Analytical Method of Average Run Length for Trend Exponential AR(1) Processes in EWMA Procedure

Suriyakat, W; Areepong, Y; Sukparungsee, S; Mititelu, G

Analytical Method of Average Run Length for Trend Exponential AR(1) Processes in EWMA Procedure

Suriyakat, W Areepong, Y Sukparungsee, S Mititelu, G

Permalink

Publisher:: International Association of Engineers
Publication Type:: Journal Article
Citation:: IAENG International Journal of Applied Mathematics, 2012, 42 (4), pp. 1 - 4
Issue Date:: 2012-01

Closed Access

	Filename	Description	Size
	2012003079OK.pdf		763.98 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Suriyakat, W	en_US
dc.contributor.author	Areepong, Y	en_US
dc.contributor.author	Sukparungsee, S	en_US
dc.contributor.author	Mititelu, G	en_US
dc.date.issued	2012-01	en_US
dc.identifier.citation	IAENG International Journal of Applied Mathematics, 2012, 42 (4), pp. 1 - 4	en_US
dc.identifier.issn	1992-9978	en_US
dc.identifier.uri	http://hdl.handle.net/10453/22775
dc.description.abstract	The Exponentially Weighted Moving Average (EWMA) procedure are used for monitoring and detecting small shifts in the process mean which performs quicker than the Shewhart control chart. Usually, the common assumption of the Statistical Process Control (SPC) is the observations are independent and identically distributed (IID). In practice, however, the observed data are from industry and finance is serially correlated with trend. In this paper, we extend to use CUSUM procedure to compare with EWMA procedure. The performance of latter is superior to the former when the magnitudes of shift are small to moderate. It is shown that EWMA procedure performs better than the CUSUM procedure for the case of trend exponential AR(1) processes.	en_US
dc.publisher	International Association of Engineers	en_US
dc.relation.ispartof	IAENG International Journal of Applied Mathematics	en_US
dc.title	Analytical Method of Average Run Length for Trend Exponential AR(1) Processes in EWMA Procedure	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	42	en_US
utslib.for	0102 Applied Mathematics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.issue	4	en_US
pubs.volume	42	en_US

Abstract:

The Exponentially Weighted Moving Average (EWMA) procedure are used for monitoring and detecting small shifts in the process mean which performs quicker than the Shewhart control chart. Usually, the common assumption of the Statistical Process Control (SPC) is the observations are independent and identically distributed (IID). In practice, however, the observed data are from industry and finance is serially correlated with trend. In this paper, we extend to use CUSUM procedure to compare with EWMA procedure. The performance of latter is superior to the former when the magnitudes of shift are small to moderate. It is shown that EWMA procedure performs better than the CUSUM procedure for the case of trend exponential AR(1) processes.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/22775