Some Omnibus Exponentially Weighted Moving Average Statistical Process Monitoring Schemes

Domangue, Rickie J.; Patch, Steven C.

doi:10.2307/1268782

Cited by 94 publications

(85 citation statements)

References 17 publications

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“…The case of a shift in the variance was studied by Chang and Gan (1994), Crowder and Hamilton (1992) and Morais and Pacheco (1998). The case of a simultaneous shift in both the mean and the variance has been studied by Domangue and Patch (1991), Gan (1995) and Morais and Pacheco (2000). Also shifts in other types of processes have been studied.…”

Section: Different Types Of Ewma Methodsmentioning

confidence: 99%

Evaluations of some Exponentially Weighted Moving Average methods

Sonesson¹

2003

Journal of Applied Statistics

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SUMMARYSeveral versions of the EWMA (Exponentially Weighted Moving Average) method for monitoring a process with the aim of detecting a shift in the mean are studied both for the onesided and the two-sided case. The effects of using barriers for the one-sided alarm statistic are also studied. One important issue is the effect of different types of alarm limits. Different measures of evaluation are considered such as the expected delay, the ARLI, the probability of successful detection and the predictive value of an alarm to give a broad picture of the features of the methods. Results are presented both for a fixed ARLO and a fixed probability of a false alarm. The differences highlight the essential problem of how to define comparability between surveillance methods. The results are from a large-scale simulation study. Special attention is given to the effect on the confidence in the final results by the stochastic variation in the calibration of the methods. It appears that important differences from an inferential point of view exist between the one-and two-sided versions of the methods. It is demonstrated that the method, usually considered as a convenient approximation, is to be preferred over the exact version in many respects.

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Section: Different Types Of Ewma Methodsmentioning

confidence: 99%

Evaluations of some Exponentially Weighted Moving Average methods

Sonesson¹

2003

Journal of Applied Statistics

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“…Page (1963), Rigdon et al (1994), Acosta-Mejia (1998) and Acosta-Mejía and Pignatiello (2000). For, on the other hand, simultaneous surveillance of µ and the variance by a single statistic, see Domangue and Patch (1991), Chen et al (2004) and Costa and Rahim (2004).…”

Section: Suggested Statistics Under Surveillancementioning

confidence: 99%

Evaluations of Likelihood‐Based Surveillance of Volatility

Bock

2007

Financial Surveillance

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The volatility of asset returns are important in finance. Different likelihood based methods of statistical surveillance for detecting a change in the variance are evaluated. The differences are how the partial likelihood ratios are weighted. The full likelihood ratio, Shiryaev-Roberts, Shewhart and the CUSUM methods are derived in case of an independent and identically distributed Gaussian process. The behavior of the methods is studied both when there is no change and when the change occurs at different time points. The false alarms are controlled by the median run length. Differences and limiting equalities of the methods are shown. The performances when the process parameters for which the methods are optimized for differ from the true values of the parameters are evaluated. The methods are illustrated on a period of Standard and Poor's 500 stock market index.

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“…Several publications dealing with the subject of detecting shifts in the dispersion using an EWMA type chart have appeared in the literature (see, e.g., AcostaMejia and Pignatiello, 2000;Domangue and Patch, 1991;MacGregor and Harris, 1993). Our main concern is to detect increases in the process dispersion.…”

Section: The Ewma Control Charts For Monitoring the Process Dispersionmentioning

confidence: 99%

“…The mean of H i is 2 3/4 3/4 0 /2 and 0 2/ √ 2 − √ 2 2 3/4 / / 2 − is the asymptotic standard deviation of H i if the reset is not used. Domangue and Patch (1991) introduced the omnibus EWMA control charts. The statistic used in these charts is Z i = x i − 0 / 0 and the proposed DomanguePatch (DP) scheme is…”

Section: The Ewma Control Charts For Monitoring the Process Dispersionmentioning

confidence: 99%

“…The performance of the EWMA charts for the dispersion under non normality appears to have been studied so far only by Stoumbos and Reynolds (2000). In this article, we examine the performance under non normality of the charts discussed in Stoumbos and Reynolds (2000) along with a new suggestion and other EWMA charts that have been proposed (Domangue and Patch, 1991) for monitoring a process' dispersion.…”

Section: Introductionmentioning

confidence: 99%

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