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. 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,
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.
