Volume 10, Issue 1 (__1334382579.pdf 2010)
2010, 10(1): 655-672 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Iranpanah N, Mokhtari Moghadam M. Bootstrap Method for Mean Control Limits of Statistical Process. Journal title 2010; 10 (1) :655-672
URL: http://jsci.khu.ac.ir/article-1-1402-en.html
URL: http://jsci.khu.ac.ir/article-1-1402-en.html
1-
2- Univ. of Isfahan- Dep. of Statistics
2- Univ. of Isfahan- Dep. of Statistics
Abstract: (8143 Views)
Shewhart control charts are widely accepted as standard tools monitoring manufacturing statistical processes. The control charts have not applied, when the process distribution is not normal. The bootstrap is one of the resampling methods that can be used in statistical quality control without normality assumption. In most of papers, only the percentile bootstrap confidence interval is used for control limits. In this paper, we apply percentile bootstrap, bootstrap-t, bias corrected accelerated (BCa) and approximate bootstrap confidence interval (ABC) for mean control limits of statistical process. Then, the bootstrap confidence intervals are used and compared for mean control limits in simulation study. Finally, the bootstrap control limits are used for mean of CO2 data in Isfahan Zamzam factory.
Send email to the article author
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
