EconPapers    
Economics at your fingertips  
 

Exponentially weighted moving average charts for correlated multivariate Poisson processes

Sherzod Akhundjanov () and Francis G. Pascual

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 10, 4977-5000

Abstract: In this article, we study exponentially weighted moving average (EWMA) control schemes to monitor the multivariate Poisson distribution with a general covariance structure, so that the practitioner can simultaneously monitor multiple correlated attribute processes more effectively. The statistical performance of the charts is assessed in terms of the run length properties and compared against other mainstream attribute control schemes. The application of the proposed methods to real-life and simulated datasets is demonstrated.

Date: 2017
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2015.1096392 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:46:y:2017:i:10:p:4977-5000

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2015.1096392

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2021-07-14
Handle: RePEc:taf:lstaxx:v:46:y:2017:i:10:p:4977-5000