In this paper, the maximum likelihood and Bayesian estimations are developed based on the pooled sample of two independent Type-II censored samples from the left truncated exponential distribution. The Bayesian estimation is discussed using different loss functions. The problem of predicting the failure times from a future sample from the sample population is also discussed from a Bayesian viewpoint. A Monte Carlo simulation study is conducted to compare the maximum likelihood estimator with the Bayesian estimators. Finally, an illustrative example is presented to demonstrate the different inference methods discussed here.
Published in | American Journal of Theoretical and Applied Statistics (Volume 3, Issue 6) |
DOI | 10.11648/j.ajtas.20140306.15 |
Page(s) | 202-210 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2014. Published by Science Publishing Group |
Bayesian Estimation, Pooled Type-II Censored Samples, Left Truncated Exponential Distribution, Bayesian Prediction, Maximum Likelihood Estimation
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APA Style
Mustafa Mohie El-Din, Yahia Abdel-Aty, Ahmed Shafay, Magdy Nagy. (2014). Bayesian Inference for the Left Truncated Exponential Distribution Based on Pooled Type-II Censored Samples. American Journal of Theoretical and Applied Statistics, 3(6), 202-210. https://doi.org/10.11648/j.ajtas.20140306.15
ACS Style
Mustafa Mohie El-Din; Yahia Abdel-Aty; Ahmed Shafay; Magdy Nagy. Bayesian Inference for the Left Truncated Exponential Distribution Based on Pooled Type-II Censored Samples. Am. J. Theor. Appl. Stat. 2014, 3(6), 202-210. doi: 10.11648/j.ajtas.20140306.15
AMA Style
Mustafa Mohie El-Din, Yahia Abdel-Aty, Ahmed Shafay, Magdy Nagy. Bayesian Inference for the Left Truncated Exponential Distribution Based on Pooled Type-II Censored Samples. Am J Theor Appl Stat. 2014;3(6):202-210. doi: 10.11648/j.ajtas.20140306.15
@article{10.11648/j.ajtas.20140306.15, author = {Mustafa Mohie El-Din and Yahia Abdel-Aty and Ahmed Shafay and Magdy Nagy}, title = {Bayesian Inference for the Left Truncated Exponential Distribution Based on Pooled Type-II Censored Samples}, journal = {American Journal of Theoretical and Applied Statistics}, volume = {3}, number = {6}, pages = {202-210}, doi = {10.11648/j.ajtas.20140306.15}, url = {https://doi.org/10.11648/j.ajtas.20140306.15}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20140306.15}, abstract = {In this paper, the maximum likelihood and Bayesian estimations are developed based on the pooled sample of two independent Type-II censored samples from the left truncated exponential distribution. The Bayesian estimation is discussed using different loss functions. The problem of predicting the failure times from a future sample from the sample population is also discussed from a Bayesian viewpoint. A Monte Carlo simulation study is conducted to compare the maximum likelihood estimator with the Bayesian estimators. Finally, an illustrative example is presented to demonstrate the different inference methods discussed here.}, year = {2014} }
TY - JOUR T1 - Bayesian Inference for the Left Truncated Exponential Distribution Based on Pooled Type-II Censored Samples AU - Mustafa Mohie El-Din AU - Yahia Abdel-Aty AU - Ahmed Shafay AU - Magdy Nagy Y1 - 2014/12/02 PY - 2014 N1 - https://doi.org/10.11648/j.ajtas.20140306.15 DO - 10.11648/j.ajtas.20140306.15 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 202 EP - 210 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20140306.15 AB - In this paper, the maximum likelihood and Bayesian estimations are developed based on the pooled sample of two independent Type-II censored samples from the left truncated exponential distribution. The Bayesian estimation is discussed using different loss functions. The problem of predicting the failure times from a future sample from the sample population is also discussed from a Bayesian viewpoint. A Monte Carlo simulation study is conducted to compare the maximum likelihood estimator with the Bayesian estimators. Finally, an illustrative example is presented to demonstrate the different inference methods discussed here. VL - 3 IS - 6 ER -