Abstract.
Bayesian predictive densities and survival functions of generalized order statistics are obtained when the underlying population is assumed to have a general class which includes several important distributions. The prior belief of the experimenter is measured by a general class of distributions, suggested by AL-Hussaini (1999)b, which covers most prior distributions used in literature.
Specializations to predictive densities and survival functions of ordinary order statistics and records are obtained and compared with existing results.
Applications to the Weibull(α,β) model are illustrated when α is the only unknown parameter and when both (α,β) are unknown.
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Acknowledgement. The authors appreciate the comments of the referees which improved the original manuscript.
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AL-Hussaini, E., Ahmad, AB. On Bayesian predictive distributions of generalized order statistics. Metrika 57, 165–176 (2003). https://doi.org/10.1007/s001840200207
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DOI: https://doi.org/10.1007/s001840200207