Estimation Using Censored Data from Exponentiated Burr Type XII Population," Open Journal of Statistics, Vol. 1 No. 2, 2011, pp. 33-45. doi: 10.4236/ojs.2011.12005.

Conflicts of Interest

The authors declare no conflicts of interest.


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