scholarly journals E-Bayesian estimation of Burr Type XII model based on adaptive Type-Ⅱ progressive hybrid censored data

2021 ◽  
Vol 6 (4) ◽  
pp. 4173-4196
Author(s):  
Hassan Okasha ◽  
◽  
Mazen Nassar ◽  
Saeed A. Dobbah ◽  
◽  
...  
2011 ◽  
Vol 35 (10) ◽  
pp. 4730-4737 ◽  
Author(s):  
Zeinhum F. Jaheen ◽  
Hassan M. Okasha

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 313
Author(s):  
Xinjing Wang ◽  
Wenhao Gui

With the rapid development of statistics, information entropy is proposed as an important indicator used to quantify information uncertainty. In this paper, maximum likelihood and Bayesian methods are used to obtain the estimators of the entropy for a two-parameter Burr type XII distribution under progressive type-II censored data. In the part of maximum likelihood estimation, the asymptotic confidence intervals of entropy are calculated. In Bayesian estimation, we consider non-informative and informative priors respectively, and asymmetric and symmetric loss functions are both adopted. Meanwhile, the posterior risk is also calculated to evaluate the performances of the entropy estimators against different loss functions. In a numerical simulation, the Lindley approximation and the Markov chain Monte Carlo method were used to obtain the Bayesian estimates. In turn, the highest posterior density credible intervals of the entropy were derived. Finally, average absolute bias and mean square error were used to evaluate the estimators under different methods, and a real dataset was selected to illustrate the feasibility of the above estimation model.


Test ◽  
1992 ◽  
Vol 1 (1) ◽  
pp. 47-60 ◽  
Author(s):  
E. K. Al-Hussaini ◽  
M. A. M. A. Mousa ◽  
Z. F. Jaheen

2019 ◽  
Vol 87 ◽  
pp. 269-284 ◽  
Author(s):  
Chi Liu ◽  
Heng-Chao Li ◽  
Kun Fu ◽  
Fan Zhang ◽  
Mihai Datcu ◽  
...  

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