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. & 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., & 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 & 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.
