Bivariate copulas on the exponentially weighted moving average control chart

Bivariate copulas on the exponentially weighted moving average control chart

This paper proposes four types of copulas on the Exponentially Weighted Moving Average (EWMA) control chart when observations are from an exponential distribution using a Monte Carlo simulation approach. The performance of the control chart is based on the Average Run Length (ARL) which is compare...

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Bibliographic Details
Main Authors: Sasigarn Kuvattana, Piyapatr Busababodhin, Yupaporn Areepong, Saowanit Sukparungsee
Format: Article
Language:English
Published: Prince of Songkla University 2016-10-01
Series:Songklanakarin Journal of Science and Technology (SJST)
Subjects:
ARL
copula
EWMA control chart
Monte Carlo simulation
Online Access:http://rdo.psu.ac.th/sjstweb/journal/38-5/38-5-12.pdf
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spelling doaj-0488804e4ddc467c83cfc42c24d604c62020-11-24T22:37:26ZengPrince of Songkla UniversitySongklanakarin Journal of Science and Technology (SJST)0125-33952016-10-0138556957410.14456/sjst-psu.2016.72Bivariate copulas on the exponentially weighted moving average control chartSasigarn Kuvattana0Piyapatr Busababodhin1Yupaporn Areepong2Saowanit Sukparungsee3Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bang Sue, Bangkok, 10800 Thailand.Department of Mathematics, Faculty of Science, Mahasarakham University, Kantharawichai, Maha Sarakham, 41150 Thailand.Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bang Sue, Bangkok, 10800 Thailand.Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Bang Sue, Bangkok, 10800 Thailand.This paper proposes four types of copulas on the Exponentially Weighted Moving Average (EWMA) control chart when observations are from an exponential distribution using a Monte Carlo simulation approach. The performance of the control chart is based on the Average Run Length (ARL) which is compared for each copula. Copula functions for specifying dependence between random variables are used and measured by Kendall’s tau. The results show that the Normal copula can be used for almost all shifts.http://rdo.psu.ac.th/sjstweb/journal/38-5/38-5-12.pdfARLcopulaEWMA control chartMonte Carlo simulation
collection DOAJ
language English
format Article
sources DOAJ
author Sasigarn Kuvattana
Piyapatr Busababodhin
Yupaporn Areepong
Saowanit Sukparungsee
spellingShingle Sasigarn Kuvattana
Piyapatr Busababodhin
Yupaporn Areepong
Saowanit Sukparungsee
Bivariate copulas on the exponentially weighted moving average control chart
Songklanakarin Journal of Science and Technology (SJST)
ARL
copula
EWMA control chart
Monte Carlo simulation
author_facet Sasigarn Kuvattana
Piyapatr Busababodhin
Yupaporn Areepong
Saowanit Sukparungsee
author_sort Sasigarn Kuvattana
title Bivariate copulas on the exponentially weighted moving average control chart
title_short Bivariate copulas on the exponentially weighted moving average control chart
title_full Bivariate copulas on the exponentially weighted moving average control chart
title_fullStr Bivariate copulas on the exponentially weighted moving average control chart
title_full_unstemmed Bivariate copulas on the exponentially weighted moving average control chart
title_sort bivariate copulas on the exponentially weighted moving average control chart
publisher Prince of Songkla University
series Songklanakarin Journal of Science and Technology (SJST)
issn 0125-3395
publishDate 2016-10-01
description This paper proposes four types of copulas on the Exponentially Weighted Moving Average (EWMA) control chart when observations are from an exponential distribution using a Monte Carlo simulation approach. The performance of the control chart is based on the Average Run Length (ARL) which is compared for each copula. Copula functions for specifying dependence between random variables are used and measured by Kendall’s tau. The results show that the Normal copula can be used for almost all shifts.
topic ARL
copula
EWMA control chart
Monte Carlo simulation
url http://rdo.psu.ac.th/sjstweb/journal/38-5/38-5-12.pdf
work_keys_str_mv AT sasigarnkuvattana bivariatecopulasontheexponentiallyweightedmovingaveragecontrolchart
AT piyapatrbusababodhin bivariatecopulasontheexponentiallyweightedmovingaveragecontrolchart
AT yupapornareepong bivariatecopulasontheexponentiallyweightedmovingaveragecontrolchart
AT saowanitsukparungsee bivariatecopulasontheexponentiallyweightedmovingaveragecontrolchart
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