A new nonparametric EWMA Sign Control Chart

Yang, Su‐Fen; Lin, Jheng-Sian; Cheng, Smiley W.

doi:10.1016/j.eswa.2010.11.044

Cited by 121 publications

(142 citation statements)

References 11 publications

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“…We used EWMA charts based on normality [21], and these are robust to such assumption in most cases. However, there are several non-parametric EWMA alternatives that are available in the literature (e.g., Reference [27]). These were not included in the decision support mix provided to nurses because we did not want to provide the nurses with too many different options at the start and therefore confuse them.…”

Section: Review Of the Datamentioning

confidence: 99%

Telehealth Monitoring of Patients in the Community

Sparks

Celler

Okugami

et al. 2016

Journal of Intelligent Systems

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This article outlines a decision support system that seeks to help community nurses monitor the well-being of their chronically ill patients. It is designed for nurses to stay in contact with their patients without spending unnecessary time on less productive aspects of community nursing, such as avoidable driving to and from patients' houses and taking measurements of vital signs to assess their health condition. It therefore allows the nurse to spend more time on managing the factors that could lead to a healthier patient. The decision support system is developed for two levels of mathematical capability. Nurses with a statistical background are provided with in-depth information allowing them to detect changes in mean, mean square error (and hence variation), and correlations using a variation on dynamic principle components. Less mathematically inclined nurses are offered information about trends, change points, and a simpler multivariate view of a patient's well-being involving parallel coordinate plots.

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Section: Review Of the Datamentioning

confidence: 99%

Telehealth Monitoring of Patients in the Community

Sparks

Celler

Okugami

et al. 2016

Journal of Intelligent Systems

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“…Graham et al (2010) and Jones-Farmer et al (2009) have considered distribution-free phase I control charts. Yang et al (2011) proposed a new nonparametric version of EWMA Sign chart for variables data to monitor the deviation from the process target, without assuming a process distribution. A nonparametric exponentially weighted moving average (NPEWMA) control chart combines the advantages of a nonparametric control chart with the better shift detection properties of a traditional EWMA chart.…”

Section: Literature Reviewmentioning

confidence: 99%

A simulation study on the performance of the sign test, Mann-Whitney test, Hodges-Lehmann estimator and control charts for Normal and Weibull data

Jayathavaj¹,

Pongpullponsak²

2014

10.5267/j.ijiec

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The new method to chart the Hodges-Lehmann estimator control chart is proposed in this study. The evaluation of the three nonparametric control charts -the Sign test (ST), Mann-Whitney (MW), and the Hodges-Lehmann estimator (HL), for the known process distribution using normal and Weibull data represent the symmetric and asymmetric shapes of the process based on the original method through the 10000 run lengths simulation. The result illustrates that the average run length performance of the ST and MW correspond to their respective test statistics but for HL's performance, the result indicates that the average run length is much greater than that derived from Wilcoxon signed rank statistics. The Hodges-Lehmann estimator control chart by the new approach for the known process distribution will be the alternative method for the process that needs to robust outliers' properties from this statistics. In addition, the simulation demonstrates that the performances of the Sign test (ST) from mean and median processes are varied in the skewed distribution, and moreover, the Sign test (ST) from the median process represents more accurate performance. Meanwhile, for the control groups, MW generated within control limits or without restriction shows slightly different performance. The performance of dual scheme for the above-mentioned variable parameters control charts also produce the weighted average values that effect from the tight control scheme to the regular control scheme.

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“…Since then numerous extensions on EWMA charts have been made. Among the more recent extensions on EWMA charts are those by Su et al [2], Graham et al [3], Castagliola et al [4], Tsai & Yen [5], Celano et al [6], Yang et al [7], Lee & Apley [8], Perry & Pignatiello [9], Lin & Chou [10], Pascual [11], Ozsan et al [12], Simoes et al [13], Epprecht et al [14], Khoo et al [15], Li et al [16], Spliid [17], Capizzi & Masarotto [18], and Thaga & Yadavalli [19]. The EWMA X chart is excellent in detecting small persistent changes in the mean.…”

Section: Introductionmentioning

confidence: 99%

A STUDY OF THE MEDIAN RUN LENGTH (MRL) PERFORMANCE OF THE EWMA t CHART FOR THE MEAN

Chin

Khoo

2012

sajie

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The exponentially weighted moving average (EWMA) X chart is effective in detecting small shifts. However, the EWMA X chart is not robust enough to prevent errors in estimating the process standard deviation or a changing standard deviation. To overcome this problem, Zhang et al. suggested the EWMA t chart in 2009. The existing optimal design of the EWMA t chart is based on the average run length (ARL) criterion. This paper proposes that the optimal design of the EWMA t chart be based on the median run length (MRL). The MRL performances of the optimal EWMA X and optimal EWMA t charts are compared. OPSOMMINGDie eksponensiaalgeweegde bewegende gemiddelde (EWMA) X -kaart is geskik om klein verskuiwings te bespeur. Die EWMA X -kaart is egter nie robuust genoeg om foute in die beraming van die proses standaardafwyking of 'n veranderende standaardafwyking te voorkom nie. Om die probleem te oorkom het Zhang et al. in 2009 die EWMA t-kaart voorgestel. Die bestaande, optimale ontwerp van die EWMA t-kaart is gebaseer op die gemiddelde lopielengte kriterium. Dié artikel stel voor dat die optimale ontwerp van die EWMA t-kaart eerder op die mediaanlopielengte gebaseer word. Die resultate van die gebruik van die mediaanlopielengte met die EWMA X -en die optimale EWMA t-kaarte word vergelyk.

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A new nonparametric EWMA Sign Control Chart

Cited by 121 publications

References 11 publications

Telehealth Monitoring of Patients in the Community

Telehealth Monitoring of Patients in the Community

A simulation study on the performance of the sign test, Mann-Whitney test, Hodges-Lehmann estimator and control charts for Normal and Weibull data

A STUDY OF THE MEDIAN RUN LENGTH (MRL) PERFORMANCE OF THE EWMA t CHART FOR THE MEAN

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