Volume 17, Issue 1, March 2018, Pages 146 - 157
Bayesian Inference Based on Multiply Type-II Censored Sample from a General Class of Distributions
Authors
A.R. Shafaya_shafay2013@yahoo.com
Nature Science Department, Community College of Riyadh, King Saud University, P.O. Box 28095, Riyadh 11437, Saudi Arabia, Department of Mathematics, Faculty of Science, Fayoum University, Fayoum, Egypt
M.M. Mohie El-Dinmmmmoheeldin@yahoo.com
Department of Mathematics, Faculty of Science, Al-Azhar University, Egypt
Y. Abdel-Atyyahia1970@yahoo.com
Department of Mathematics, Faculty of Science, Al-Azhar University, Egypt
Received 18 October 2016, Accepted 21 December 2017, Available Online 31 March 2018.
- DOI
- 10.2991/jsta.2018.17.1.11How to use a DOI?
- Keywords
- Order statistics; Multiply Type-II censored sample; Bayesian prediction; Bayesian estimation; The inverse Weibull distribution; The inverse exponential distribution; The inverse Rayleigh distribution
- Abstract
In this paper, we consider a general form for the underlying distribution and a general conjugate prior, and develop a general procedure for Bayesian estimation based on an observed multiply Type-II censored sample. The problem of predicting the order statistics from a future sample are also discussed from a Bayesian view-point. For the illustration of the developed results, the inverse Weibull distribution is used as example. Finally, two numerical examples are presented for illustrating all the inferential procedures developed here.
- Copyright
- Copyright © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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TY - JOUR AU - A.R. Shafay AU - M.M. Mohie El-Din AU - Y. Abdel-Aty PY - 2018 DA - 2018/03/31 TI - Bayesian Inference Based on Multiply Type-II Censored Sample from a General Class of Distributions JO - Journal of Statistical Theory and Applications SP - 146 EP - 157 VL - 17 IS - 1 SN - 2214-1766 UR - https://doi.org/10.2991/jsta.2018.17.1.11 DO - 10.2991/jsta.2018.17.1.11 ID - Shafay2018 ER -