Statistical inference for Burr type III distribution on dual generalized order statistics and real data analysis

2016 ◽  
Vol 10 ◽  
pp. 683-695 ◽  
Author(s):  
Chansoo Kim ◽  
Seongho Song ◽  
Woosuk Kim

Author(s):  
R. E. Abd EL-Kader ◽  
A. M. Abd AL-Fattah ◽  
G. R. AL-Dayian ◽  
A. A. EL-Helbawy

Statistical prediction is one of the most important problems in life testing; it has been applied in medicine, engineering, business and other areas as well. In this paper, the exponentiated generalized xgamma distribution is introduced as an application on the exponentiated generalized general class of distributions. Bayesian point and interval prediction of exponentiated generalized xgamma distribution based on dual generalized order statistics are considered. All results are specialized to lower records. The results are verified using simulation study as well as applications to real data sets to demonstrate the flexibility and potential applications of the distribution.



2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Chansoo Kim ◽  
Woosuk Kim

The estimation of the parameters of Burr type III distribution based on dual generalized order statistics is considered by using the maximum likelihood (ML) approach as well as the Bayesian approach. The exact expression of the expected Fisher information matrix of the parameters in the distribution is obtained. Also, an approximation based on Lindley is used to obtain the Bayes estimator. To compare the maximum likelihood estimator and the Bayes estimator of the parameters, Monte Carlo simulation study is performed.



Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 335
Author(s):  
Mohamed A. Abd Elgawad ◽  
Haroon M. Barakat ◽  
Shengwu Xiong ◽  
Salem A. Alyami

In this paper, we study the concomitants of dual generalized order statistics (and consequently generalized order statistics) when the parameters γ1,⋯,γn are assumed to be pairwise different from Huang–Kotz Farlie–Gumble–Morgenstern bivariate distribution. Some useful recurrence relations between single and product moments of concomitants are obtained. Moreover, Shannon’s entropy and the Fisher information number measures are derived. Finally, these measures are extensively studied for some well-known distributions such as exponential, Pareto and power distributions. The main motivation of the study of the concomitants of generalized order statistics (as an important practical kind to order the bivariate data) under this general framework is to enable researchers in different fields of statistics to use some of the important models contained in these generalized order statistics only under this general framework. These extended models are frequently used in the reliability theory, such as the progressive type-II censored order statistics.



2016 ◽  
Vol 5 (3) ◽  
pp. 243-254
Author(s):  
M. M. Mohie El-Din ◽  
Nahed S. A. Ali ◽  
M. M. Amein ◽  
M. S. Mohamed


Statistics ◽  
2016 ◽  
Vol 51 (3) ◽  
pp. 572-590 ◽  
Author(s):  
M. A. Abd Elgawad ◽  
H. M. Barakat ◽  
Hong Qin ◽  
Ting Yan


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