Bayesian predictive density functions of the median of a set of odd and even number of future order statistics are obtained when the observations (informative and future) are assumed to follow a finite mixture of components of general form and type 1 censoring is imposed on the informative sample. The prior belief of the experimenter is measured by a general class of distributions which includes most priors used in literature. A mixture of two Weibull components model is given as an application. A numerical example presents Bayesian prediction bounds of the future median of observations based on a finite mixture of two exponential components.
Al-Hussaini, E. (2004). Bayesian Prediction of the Median of Future Observations Based on Finite Mixture Models. The Egyptian Statistical Journal, 48(1), 21-33. doi: 10.21608/esju.2004.313571
MLA
Essam K. Al-Hussaini. "Bayesian Prediction of the Median of Future Observations Based on Finite Mixture Models", The Egyptian Statistical Journal, 48, 1, 2004, 21-33. doi: 10.21608/esju.2004.313571
HARVARD
Al-Hussaini, E. (2004). 'Bayesian Prediction of the Median of Future Observations Based on Finite Mixture Models', The Egyptian Statistical Journal, 48(1), pp. 21-33. doi: 10.21608/esju.2004.313571
VANCOUVER
Al-Hussaini, E. Bayesian Prediction of the Median of Future Observations Based on Finite Mixture Models. The Egyptian Statistical Journal, 2004; 48(1): 21-33. doi: 10.21608/esju.2004.313571
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