DocumentCode
3438317
Title
Notice of Retraction
Outlier test and analysis method of degradation data based on linear regression
Author
Hui-Rui Zhang ; Yun-Xia Chen ; Rui Kang ; Feng-Chun Lin
Author_Institution
Sch. of Reliability & Syst. Eng., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
fYear
2013
fDate
15-18 July 2013
Firstpage
854
Lastpage
858
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.
Under the assumption that the degradation data obey the same path model form, a degradation outlier test method based on path model is presented in this paper. Through testing whether the model parameters are equal for two groups of degradation data, the abnormal data can be distinguished. The critical regions are given based on Chow test. Furthermore, a new analysis method of abnormal degradation data is proposed. It can examine the differences in model intercepts and slopes of degradation data, and determine whether the degradation abnormity is caused by the differences in intercepts or slopes or both. The presented methods are available for degradation data point and segment, and provide a scientific gist for the judgment and correction of abnormal data. Finally, an example is given to verify these methods.
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.
Under the assumption that the degradation data obey the same path model form, a degradation outlier test method based on path model is presented in this paper. Through testing whether the model parameters are equal for two groups of degradation data, the abnormal data can be distinguished. The critical regions are given based on Chow test. Furthermore, a new analysis method of abnormal degradation data is proposed. It can examine the differences in model intercepts and slopes of degradation data, and determine whether the degradation abnormity is caused by the differences in intercepts or slopes or both. The presented methods are available for degradation data point and segment, and provide a scientific gist for the judgment and correction of abnormal data. Finally, an example is given to verify these methods.
Keywords
data handling; regression analysis; statistical testing; Chow test; abnormal data correction; abnormal data judgment; abnormal degradation data; degradation abnormity; degradation data point; degradation data segment; degradation data slopes; degradation outlier test method; linear regression; model intercepts; model parameters; outlier analysis method; path model form; Analytical models; Data models; Degradation; Electrical resistance measurement; Estimation; Linear regression; Reliability; chow test; degradation; degradation path; linear regression; outlier test;
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.2013.6625703
Filename
6625703
Link To Document