BAYESIAN TWO-SAMPLE PREDICTION OF THE GENERALIZED PARETO DISTRIBUTION WITH FIXED AND RANDOM SAMPLE SIZES BASED ON GENERALIZED ORDER STATISTICS

Mohamed Abd Al wahhab Mahmoud; Asmaa Ahmed Saleh

doi:10.24297/jam.v9i5.2334

BAYESIAN TWO-SAMPLE PREDICTION OF THE GENERALIZED PARETO DISTRIBUTION WITH FIXED AND RANDOM SAMPLE SIZES BASED ON GENERALIZED ORDER STATISTICS

Authors

Mohamed Abd Al wahhab Mahmoud Mathematics Department, Faculty of Science, Al-Azhar University
Asmaa Ahmed Saleh Mathematics Department, Faculty of women, Ain Sams University, Cairo, Egypt

DOI:

https://doi.org/10.24297/jam.v9i5.2334

Keywords:

Two-samples Bayesian prediction, generalized order statistics, generalized Pareto distribution, ordinary order statistics, progressive type II censoring, random sample size.

Abstract

Bayesian predictive intervals for future observations from a future sample from the generalized Pareto distribution (GPD) based on generalized order statistics (GOS) are obtained when the shape parameter is unknown. We consider two cases: (i) fixed sample size (FSS), and (ii) random sample size (RSS).Some closed forms for the Bayesian predictive functions are obtained. Finally examples are calculated for the lower and the upper bounds of the future observations in cases when the future sample is ordinary order statistics (OOS), record values and progressive type II censoring with different values for the scale parameter

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Author Biographies

Mohamed Abd Al wahhab Mahmoud, Mathematics Department, Faculty of Science, Al-Azhar University

Mathematics Department, Faculty of Science, Al-Azhar University

Asmaa Ahmed Saleh, Mathematics Department, Faculty of women, Ain Sams University, Cairo, Egypt

Mathematics Department,

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Published

2014-11-18

How to Cite

Mahmoud, M. A. A. wahhab, & Saleh, A. A. (2014). BAYESIAN TWO-SAMPLE PREDICTION OF THE GENERALIZED PARETO DISTRIBUTION WITH FIXED AND RANDOM SAMPLE SIZES BASED ON GENERALIZED ORDER STATISTICS. JOURNAL OF ADVANCES IN MATHEMATICS, 9(5), 2635–2646. https://doi.org/10.24297/jam.v9i5.2334