Please use this identifier to cite or link to this item:
https://doi.org/10.1002/qre.778
DC Field | Value | |
---|---|---|
dc.title | Robust regression using probability plots for estimating the Weibull shape parameter | |
dc.contributor.author | Zhang, L.-F. | |
dc.contributor.author | Xie, M. | |
dc.contributor.author | Tang, L.-C. | |
dc.date.accessioned | 2014-10-07T10:25:35Z | |
dc.date.available | 2014-10-07T10:25:35Z | |
dc.date.issued | 2006-12 | |
dc.identifier.citation | Zhang, L.-F., Xie, M., Tang, L.-C. (2006-12). Robust regression using probability plots for estimating the Weibull shape parameter. Quality and Reliability Engineering International 22 (8) : 905-917. ScholarBank@NUS Repository. https://doi.org/10.1002/qre.778 | |
dc.identifier.issn | 07488017 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/87216 | |
dc.description.abstract | The Weibull shape parameter is important in reliability estimation as it characterizes the ageing property of the system. Hence, this parameter has to be estimated accurately. This paper presents a study of the efficiency of using robust regression methods over the ordinary least-squares regression method based on a Weibull probability plot. The emphasis is on the estimation of the shape parameter of the two-parameter Weibull distribution. Both the case of small data sets with outliers and the case of data sets with multiple-censoring are considered. Maximum-likelihood estimation is also compared with linear regression methods. Simulation results show that robust regression is an effective method in reducing bias and it performs well in most cases. Copyright © 2006 John Wiley & Sons, Ltd. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/qre.778 | |
dc.source | Scopus | |
dc.subject | Least-squares estimator | |
dc.subject | Robust regression estimator | |
dc.subject | Shape parameter | |
dc.subject | Weibull distribution | |
dc.subject | Weibull probability plot | |
dc.type | Article | |
dc.contributor.department | INDUSTRIAL & SYSTEMS ENGINEERING | |
dc.description.doi | 10.1002/qre.778 | |
dc.description.sourcetitle | Quality and Reliability Engineering International | |
dc.description.volume | 22 | |
dc.description.issue | 8 | |
dc.description.page | 905-917 | |
dc.description.coden | QREIE | |
dc.identifier.isiut | 000242694100005 | |
Appears in Collections: | Staff Publications |
Show simple item record
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.