Evaluations of some Exponentially Weighted Moving Average methods
Christian Sonesson
Journal of Applied Statistics, 2003, vol. 30, issue 10, 1115-1133
Abstract:
The need for statistical surveillance has been noted in many different areas, and examples of applications include the detection of an increased incidence of a disease, the detection of an increased radiation level and the detection of a turning point in a leading index for a business cycle. In all cases, preventive actions are possible if the alarm is made early. Several versions of the EWMA (Exponentially Weighted Moving Average) method for monitoring a process with the aim of detecting a shift in the mean are studied both for the one-sided and the two-sided case. The effects of using barriers for the one-sided alarm statistic are also studied. One important issue is the effect of different types of alarm limits. Different measures of evaluation, suitable in different types of applications, are considered such as the expected delay, the ARL¹, the probability of successful detection and the predictive value of an alarm, to give a broad picture of the features of the methods. Results from a large-scale simulation study are presented both for a fixed ARL0 and a fixed probability of a false alarm. It appears that important differences from an inferential point of view exist between the one- and two-sided versions of the methods. It is demonstrated that the method, usually considered as a convenient approximation, is to be preferred over the exact version in the overwhelming majority of applications.
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/0266476032000107141 (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:japsta:v:30:y:2003:i:10:p:1115-1133
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20
DOI: 10.1080/0266476032000107141
Access Statistics for this article
Journal of Applied Statistics is currently edited by Robert Aykroyd
More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().