EconPapers    
Economics at your fingertips  
 

Distribution-Free Multivariate Phase I Shewhart Control Charts: Analysis, Comparisons and Recommendations

Giovanna Capizzi () and Guido Masarotto ()
Additional contact information
Giovanna Capizzi: University of Padua, Department of Statistical Sciences
Guido Masarotto: University of Padua, Department of Statistical Sciences

A chapter in Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science, 2024, pp 59-81 from Springer

Abstract: Abstract The need to develop nonparametric techniques for multivariate Phase I analysis has received increasing attention in the statistical process monitoring literature. Some critical issues related to univariate Phase I analysis become even more challenging when several quality characteristics need to be analysed simultaneously. Multivariate Shewhart-type control charts, such as Hotelling’s T 2 $$T^2$$ control chart, are simple to use and effective in detecting large outliers in Phase I applications. However, the traditional design of the T 2 $$T^2$$ chart assumes that the underlying process distribution is multivariate normal. When this assumption is violated, the chart’s signals become questionable. This study investigates a class of distribution-free Phase I Shewhart-type control charts for detecting shifts in the location vector of a multivariate process. This class contains the original Hotelling’s T 2 $$T^2$$ control statistic, as well as other T 2 $$T^2$$ -type control statistics based on affine invariant transformations of the original multivariate data, such as the ranks of the Mahalanobis depths, the spatial signs and the multivariate spatial and signed ranks. To attain the desired in-control properties independently of the underlying process distribution, a permutation-based approach is used and recommended to compute the control limits. A simulation study is carried out to investigate the out-of-control performance of these distribution-free Phase I Shewhart control charts and provide practical recommendations to users.

Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-69111-9_3

Ordering information: This item can be ordered from
http://www.springer.com/9783031691119

DOI: 10.1007/978-3-031-69111-9_3

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-02-19
Handle: RePEc:spr:sprchp:978-3-031-69111-9_3