Bayesian Estimation and Prediction for the Generalized Burr Distribution

نوع المستند : المقالة الأصلية

المؤلف

AL-Sayed, N. T., EL-Helbawy, A. A. and AL-Dayian, G. R. Statistics Department, Faculty of Commerce AL-Azhar University (Girls' Branch), Cairo, Egypt

المستخلص

In this paper, Bayes estimators for the parameters,
reliability and hazard rate functions of the generalized Burr
distribution are derived. Point and credible interval
estimation are considered based on Type II censored data
under a symmetric and asymmetric loss functions. Also,
Bayesian prediction for a future observation is obtained
using two-sample prediction technique. Finally, numerical
examples are given via Markov Chain Monte Carlo
simulation study and some interesting comparisons are
presented to illustrate the theoretical results. Moreover, the
results are applied on real data sets.

نقاط رئيسية

Generalized Burr distribution;

loss functions;
Type II censored data;

Bayesian prediction; Bayesian
predictive density function;

Markov Chain Monte Carlo
simulation.

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