Bayes Estimation Based on Joint Progressive Type II Censored Data Under LINEX Loss Function

2013 ◽  
pp. 130102064423005 ◽  
Author(s):  
Mahdi Doostparast ◽  
Mohammad Vali Ahmadi ◽  
Jafar Ahmadi
Keyword(s):  
Censored Data ◽  
Loss Function ◽  
Bayes Estimation ◽  
Type Ii ◽  
Linex Loss Function ◽  
Linex Loss ◽  
Progressive Type ◽  
Type Ii Censored Data

scholarly journals On estimation of gumbel type-ii with numerous kinds of linex loss function

2021 ◽  
Vol 1897 (1) ◽  
pp. 012008
Author(s):  
Nadia J. Fezaa Al-Obedy ◽  
Wafaa S. Hasanain
Keyword(s):  
Loss Function ◽  
Type Ii ◽  
Linex Loss Function ◽  
Linex Loss

scholarly journals Bayes Estimation of a Two-Parameter Geometric Distribution under Multiply Type II Censoring

2011 ◽  
Vol 2011 ◽  
pp. 1-10
Author(s):  
J. B. Shah ◽  
M. N. Patel
Keyword(s):  
Geometric Distribution ◽  
Correct Choice ◽  
Bayes Estimation ◽  
Loss Functions ◽  
Type Ii ◽  
Expected Loss ◽  
Bayes Estimators ◽  
Linex Loss ◽  
Type Ii Censored Data ◽  
Two Parameter

We derive Bayes estimators of reliability and the parameters of a two- parameter geometric distribution under the general entropy loss, minimum expected loss and linex loss, functions for a noninformative as well as beta prior from multiply Type II censored data. We have studied the robustness of the estimators using simulation and we observed that the Bayes estimators of reliability and the parameters of a two-parameter geometric distribution under all the above loss functions appear to be robust with respect to the correct choice of the hyperparameters a(b) and a wrong choice of the prior parameters b(a) of the beta prior.

scholarly journals Estimating the Parameters of the Exponential-Geometric distribution based on progressively type-II censored data

2018 ◽  
Vol 6 (1) ◽  
pp. 37
Author(s):  
Aisha Fayomi ◽  
Hamdah Al-Shammari
Keyword(s):  
Censored Data ◽  
Geometric Distribution ◽  
Asymptotic Variance ◽  
Parameters Estimation ◽  
Type Ii ◽  
Progressive Type ◽  
The Em Algorithm ◽  
Asymptotic Confidence Intervals ◽  
Distribution Parameters ◽  
Type Ii Censored Data

This paper deals with the problem of parameters estimation of the Exponential-Geometric (EG) distribution based on progressive type-II censored data. It turns out that the maximum likelihood estimators for the distribution parameters have no closed forms, therefore the EM algorithm are alternatively used. The asymptotic variance of the MLEs of the targeted parameters under progressive type-II censoring is computed along with the asymptotic confidence intervals. Finally, a simple numerical example is given to illustrate the obtained results.

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