Monitoring a bivariate INAR(1) process with application to Hepatitis A
Francis G. Pascual and
Sherzod Akhundjanov ()
Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 5, 1036-1058
In this article, we study multivariate monitoring systems based on a bivariate integer-valued autoregressive process of order 1, BINAR(1). The charting procedures are evaluated using extensive simulated shift scenarios, and are compared to multiple univariate charts. The proposed methods improve the efficiency of surveillance systems by taking account of both pairwise correlation and autocorrelation in a bivariate data structure. The methods also account for overdispersion in responses for which the Poisson distribution is inappropriate. An example of hepatitis A incidents in Australia is presented to demonstrate the application of these methods. The proposed methods have important applications in public healthcare and biosurveillance as well as industrial and business applications.
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
Access to full text is restricted to subscribers.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:50:y:2021:i:5:p:1036-1058
Ordering information: This journal article can be ordered from
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 ().