DocumentCode :
111540
Title :
Statistical Inference of a Two-Component Series System With Correlated Log-Normal Lifetime Distribution Under Multiple Type-I Censoring
Author :
Tsai-Hung Fan ; Tsung-Ming Hsu
Author_Institution :
Grad. Inst. of Stat., Nat. Central Univ., Jhongli, Taiwan
Volume :
64
Issue :
1
fYear :
2015
fDate :
Mar-15
Firstpage :
376
Lastpage :
385
Abstract :
In a series system, the system fails if any of the components fails. When the system functions, there may exist correlation among components because they are connected within the same system. In this paper, we consider the reliability analysis of multiple Type-I censored life tests of series systems composed of two components with bivariate log-normal lifetime distributions. The major interest is the inference on the mean lifetimes, and the reliability functions of the system and its components. Given observations of the minimum lifetime of the components of each failed system, location of the MLEs highly relies on the initial values in executing the computation numerically. Alternatively, we apply the Bayesian approach after a re-parametrization of the parameters of interest. A simulation study is conducted which shows that the Bayesian approach provides considerably accurate inference. The proposed approach is successfully applied to a real data set.
Keywords :
inference mechanisms; log normal distribution; maximum likelihood estimation; reliability; Bayesian approach; MLE; bivariate log-normal lifetime distributions; correlated log-normal lifetime distribution; maximum likelihood estimates; multiple type-I censored life tests; re-parametrization; reliability analysis; reliability functions; statistical inference; two-component series system; Bayes methods; Correlation; Maximum likelihood estimation; Numerical models; Reliability; Standards; Bivariate log-normal distribution; life test; multiple Type-I censoring; series system;
fLanguage :
English
Journal_Title :
Reliability, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9529
Type :
jour
DOI :
10.1109/TR.2014.2337813
Filename :
6866268
Link To Document :
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