DocumentCode
3435242
Title
Notice of Retraction
Bayesian estimation of products with wiener process degradation based on linex loss function
Author
Bao-Wei Song ; Wei-An Yan ; Zhao-Yong Mao ; Gui-Lin Duan
Author_Institution
Coll. of Marine, Northwestern Polytech. Univ., Xi´an, China
fYear
2013
fDate
15-18 July 2013
Firstpage
138
Lastpage
144
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Bayesian estimation for parameters and the reliability of products for which the performance degradation process modeled by wiener process is obtained based on linex loss function. Using both non-informative and conjugate prior distribution, several Bayesian estimates under squared error and linex loss functions are computed. Finally, these Bayesian estimates are compared through the mean squared error (MSE) based on Monte Carlo simulation study. According to these comparisons, it is shown that Bayesian estimators with linex loss function are more flexible.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Bayesian estimation for parameters and the reliability of products for which the performance degradation process modeled by wiener process is obtained based on linex loss function. Using both non-informative and conjugate prior distribution, several Bayesian estimates under squared error and linex loss functions are computed. Finally, these Bayesian estimates are compared through the mean squared error (MSE) based on Monte Carlo simulation study. According to these comparisons, it is shown that Bayesian estimators with linex loss function are more flexible.
Keywords
Bayes methods; mean square error methods; parameter estimation; product quality; reliability; statistical distributions; stochastic processes; Bayesian estimation; Bayesian estimators; Bayesian parameter estimation; MSE; Monte Carlo simulation study; Wiener process degradation; conjugate prior distribution; linex loss function; mean squared error; noninformative distribution; performance degradation process; product reliability; several Bayesian estimates; Bayes methods; Degradation; Density functional theory; Distribution functions; Estimation; Reliability; Stochastic processes; Bayesian estimation; Wiener process; life data; linex loss function; performance degradation data;
fLanguage
English
Publisher
ieee
Conference_Titel
Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE), 2013 International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4799-1014-4
Type
conf
DOI
10.1109/QR2MSE.2013.6625553
Filename
6625553
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