Bayesian analysis for partially complete time and type of failure data

2013 ◽  
Vol 40 (6) ◽  
pp. 1289-1300 ◽  
Author(s):  
Debasis Kundu
Keyword(s):  
Bayesian Analysis ◽  
Failure Data ◽  
Type Of Failure

Bayesian analysis for masked system failure data using non-identical Weibull models

1999 ◽  
Vol 78 (1-2) ◽  
pp. 255-275 ◽  
Author(s):  
Sanjib Basu ◽  
Asit, P. Basu ◽  
Chiranjit Mukhopadhyay
Keyword(s):  
Bayesian Analysis ◽  
System Failure ◽  
Failure Data ◽  
Weibull Models

The Bayesian analysis of reliability of zero-failure data

2012 ◽  
Author(s):  
Jin Shaohua ◽  
Lu Jianguo ◽  
Wan Yanping ◽  
Sun Shuguang ◽  
Chen Xiuyin
Keyword(s):  
Bayesian Analysis ◽  
Failure Data

E-Bayesian Estimation of Failure Probability under Zero-Failure Data with Double Hyper Parameters

2012 ◽  
Vol 190-191 ◽  
pp. 977-981 ◽  
Author(s):  
Xian Bin Wu
Keyword(s):  
Bayesian Analysis ◽  
Bayesian Estimation ◽  
Uniform Distribution ◽  
Loss Function ◽  
Failure Probability ◽  
Prior Distribution ◽  
Quadratic Loss ◽  
Quadratic Loss Function ◽  
Failure Data

This paper presents the Bayesian analysis of the zero-failure data with double hyper parameters a, b. We take prior distribution of failure probability pi be its conjugated distribution—Beta (pi-1, 1, 1, b) and hyper parameter b as the uniform distribution in (1, c). With quadratic loss function, If pi  (pi-1, 1), the E-Bayesian estimation of pi is . When 0 < c < si, and satisfy (I) ;(II) . The results satisfy . The properties of E-Bayesian estimation are given. A Simulation example is discussed, which shows that the method is both efficiency and easy to operate.

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