Toggle Main Menu Toggle Search

Open Access padlockePrints

Exact Average Run Lengths for Monitoring Poisson Counts

Lookup NU author(s): Dr Mike Cox

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

Control charts are widely employed in public health surveillance. One use is as an aid in monitoring rare health events. A chart is designed to exhibit acceptable average run lengths both when the process is in and out of control. Thus, the chart provides a real-time assessment of the situation. This paper considers the average run lengths of general control charts associated with the Poisson distribution. The Shewhart, cumulative sum, and exponentially weighted moving average charts are special cases of the general chart considered here. An exact solution for the average run length is found for a chart with integer parameters. An approximate solution is obtained for a chart with non integer parameters. If desired, this solution can be iterated to provide an accurate full description of the average run length distribution.Short AbstractControl charts are widely employed in public health surveillance. A chart is designed to exhibit acceptable average run lengths both when the process is in and out of control. Thus, the chart provides a real-time assessment of the situation. This paper considers the average run lengths of general control charts associated with the Poisson distribution. An exact solution for the average run length is found for a chart with integer parameters. An approximate solution is obtained for a chart with non integer parameters. If desired, this solution can be iterated to provide the exact average run length distribution.


Publication metadata

Author(s): Cox MAA

Publication type: Article

Publication status: Published

Journal: Communications in Statistics - Theory and Methods

Year: 2015

Volume: 44

Issue: 22

Pages: 4757-4771

Print publication date: 01/01/2015

Online publication date: 14/11/2014

Acceptance date: 01/03/2013

ISSN (print): 0361-0926

ISSN (electronic): 1532-415X

Publisher: Taylor & Francis Inc.

URL: http://dx.doi.org/10.1080/03610926.2013.784997

DOI: 10.1080/03610926.2013.784997


Altmetrics

Altmetrics provided by Altmetric


Actions

Find at Newcastle University icon    Link to this publication


Share