Let X1, X2, ..., Xr be the first r order statistics from a sample of size n from the generalized exponential distribution with shape parameter θ. In this paper, we consider a Bayesian approach to predicting future order statistics based on the observed ordered data. The predictive densities are obtained and used to determine prediction intervals for unobserved order statistics for one-sample and two-sample prediction plans. A numerical study is conducted to il- lustrate the prediction procedures.
A. Alamm,A , Raqab,M Z and Madi,M T . (2022). Bayesian Prediction Intervals for Future Order Statistics from the Generalized Exponential Distribution. Journal of the Iranian Statistical Society, 6(1), 17-30.
MLA
A. Alamm,A , , Raqab,M Z , and Madi,M T . "Bayesian Prediction Intervals for Future Order Statistics from the Generalized Exponential Distribution", Journal of the Iranian Statistical Society, 6, 1, 2022, 17-30.
HARVARD
A. Alamm A, Raqab M Z, Madi M T. (2022). 'Bayesian Prediction Intervals for Future Order Statistics from the Generalized Exponential Distribution', Journal of the Iranian Statistical Society, 6(1), pp. 17-30.
CHICAGO
A A. Alamm, M Z Raqab and M T Madi, "Bayesian Prediction Intervals for Future Order Statistics from the Generalized Exponential Distribution," Journal of the Iranian Statistical Society, 6 1 (2022): 17-30,
VANCOUVER
A. Alamm A, Raqab M Z, Madi M T. Bayesian Prediction Intervals for Future Order Statistics from the Generalized Exponential Distribution. JIRSS. 2022;6(1):17-30.
Journal of the Iranian Statistical Society