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Bayesian Prediction based on an Adaptive Type-II Progressive Censored Data from the Generalized Exponential Distribution

by M. M. Mohie El-Din, M. M. Amein, A. R. Shafay, S. Mohamed
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 46
Year of Publication: 2018
Authors: M. M. Mohie El-Din, M. M. Amein, A. R. Shafay, S. Mohamed
10.5120/ijca2018917032

M. M. Mohie El-Din, M. M. Amein, A. R. Shafay, S. Mohamed . Bayesian Prediction based on an Adaptive Type-II Progressive Censored Data from the Generalized Exponential Distribution. International Journal of Computer Applications. 179, 46 ( Jun 2018), 1-6. DOI=10.5120/ijca2018917032

@article{ 10.5120/ijca2018917032,
author = { M. M. Mohie El-Din, M. M. Amein, A. R. Shafay, S. Mohamed },
title = { Bayesian Prediction based on an Adaptive Type-II Progressive Censored Data from the Generalized Exponential Distribution },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2018 },
volume = { 179 },
number = { 46 },
month = { Jun },
year = { 2018 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number46/29481-2018917032/ },
doi = { 10.5120/ijca2018917032 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:58:28.250133+05:30
%A M. M. Mohie El-Din
%A M. M. Amein
%A A. R. Shafay
%A S. Mohamed
%T Bayesian Prediction based on an Adaptive Type-II Progressive Censored Data from the Generalized Exponential Distribution
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 46
%P 1-6
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, based on an observed adaptive Type-II progressively censored sample from the generalized exponential distribution, the problem of predicting the order statistics from a future unobserved sample from the same distribution is discussed. The description of the model of the adaptive Type-II progressively censored sample from the generalized exponential distribution is presented. Also, Markov chain Monte Carlo method is applied to construct the Bayesian prediction intervals of the order statistics from a future sample from the same distribution. Finally, results from simulation studies assessing the performance of our proposed method are included and then an illustrative example using real data set is presented for illustrating all the inferential procedures developed here.

References
  1. Amein, M.M. (2016). Estimation for Unknown Parameters of the Burr Type-XII Distribution Based on an Adaptive Progressive Type-II Censoring Scheme. Journal of Mathematics and Statistics 12, 119-126.
  2. Amein, M.M. (2017). Estimation for Unknown Parameters of the Extended Burr Type-XII Distribution Based on an Adaptive Type-II Progressive Censoring Scheme, Global Journal of Pure and Applied Mathematics 13, 7709-7724.
  3. Balakrishnan, N. (2007). Progressive censoring methodology: An appraisal (with discussions). Test 16, 211-296.
  4. Balakrishnan, N. and Aggarwala, R. (2000). Progressive Censoring: Theory, Methods, and Applications, Birkhauser, Boston, Berlin .
  5. Bernardo, J.M. (1988). Bayesian linear probabilistic classifcation. In: Gupta, S.S., Berger, J.O. (Eds.), Statistical Decision Theory and Related Topics IV, vol. 1. Springer, Berlin, pp. 151162.
  6. Brown, P.J. and Makalainen, T. (1992). Regression, sequential measurements and coherent calibration. In: Bernardo, J.M., Berger, J.O., Dawid, A.P., Smith, A.F.M. (Eds.), Bayesian Statistics 4. Oxford University Press, Oxford, pp. 97108 (with discussion).
  7. Cramer, E. and Iliopoulos, G. (2010). Adaptive progressive Type-II censoring. Test 9, 342-358.
  8. Devroye, L. and Gyorfi, L. (1985). Nonparametric Density Estimation: The L1 View, Wiley, New York.
  9. Gupta, R.D. and Kundu, D. (1999). Generalized exponential distribution. Australian & New Zealand Journal of Statistics 41 173-188.
  10. Hastings, W.K. (1970). Monte Carlo sampling methods using Markovchains and their applications. Biometrika 57, 97-109.
  11. Lawless, J.F. (1982). Statistical models and methods for lifetime data. New York: Wiley.
  12. Mahmoud, M.A.W., Soliman, A.A., Abd Ellah, A.H., El- Sagheer, R.M. (2013). Estimation of Generalized Pareto under an Adaptive Type-II Progressive Censoring,
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive Type-II progressive censored scheme Bayesian prediction Generalized exponential distribution Markov chain Monte Carlo technique

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