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A direct procedure for monitoring the coefficient of variation using a variable sample size scheme

A variable sample size (VSS) scheme directly monitoring the coefficient of variation (CV), instead of monitoring the transformed statistics, is proposed. Optimal chart parameters are computed based on two criteria: (i) minimizing the out-of-control ARL (ARL1) and (ii) minimizing the out-of-control A...

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Main Authors: Yeong, W.C., Khoo, M.B.C., Lim, S.L., Lee, M.H.
Format: Article
Published: Marcel Dekker (now owned by Taylor & Francis) 2017
Subjects:
Business
QA Mathematics
Online Access:http://eprints.um.edu.my/18938/
http://dx.doi.org/10.1080/03610918.2015.1109659
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spelling my.um.eprints.189382018-07-30T07:25:19Z http://eprints.um.edu.my/18938/ A direct procedure for monitoring the coefficient of variation using a variable sample size scheme Yeong, W.C. Khoo, M.B.C. Lim, S.L. Lee, M.H. Business QA Mathematics A variable sample size (VSS) scheme directly monitoring the coefficient of variation (CV), instead of monitoring the transformed statistics, is proposed. Optimal chart parameters are computed based on two criteria: (i) minimizing the out-of-control ARL (ARL1) and (ii) minimizing the out-of-control ASS (ASS1). Then the performances are compared between these two criteria. The advantages of the proposed chart over the VSS chart based on the transformed statistics in the existing literature are: the former (i) provides an easier alternative as no transformation is involved and (ii) requires less number of observations to detect a shift when ASS1 is minimized. Marcel Dekker (now owned by Taylor & Francis) 2017 Article PeerReviewed Yeong, W.C. and Khoo, M.B.C. and Lim, S.L. and Lee, M.H. (2017) A direct procedure for monitoring the coefficient of variation using a variable sample size scheme. Communications in Statistics - Simulation and Computation, 46 (6). pp. 4210-4225. ISSN 0361-0918 http://dx.doi.org/10.1080/03610918.2015.1109659 doi:10.1080/03610918.2015.1109659
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic Business
QA Mathematics
spellingShingle Business
QA Mathematics
Yeong, W.C.
Khoo, M.B.C.
Lim, S.L.
Lee, M.H.
A direct procedure for monitoring the coefficient of variation using a variable sample size scheme
description A variable sample size (VSS) scheme directly monitoring the coefficient of variation (CV), instead of monitoring the transformed statistics, is proposed. Optimal chart parameters are computed based on two criteria: (i) minimizing the out-of-control ARL (ARL1) and (ii) minimizing the out-of-control ASS (ASS1). Then the performances are compared between these two criteria. The advantages of the proposed chart over the VSS chart based on the transformed statistics in the existing literature are: the former (i) provides an easier alternative as no transformation is involved and (ii) requires less number of observations to detect a shift when ASS1 is minimized.
format Article
author Yeong, W.C.
Khoo, M.B.C.
Lim, S.L.
Lee, M.H.
author_facet Yeong, W.C.
Khoo, M.B.C.
Lim, S.L.
Lee, M.H.
author_sort Yeong, W.C.
title A direct procedure for monitoring the coefficient of variation using a variable sample size scheme
title_short A direct procedure for monitoring the coefficient of variation using a variable sample size scheme
title_full A direct procedure for monitoring the coefficient of variation using a variable sample size scheme
title_fullStr A direct procedure for monitoring the coefficient of variation using a variable sample size scheme
title_full_unstemmed A direct procedure for monitoring the coefficient of variation using a variable sample size scheme
title_sort direct procedure for monitoring the coefficient of variation using a variable sample size scheme
publisher Marcel Dekker (now owned by Taylor & Francis)
publishDate 2017
url http://eprints.um.edu.my/18938/
http://dx.doi.org/10.1080/03610918.2015.1109659
_version_ 1643690838455222272
score 13.211869

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