Journal articles: 'EWMA'

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Bohdalová, Mária, and Michal Greguš. "VaR BASED RISK MANAGEMENT." CBU International Conference Proceedings 1 (June 30, 2013): 25–33. http://dx.doi.org/10.12955/cbup.v1.11.

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In this paper we discuss the Value–at–Risk concept and we analyse the market risk by using EWMA approach. EWMA (exponentially weighted moving average) forecasting technique is a popular measure of various risks in financial risk management. We will compare standard EWMA, robust EWMA and skewed EWMA forecast of VaR. JP Morgan standard EWMA is derived from Gaussian distribution. Robust EWMA is based on Laplace distribution and skewed EWMA is a new approach derived from an asymmetric Laplace distribution. Asymmetric Laplace distribution takes into account both skewness and heavy tails in return distribution and the time varying nature of them in practice. Skewed EWMA VaR is a generalization of the standard EWMA method. Using these approaches we will analyse selected financial series (three European market indexes and one exchange rate). We have found andconfirmed that skewed EWMA forecasting of VaR outperforms the standard EWMA method.

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Yang, Su-Fen, and Barry C. Arnold. "A Simple Approach for Monitoring Business Service Time Variation." Scientific World Journal 2014 (2014): 1–16. http://dx.doi.org/10.1155/2014/238719.

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Control charts are effective tools for signal detection in both manufacturing processes and service processes. Much of the data in service industries comes from processes having nonnormal or unknown distributions. The commonly used Shewhart variable control charts, which depend heavily on the normality assumption, are not appropriately used here. In this paper, we propose a new asymmetric EWMA variance chart (EWMA-AV chart) and an asymmetric EWMA mean chart (EWMA-AM chart) based on two simple statistics to monitor process variance and mean shifts simultaneously. Further, we explore the sampling properties of the new monitoring statistics and calculate the average run lengths when using both the EWMA-AV chart and the EWMA-AM chart. The performance of the EWMA-AV and EWMA-AM charts and that of some existing variance and mean charts are compared. A numerical example involving nonnormal service times from the service system of a bank branch in Taiwan is used to illustrate the applications of the EWMA-AV and EWMA-AM charts and to compare them with the existing variance (or standard deviation) and mean charts. The proposed EWMA-AV chart and EWMA-AM charts show superior detection performance compared to the existing variance and mean charts. The EWMA-AV chart and EWMA-AM chart are thus recommended.

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Shamsuzzaman, Mohammad. "Optimization Design of 2-EWMA Control Chart Based on Random Process Shift." Applied Mechanics and Materials 465-466 (December 2013): 1185–90. http://dx.doi.org/10.4028/www.scientific.net/amm.465-466.1185.

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The exponentially weighted moving average (EWMA) control charts are widely used for detecting process shifts of small and moderate sizes in Statistical Process Control (SPC).This article presents an algorithm for the optimization design of a multi-EWMA scheme comprising two EWMA control charts (known as 2-EWMA chart) considering random process shifts in mean. The random process shifts in mean is characterized by a Rayleigh distribution. The design algorithm optimizes the charting parameters of the 2-EWMA chart based on loss function. Comparative study shows that the optimal 2-EWMA chart outperforms the original 2-EWMA chart, as well as the original EWMA chart. In general, this article will help to enhance the detection effectiveness of the 2-EWMA chart, and facilitate its applications in SPC.

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CASTAGLIOLA, PHILIPPE, GIOVANNI CELANO, SERGIO FICHERA, and VALERIA NUNNARI. "A VARIABLE SAMPLE SIZE S2-EWMA CONTROL CHART FOR MONITORING THE PROCESS VARIANCE." International Journal of Reliability, Quality and Safety Engineering 15, no. 03 (June 2008): 181–201. http://dx.doi.org/10.1142/s0218539308003039.

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Monitoring the stability of measures dispersion from a process quality parameter is an important aspect of Statistical Process Control which should be carefully planned by practitioners. To perform this task, this paper proposes an adaptive EWMA chart as a practical and efficient tool. The developed EWMA chart is the Variable Sample Size (VSS) version of a static S2-EWMA control chart previously developed by one of the authors to monitor the sample variance. The way to compute the design parameters of this VSS S2-EWMA control chart is discussed and an optimal design strategy based on the Average Time to Signal (ATS) after a shift in process dispersion is presented. The statistical performance of the VSS S2-EWMA has been evaluated by means of a comparison with two other EWMA charts: the static S2-EWMA and the adaptive (VSI) S2-EWMA allowing to vary the sampling intervals. The obtained results show how the possibility of varying the sample size significantly improves the statistical performance over the static S2-EWMA; furthermore, some interesting findings suggest to implement the VSS S2-EWMA with respect to the VSI S2-EWMA when some particular process operating conditions occur.

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Hu, Xuelong, Suying Zhang, Guan Sun, Jianlan Zhong, and Shu Wu. "Modified One-Sided EWMA Charts without- and with Variable Sampling Intervals for Monitoring a Normal Process." Symmetry 14, no. 1 (January 13, 2022): 159. http://dx.doi.org/10.3390/sym14010159.

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Much research has been conducted on two-sided Exponentially Weighted Moving Average (EWMA) control charts, while less work has been devoted to the one-sided EWMA charts. Traditional one-sided EWMA charts involve resetting the EWMA statistic to the target whenever it falls below or above the target, or truncating the observations above or below the target and further applying the EWMA statistic to the truncated samples. In order to further improve the performance of traditional one-sided EWMA mean (X¯) charts, this paper studies the performance of the Modified One-sided EWMA (MOEWMA) X¯ charts to monitor a normally distributed process. The Monte-Carlo simulation method is used to obtain the zero- and steady-state Run Length (RL) properties of the proposed control charts. Through extensive simulations and comparisons with other charts, it is shown that the proposed MOEWMA X¯ charts compare favorably with some existing competing charts. Moreover, by attaching the variable sampling intervals (VSI) feature to the MOEWMA X¯ charts, it is shown that the VSI MOEWMA charts outperform the corresponding charts without the VSI feature. Finally, a real data example from manufacturing process shows the implementation of the proposed one-sided charts.

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ناصر, جنان عباس. "حول خصائص طول التشغيل للوحتي سيطرة ( المجموع المتراكم (Cusum) و المتوسط المتحرك الموزون اسيا (EWMA) ) لتوزيع بواسون." Journal of Economics and Administrative Sciences 25, no. 114 (October 1, 2019): 475–97. http://dx.doi.org/10.33095/jeas.v25i114.1747.

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في هذا البحث نتحرى حول خصائص طول التشغيل للوحتي سيطرة المجموع المتراكم (cumulative sum (Cusum)) والمتوسط المتحرك الموزون اسيا (Exponentially Weighted Moving Average (EWMA)) للكشف عن الانحرافات الموجبة في متوسط العملية عندما تكون العملية تتبع توزيع بواسون بمتوسط غير معلوم. وقد استعمل اسلوب سلسلة ماركوف لحساب المتوسط والانحراف المعياري لطول التشغيل للوحتي سيطرة المجموع المتراكم (Cusum) والمتوسط المتحرك الموزون اسيا (EWMA) عندما يكون المتغير تحت السيطرة يتبع توزيع بواسون. استعملت لوحتي سيطرة الـ Cusum والـ EWMA أيضا لمراقبة متوسط العملية عندما المشاهدات (منتجات اختيرت من مصنع المأمون) تكون مستقلة ومتطابقة التوزيع (iid) من توزيع بواسون بعملية تصنيع مستمرة. اذ افترضنا عدة قيم لمعلمات للوحتي سيطرة الـ poisson Cusum والـ EWMA poisson ولعدد حالات لسلسلة ماركوف. وقد استحصلت نتائج البحث باستعمال برامج مكتوبة ببرنامج Matlab -R2018a . تبين نتائج البحث بان لوحاتي سيطرة الـ poisson Cusum والـ EWMA poisson كانت حساسة أكثر عند قيم معينة لمعلمات لوحتي سيطرة الـ poisson Cusum والـ EWMA poisson. ولعدد الحالات في سلسلة ماركوف.

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Chen, Jen-Hsiang, and Shin-Li Lu. "An Enhanced Auxiliary Information-Based EWMA-t Chart for Monitoring the Process Mean." Applied Sciences 10, no. 7 (March 26, 2020): 2252. http://dx.doi.org/10.3390/app10072252.

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The exponentially weighted moving average t chart using auxiliary information (AIB-EWMA-t chart) is an effective approach for monitoring small process mean shifts when the process standard deviation is unstable or poorly estimated. To further enhance the sensitivity of the AIB-EWMA-t chart, in this study, we propose an AIB generally weighted moving average (GWMA) t chart (AIB-GWMA-t chart) to monitor the process mean. The existing EWMA-t, GWMA-t, and AIB-EWMA-t charts are special cases of the AIB-GWMA-t chart. Numerical simulation studies indicate that the AIB-GWMA-t chart performs uniformly and substantially better than the EWMA-t and GWMA-t charts in terms of average run length. Moreover, the AIB-GWMA-t chart with large design and adjustment parameters also outperforms the AIB-EWMA-t chart when the correlation coefficients are within a certain range. An illustrative example is provided to highlight the efficiency of the proposed AIB-GWMA-t chart in detecting small process mean shifts.

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Nelwati, Nelwati, Hazmira Yozza, and Maiyastri Maiyastri. "Peta Kendali Exponentially Weighted Moving Average (EWMA) Untuk Jumlah Wisatawan Yang Berkunjung Ke Sumatera Barat." Jurnal Matematika UNAND 4, no. 4 (July 26, 2019): 83. http://dx.doi.org/10.25077/jmu.4.4.83-90.2015.

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Pola jumlah wisatawan yang berkunjung ke Sumatera Barat harus selalu dipantau dan dikendalikan oleh pemerintah daerah tersebut. Dalam statistika dikenal suatu metode untuk melihat keterkendalian jumlah wisatawan yang berkunjung ke Sumatera Barat yang dinamakan pengendalian mutu statistik. Dalam penelitian ini akan digunakan salah satu alat dalam SPC yaitu peta kendali Exponentially Weighted Moving Average (EWMA). Peta Kendali ini dapat digunakan untuk melakukan pengendalian statistik terhadap jumlah kunjungan wisatawan ke Sumatera Barat yang merupakan data deret waktu. Pada penelitian ini peta kendali EWMA dibentuk dari jumlah kunjungan wisatawan yang berasal dari negara Malaysia, Australia, Singapura, negara-negara Eropa, Amerika, dan negara lainnya. Peta kendali EWMA negara-negara ini memiliki pola yang hampir sama dan seluruh nilai EWMA berada dalam batas kendali kecuali negara Singapura. Negara Malaysia memiliki nilai EWMA yang paling besar dibandingkan negara-negara lainnya, yang berarti jumlah kunjungan wisatawan asal Malaysia lebih tinggi dibandingkan negara lainnya.Kata Kunci: SPC, Peta Kendali EWMA, Data Pariwisata dan Transportasi Sumatera Barat

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Wang, Hai Yu. "Comparing Robustness of EWMA Dispersion Control Chart for Non-Normal Process." Advanced Materials Research 912-914 (April 2014): 1189–92. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.1189.

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This article discusses robustness to non-normality of EWMA charts for dispersion. Comparison analysis of run length of four kinds of EWMA charts to monitoring process dispersion is provided to evaluate control charts performance and robustness. At last robust EWMA dispersion charts for non-normal processes are proposed by this way.

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Su-Fen, Yang, Tsai Wen-Chi, Huang Tzee-Ming, Yang Chi-Chin, and Cheng Smiley. "Monitoring process mean with a new EWMA control chart." Production 21, no. 2 (May 27, 2011): 217–22. http://dx.doi.org/10.1590/s0103-65132011005000026.

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In practice, sometimes the process data did not come from a known population distribution. So the commonly used Shewhart variables control charts are not suitable since their performance could not be properly evaluated. In this paper, we propose a new EWMA Control Chart based on a simple statistic to monitor the small mean shifts in the process with non-normal or unknown distributions. The sampling properties of the new monitoring statistic are explored and the average run lengths of the proposed chart are examined. Furthermore, an Arcsine EWMA Chart is proposed since the average run lengths of the Arcsine EWMA Chart are more reasonable than those of the new EWMA Chart. The Arcsine EWMA Chart is recommended if we are concerned with the proper values of the average run length.

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Engmann, Gideon Mensah, and Dong Han. "Multichart Schemes for Detecting Changes in Disease Incidence." Computational and Mathematical Methods in Medicine 2020 (May 15, 2020): 1–14. http://dx.doi.org/10.1155/2020/7267801.

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Several methods have been proposed in open literatures for detecting changes in disease outbreak or incidence. Most of these methods are likelihood-based as well as the direct application of Shewhart, CUSUM and EWMA schemes. We use CUSUM, EWMA and EWMA-CUSUM multi-chart schemes to detect changes in disease incidence. Multi-chart is a combination of several single charts that detects changes in a process and have been shown to have elegant properties in the sense that they are fast in detecting changes in a process as well as being computationally less expensive. Simulation results show that the multi-CUSUM chart is faster than EWMA and EWMA-CUSUM multi-charts in detecting shifts in the rate parameter. A real illustration with health data is used to demonstrate the efficiency of the schemes.

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Neubauer, Aljoscha Steffen. "The EWMA control chart: properties and comparison with other quality-control procedures by computer simulation." Clinical Chemistry 43, no. 4 (April 1, 1997): 594–601. http://dx.doi.org/10.1093/clinchem/43.4.594.

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Abstract A quality-control chart based on exponentially weighted moving averages (EWMA) has, in the past few years, become a popular tool for controlling inaccuracy in industrial quality control. In this paper, I explain the principles of this technique, present some numerical examples, and by computer simulation compare EWMA with other control charts currently used in clinical chemistry. The EWMA chart offers a flexible instrument for visualizing imprecision and inaccuracy and is a good alternative to other charts for detecting inaccuracy, especially where small shifts are of interest. Detection of imprecision with EWMA charts, however, requires special modification.

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Chan, K. M., Z. L. Chong, M. B. C. Khoo, K. W. Khaw, and W. L. Teoh. "A Comparative Study of the EWMA and Double EWMA Control Schemes." Journal of Physics: Conference Series 2051, no. 1 (October 1, 2021): 012067. http://dx.doi.org/10.1088/1742-6596/2051/1/012067.

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Abstract A control scheme is the most excellent and irreplaceable tool in Statistical Process Control because of its effectiveness in controlling and monitoring the process, which indirectly helps ensure that the quality of a product is controlled. The EWMA scheme is one of the popular memory-type schemes used to control a normally distributed process. Therefore, various studies and improvements are performed on this scheme and are available in the literature. One of the significant improvements of the EWMA scheme is its extension to the double EWMA scheme, which has a better performance in detecting a small to moderate shift in the process than the traditional EWMA scheme. In order to study and compare the performance of the EWMA and double EWMA schemes in a comprehensive way, other run-length properties, such as the standard deviation and percentiles of the run-length, are also evaluated, rather than solely evaluating the average run-length results. Furthermore, the exact shift size in the process is usually not known in real life. Thus, the expected average run-length and expected median run-length metrics are used to evaluate the overall performances of these two schemes in a range of shift sizes. Then, the implementation of these two schemes is illustrated with a dataset. Last, some concluding remarks are made.

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Ng, Jing Wen, Voon Hee Wong, and Sook Theng Pang. "A synthetic exponentially weighted moving average control chart to monitor process median based on ranked set sampling." ITM Web of Conferences 36 (2021): 01002. http://dx.doi.org/10.1051/itmconf/20213601002.

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Exponentially Weighted Moving Average (EWMA) control charts yield insights into data in a way more comprehensible to the practitioners and researchers because of its capability in discovering small to moderate process mean shifts. EWMA control chart is incorporated with conforming run length (CRL) chart, named synthetic EWMA chart, to enhance the performance of the chart in detecting the out-of-control signal. Synthetic EWMA chart based on ranked set sampling (RSS) for monitoring process mean has been proposed as it advanced the detection of chart over a series of mean shifts. With the situation that normality assumption is scarcely attain in practice, we proposed synthetic EWMA median chart based on RSS. Rather than select average run length (ARL) as sole performance evaluating tool, the median and percentiles of run-length distribution are used to examine the performance of the proposed chart as it provides more information on the entire run-length distribution. Near-optimal parameters of the proposed chart will be acquired by setting the incontrol ARL at a designated value. The run length performances of the proposed chart are then compared with the existing charts such as EWMA median chart based on RSS.

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Yang, Chung Ming, Su Fen Yang, and Jin Tyan Yeh. "Design of EWMA Control Charts for Controlling Dependent Process Stages with Attribute Data." Applied Mechanics and Materials 411-414 (September 2013): 1085–88. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.1085.

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In this study, we propose EWMA control charts to monitor two dependent process stages with attribute data. The detection ability of the EWMA control charts is compared to those of Shewhart attribute control charts and cause selecting control chart by different correlation. Numerical example and simulation study show that the EWMA control charts have better performance compared to Shewhart attribute control charts and cause selecting control charts.

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Resti, Aulia, Tatik Widiharih, and Rukun Santoso. "GRAFIK PENGENDALI MIXED EXPONENTIALLY WEIGHTED MOVING AVERAGE – CUMULATIVE SUM (MEC) DALAM ANALISIS PENGAWASAN PROSES PRODUKSI (Studi Kasus : Wingko Babat Cap “Moel”)." Jurnal Gaussian 10, no. 1 (February 28, 2021): 114–24. http://dx.doi.org/10.14710/j.gauss.v10i1.30938.

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Quality control is an important role in industry for maintain quality stability. Statistical process control can quickly investigate the occurrence of unforeseen causes or process shifts using control charts. Mixed Exponentially Weighted Moving Average - Cumulative Sum (MEC) control chart is a tool used to monitor and evaluate whether the production process is in control or not. The MEC control chart method is a combination of the Exponentially Weighted Moving Average (EWMA) and Cumulative Sum (CUSUM) charts. Combining the two charts aims to increase the sensitivity of the control chart in detecting out of control. To compare the sensitivity level of the EWMA, CUSUM, and MEC methods, the Average Run Length (ARL) was used. From the comparison of ARL values, the MEC chart is the most sensitive control chart in detecting out of control compared to EWMA and CUSUM charts for small shifts. Keywords: Grafik Pengendali, Exponentially Weighted Moving Average, Cumulative Sum, Mixed EWMA-CUSUM, Average Run Lenght, EWMA, CUSUM, MEC, ARL

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Midi, Habshah, and Ashkan Shabbak. "Robust Multivariate Control Charts to Detect Small Shifts in Mean." Mathematical Problems in Engineering 2011 (2011): 1–19. http://dx.doi.org/10.1155/2011/923463.

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The classical multivariate CUSUM and EWMA charts are commonly used to detect small shifts in the mean vectors. It is now evident that those charts are easily affected by outliers which may be due to small or moderate changes in the mean vector. In this paper, we propose a robust multivariate CUSUM and Robust multivariate EWMA charts to remedy the problem of small changed in scatter outliers. Both the empirical and simulation results indicate that the proposed robust multivariate CUSUM and EWMA charts offer substantial improvement over other multivariate CUSUM and EWMA charts. This article also discussed the robustness of the proposed charts, when there is a small or moderate sustained shift in the data set.

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TOLLEY, GILBERT O., and JOHN R. ENGLISH. "Economic designs of constrained EWMA and combined EWMA-X¯ control schemes." IIE Transactions 33, no. 6 (June 2001): 429–36. http://dx.doi.org/10.1080/07408170108936842.

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AFGANI, L. M. JAMALUDDIN Al. "Accuracy of Zero Inflated Generalized Poisson Exponentially Moving Average Control Chart." Jurnal Matematika, Statistika dan Komputasi 18, no. 1 (September 2, 2021): 121–29. http://dx.doi.org/10.20956/j.v18i1.14035.

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The Zero-Inflated Generalized Poisson (ZIGP) distribution is a case-based distribution where the discrete data has a large number of zeros and an overdispersion occurs, i.e. the variance is greater than the mean value. The purpose of this study is to determine the Exponential Weight Moving Average (EWMA) control chart with the assumption that the data has a Zero-Inflated Generalized Poisson (ZIP) distribution. The results show that the ARL value of the ARL ZIGP EWMA control chart has better accuracy when compared to when using the ZIP EWMA control chart on ZIGP distributed data. This is indicated by the smaller ARL value compared to the ZIP EWMA control chart, namely when φ = 1.4, and φ = 0.6. So that the ARL ZIGP EWMA control chart has a fairly good accuracy in detecting out of control conditions for ZIGP distributed data. In addition, the modified ARL shows the same values before and after the modification for the underdispersion data and shows a larger or negative value for the overdispersion data. This can eliminate or reduce errors in analyzing the accuracy of the control chart.

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Supharakonsakun, Yadpirun, Yupaporn Areepong, and Saowanit Sukparungsee. "The performance of a modified EWMA control chart for monitoring autocorrelated PM2.5 and carbon monoxide air pollution data." PeerJ 8 (December 15, 2020): e10467. http://dx.doi.org/10.7717/peerj.10467.

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PM2.5 (particulate matter less than or equal to 2.5 micron) is found in the air and comprises dust, dirt, soot, smoke, and liquid droplets. PM2.5 and carbon monoxide emissions can have a negative impact on humans and animals throughout the world. In this paper, we present the performance of a modified exponentially weighted moving average (modified EWMA) control chart to detect small changes when the observations are autocorrelated with exponential white noise through the average run length evaluated (ARLs) by explicit formulas. The accuracy of the solution was verified with a numerical integral equation method. The efficacy of the modified EWMA control chart to monitor PM2.5 and carbon monoxide air pollution data and compare its performance with the standard EWMA control chart. The results suggest that the modified EWMA control chart is far superior to the standard one.

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DEWIANTARI, NI KADEK YUNI, I. WAYAN SUMARJAYA, and G. K. GANDHIADI. "PETA KENDALI EWMA RESIDUAL PADA DATA BERAUTOKORELASI." E-Jurnal Matematika 8, no. 1 (February 2, 2019): 64. http://dx.doi.org/10.24843/mtk.2019.v08.i01.p236.

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Control charts with autocorrelation can be overcome by creating control chart with residuals from the best forecasting model. EWMA control chart is a alternative to the Shewhart control chart when detecting small shifts. The purpose of this study is to make the best forecasting model to obtain residual, and see the stability of the rupiah exchange rate against US dollar using EWMA control chart with residual. The best model of the case is ARIMA (1,1,1). The results of the EWMA residual control chart with ? = 0.1 there is a pattern that makes the process unstable.

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Borror, Connie M., Charles W. Champ, and Steven E. Rigdon. "Poisson EWMA Control Charts." Journal of Quality Technology 30, no. 4 (October 1998): 352–61. http://dx.doi.org/10.1080/00224065.1998.11979871.

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Zhang, Lingyun, M. S. Bebbington, K. Govindaraju, and C. D. Lai. "Composite EWMA Control Charts." Communications in Statistics - Simulation and Computation 33, no. 4 (October 2004): 1133–58. http://dx.doi.org/10.1081/sac-200040354.

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Yang, Chung Ming, Su Fen Yang, and Jeng Sheng Lin. "A New EWMA Loss Control Chart with Adaptive Control Scheme." Applied Mechanics and Materials 631-632 (September 2014): 12–17. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.12.

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A single chart, instead of and R charts or and S charts, to simultaneously monitor the process mean and variability would reduce the required time and effort. A number of studies have attempted to find such charts. Moreover, a number of studies demonstrated that the adaptive control charts may detect process shifts faster than the fixed control charts. This paper proposes the EWMA loss chart with variable sample sizes and sampling intervals (VSSI) to effectively monitor the difference of process measurements and target. An example is used to illustrate the application and performance of the proposed control chart in detecting the changes in the difference of the process measurements and target. Numerical analyses demonstrated that the VSSI EWMA loss chart outperforms the fixed sampling interval EWMA average loss chart and the Shewhart joint and S charts. Therefore, the VSSI EWMA loss chart is recommended.

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Christianti, Ari. "RISIKO PASAR: PERBANDINGAN MODEL EWMA DAN GARCH PADA NILAI TUKAR RUPIAH TERHADAP US DOLLAR." Jurnal Riset Manajemen dan Bisnis 5, no. 2 (December 1, 2010): 153. http://dx.doi.org/10.21460/jrmb.2010.52.59.

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Financial risk model evaluation or backtesting is a key part of the internal model’s approach to market risk management as laid out by the Basle Committee on Banking Supervision. Using daily exchange rate from January 2006-February 2008, will be compared measuring volatility between EWMA (Exponential Weighted Moving Average) and GARCH (Generalized Autoregressive Conditional Heterocedasticity). The results show that GARCH methods have considerably better power properties in measuring the volatility than the EWMA methods. However, the number of exceptions from the GARCH model, although much less than the EWMA model but the numbers were still above 5% and 1% (confidence level of 95% and 99%). The arguments for explained this finding is a pressure from stakeholders or the existence of an economic events that result in changes in exposure due to the different policies. As a result, the VaR model would be inaccurate to reality.Keywords: volatility, backtesting, EWMA, and GARCH

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Tang, Dan, Kai Chen, XiaoSu Chen, HuiYu Liu, and Xinhua Li. "Adaptive EWMA Method Based on Abnormal Network Traffic for LDoS Attacks." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/496376.

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The low-rate denial of service (LDoS) attacks reduce network services capabilities by periodically sending high intensity pulse data flows. For their concealed performance, it is more difficult for traditional DoS detection methods to detect LDoS attacks; at the same time the accuracy of the current detection methods for LDoS attacks is relatively low. As the fact that LDoS attacks led to abnormal distribution of the ACK traffic, LDoS attacks can be detected by analyzing the distribution characteristics of ACK traffic. Then traditional EWMA algorithm which can smooth the accidental error while being the same as the exceptional mutation may cause some misjudgment; therefore a new LDoS detection method based on adaptive EWMA (AEWMA) algorithm is proposed. The AEWMA algorithm which uses an adaptive weighting function instead of the constant weighting of EWMA algorithm can smooth the accidental error and retain the exceptional mutation. So AEWMA method is more beneficial than EWMA method for analyzing and measuring the abnormal distribution of ACK traffic. The NS2 simulations show that AEWMA method can detect LDoS attacks effectively and has a low false negative rate and a false positive rate. Based on DARPA99 datasets, experiment results show that AEWMA method is more efficient than EWMA method.

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Cisar, Petar, and Sanja Maravic-Cisar. "EWMA statistics and fuzzy logic in function of network anomaly detection." Facta universitatis - series: Electronics and Energetics 32, no. 2 (2019): 249–65. http://dx.doi.org/10.2298/fuee1902249c.

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Anomaly detection is used to monitor and capture traffic anomalies in network systems. Many anomalies manifest in changes in the intensity of network events. Because of the ability of EWMA control chart to monitor the rate of occurrences of events based on their intensity, this statistic is appropriate for implementation in control limits based algorithms. The performance of standard EWMA algorithm can be made more effective combining the logic of adaptive threshold algorithm and adequate application of fuzzy theory. This paper analyzes the theoretical possibility of applying EWMA statistics and fuzzy logic to detect network anomalies. Different aspects of fuzzy rules are discussed as well as different membership functions, trying to find the most adequate choice. It is shown that the introduction of fuzzy logic in standard EWMA algorithm for anomaly detection opens the possibility of previous warning from a network attack. Besides, fuzzy logic enables precise determination of degree of the risk.

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ناصر, جنان عباس. "خاصيتين تصادفية للوحات سيطرة الـEWMA من جانب واحد." Journal of Economics and Administrative Sciences 16, no. 57 (March 1, 2010): 191. http://dx.doi.org/10.33095/jeas.v16i57.1437.

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هذا البحث يقيم نتيجتين تصادفيه رتيبة متعلقة بطول التشغيل للوحة سيطرة المتوسط المتحرك الموزون اسيا (EWMA) من جانب واحد الاعلى، مستندة على اللوغاريتم لتباين العينة، لمراقبة الانحراف المعياري للعملية.تلك الخاصيتين تهتم بتسليط الضوء على اداء لوحة السيطرة، وامتداد تلك الخاصيتين للوحات سيطرة اخرى مثل الـ EWMA من الجانب الاعلى.

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Fronzo, Camila. "Antimicrobial stewardship: wound treatment challenges." Journal of Wound Care 31, no. 2 (February 2, 2022): 118–20. http://dx.doi.org/10.12968/jowc.2022.31.2.118.

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The issues with silver resistance and the effectiveness of using DACC-coated dressings in wound treatment were discussed at an Essity-sponsored symposium. Camila Fronzo noted the key points presented by three speakers at the EWMA and Journées Cicatrisations conference 2021 This conference report presents an overview of the symposium ‘Being smart about wound infection: evaluating and treating wounds in the era of antimicrobial stewardship’, held in October 2021 as part of the joint European Wound Management Association (EWMA) and Journées Cicatrisations virtual conference. The first speaker, Hadar Lev-Tov, talked about the rising problem of silver resistance in wound care, and presented published data that show a general bacterial resistance against silver dressings. The next speaker, Cornelia Wiegand, explained the antimicrobial activity in Cutimed Sorbact dressings (Essity) against five top World Health Organization (WHO)-relevant pathogens, for which new antibiotics are urgently needed. The third and final speaker, Ewa Klara Stürmer, presented six case studies showing the use of Cutimed Sorbact to control bacteria and biofilm on hard-to-heal (a term which has replaced ‘chronic’) leg ulcers. These demonstrated the effectiveness of Sorbact when managing such wounds.

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Werner, Liane, Aline Da Silva Argenta, and Felipe Soares. "ANÁLISE DO DESEMPENHO DOS GRÁFICOS DE CONTROLE CUSUM E EWMA: ESTUDO COMPARATIVO COM USO DE SIMULAÇÃO." Cadernos do IME - Série Estatística 47 (October 29, 2020): 17. http://dx.doi.org/10.12957/cadest.0.51576.

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Este trabalho apresenta um estudo comparativo dos gráficos de controle de soma cumulativa (CUSUM) e de médias móveis exponencialmente ponderadas (EWMA). O objetivo principal é o de estudar a influência dos parâmetros de controle de ambos os gráficos no desempenho de detecção de situações fora de controle, definido pelo Average Run Length (ARL). Simulações computacionais são efetuadas considerando diversos cenários, alterando os parâmetros das cartas de controle e também os parâmetros do processo, investigando o ARL. Verificou-se que o CUSUM obteve desempenho superior ao EWMA para pequenas alterações na média, até um desvio padrão do processo, enquanto o EWMA mostrou-se mais eficaz para alterações de maior magnitude. Além disso, foi verificado que o EWMA é superior quando há alterações simultâneas na média do processo e na sua variabilidade. As rotinas de simulação provaram-se úteis para estudar o comportamento do ARL de acordo com os parâmetros das cartas de controle e dos processos, sendo uma abordagem válida para o estudo e escolha dos parâmetros em aplicações reais.

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Werner, Liane, Aline Da Silva Argenta, and Felipe Soares. "ANÁLISE DO DESEMPENHO DOS GRÁFICOS DE CONTROLE CUSUM E EWMA: ESTUDO COMPARATIVO COM USO DE SIMULAÇÃO." Cadernos do IME - Série Estatística 47 (October 29, 2020): 17. http://dx.doi.org/10.12957/cadest.2019.51576.

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Este trabalho apresenta um estudo comparativo dos gráficos de controle de soma cumulativa (CUSUM) e de médias móveis exponencialmente ponderadas (EWMA). O objetivo principal é o de estudar a influência dos parâmetros de controle de ambos os gráficos no desempenho de detecção de situações fora de controle, definido pelo Average Run Length (ARL). Simulações computacionais são efetuadas considerando diversos cenários, alterando os parâmetros das cartas de controle e também os parâmetros do processo, investigando o ARL. Verificou-se que o CUSUM obteve desempenho superior ao EWMA para pequenas alterações na média, até um desvio padrão do processo, enquanto o EWMA mostrou-se mais eficaz para alterações de maior magnitude. Além disso, foi verificado que o EWMA é superior quando há alterações simultâneas na média do processo e na sua variabilidade. As rotinas de simulação provaram-se úteis para estudar o comportamento do ARL de acordo com os parâmetros das cartas de controle e dos processos, sendo uma abordagem válida para o estudo e escolha dos parâmetros em aplicações reais.

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Engler, J., K. H. Tölle, H. H. Timm, E. Hohls, and J. Krieter. "Control charts applied to pig farming data." Archives Animal Breeding 52, no. 3 (October 10, 2009): 272–83. http://dx.doi.org/10.5194/aab-52-272-2009.

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Abstract. Statistical control charts are effective tools to reveal changes in a production process. The CUSUM (cumulative sum) and the EWMA (exponentially weighted moving average) control chart are used to detect small deviations in a process. Data from two sow herds, herd A and herd B, were collected from 1999 to 2004. Farm A had an average number of 530 breeding sows, Farm B had an average of 370 breeding sows. Both herds were diagnosed with Porcine Reproductive and Respiratory Syndrome (PRRS). The weekly means of the number of piglets weaned (NPW), the pre-weaning mortality (PWM) and return to service rate (RSR) were analysed with different settings of the CUSUM as well as the EWMA control chart to reveal a shift in the production process. For the pre-weaning mortality and the number of piglets weaned, the two charts detected a change in the process 4 weeks (Farm A) and 2 weeks before (Farm B) PRRS was diagnosed. The CUSUM and the EWMA chart revealed a shift in the return to service rate on Farm A 3.5 months before PRRS was detected. On Farm B, the signal occurred 6 weeks before the infection was detected. The CUSUM and the EWMA control charts were effective tools for detecting small deviations in sow herd data. Compared with EWMA, the use of the CUSUM chart is more straightforward and the settings are more easily handled. The CUSUM chart is therefore the preferred option for use in practice.

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SHEU, SHEY-HUEI, and SHIN-LI LU. "MONITORING AUTOCORRELATED PROCESS MEAN AND VARIANCE USING A GWMA CHART BASED ON RESIDUALS." Asia-Pacific Journal of Operational Research 25, no. 06 (December 2008): 781–92. http://dx.doi.org/10.1142/s0217595908002012.

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This investigation elucidates the feasibility of monitoring a process for which observational data are largely autocorrelated. Special causes typically affect not only the process mean but also the process variance. The EWMA control chart has recently been developed and adopted to detect small shifts in the process mean and/or variance. This work extends the EWMA control chart, called the generally weighted moving average (GWMA) control chart, to monitor a process in which the observations can be regarded as a first-order autoregressive process with a random error. The EWMA and GWMA control charts of residuals used to monitor process variability and to monitor simultaneously the process mean and variance are considered to evaluate how average run lengths (ARLs) differ in each case.

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Ikpotokin, O., J. O. Braimah, and H. E. Oboh. "Performance evaluation of conventional exponentially weighted moving average (EWMA) and p-value cumulative sum (CUSUM) control chart." Global Journal of Pure and Applied Sciences 27, no. 2 (June 24, 2021): 171–79. http://dx.doi.org/10.4314/gjpas.v27i2.9.

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This paper is aimed at comparing the performances of the conventional Exponentially Weighted Moving Average (EWMA) and p-value Cumulative Sum (CUSUM) control chart. These charts were applied in monitoring the outbreak of pulmonary tuberculosis in Delta State University Teaching Hospital (DELSUTH), Oghara for a period of eighty four (84) calendar months. Line chart and histogram were plotted to test for stationary and normality of the data. Autocorrelation plot was also used to study the randomness of the data. The results of the control charts show that conventional EWMA chart detects shifts faster in monitoring process mean than the p-value CUSUM control chart. Keywords and Phrases: Exponentially Weighted Moving Average (EWMA), p-value, Cumulative Sum (CUSUM), Autocorrelation, Randomness

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You, Huay Woon, Michael Khoo Boon Chong, Chong Zhi Lin, and Teoh Wei Lin. "The Expected Average Run Length of the EWMA Median Chart with Estimated Process Parameters." Austrian Journal of Statistics 49, no. 3 (February 20, 2020): 19–24. http://dx.doi.org/10.17713/ajs.v49i3.1020.

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The performance of a control chart is commonly investigated based on the assumption of known process parameters. Nevertheless, in most manufacturing and service applications, the process parameters are usually unknown to practitioners. Hence, they are estimated from an in-control Phase-I samples. As such, the performance of the control chart with estimated process parameters will behave differently from the corresponding chart with known process parameters. To study this issue, the exponentially weighted moving average (EWMA) median chart is examined in this article. The EWMA median chart is traditionally investigated based on the average run length (ARL). The limitation of the ARL is that it requires practitioners to specify the shift size in advance. This phenomenon is not ideal for practitioners who do not have background knowledge of the process. In view of this, the EWMA median chart with known and estimated process parameters is studied based on the ARL and expected average run length (EARL). The results indicate that as long as the particular shift size is within the range of shifts, the performance of the chart is almost the same, for the EWMA median chart with known and estimated process parameters.

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Aslam, Muhammad, Srinivasa Rao Gadde, Mansour Sattam Aldosari, and Chi-Hyuck Jun. "A hybrid EWMA chart using coefficient of variation." International Journal of Quality & Reliability Management 36, no. 4 (April 1, 2019): 587–600. http://dx.doi.org/10.1108/ijqrm-12-2017-0285.

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Purpose The purpose of this paper is to develop a new control chart using two EWMA statistics called the hybrid exponentially weighted moving average (HEWMA) chart to improve the sensitivity of EWMA chart proposed by Zhang et al. (2014). When mean and variance of process are not constants, the use of control chart using coefficient of variation (CV) is a successful approach. Design/methodology/approach The control chart using EWMA statistics has ability to detect moderate and small shifts in the process. The authors present the designing of the proposed HEWMA statistics control chart called the HEWMACV chart based on two hybrid EWMA (HEWMA) statistics. The proposed control chart utilizes the current information and previous information to make decision about the state of control chart. Findings In this paper, the authors will present the designing of HEWMA statistics control chart called the HEWMACV chart. The efficiency of the proposed control chart is shown using the simulated data and real data from the industry. The application of proposed chart on the real data shows that the proposed chart has ability to detect shift in the process and it is superior than existing chart in terms of average run length (ARL). Research limitations/implications The design and implementation of the proposed control chart on a real data shows that it can be applied in several industries, such as chemical industry, biological assays, etc. Practical implications The practical application of HEWMA chart using coefficient variation is gaining extensive adequacy. The design and implementation of the HEWMA chart offers a new approach in the detection of small process mean shift. Originality/value In practice, when mean and variance of process are not constants, the use of control chart using CV is a successful approach. In this paper, the authors designed a new control chart using two EWMA statistics called the HEWMA chart to improve the sensitivity of EWMA chart. The comparison shows that the proposed chart is superior than the existing chart in terms of ARL.

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Kang, Hae Woon, Chang Wook Kang, Jae Won Baik, and Sung Ho Nam. "Demerit-GWMA Control Chart for Demerit Statistics." Advanced Materials Research 156-157 (October 2010): 413–21. http://dx.doi.org/10.4028/www.scientific.net/amr.156-157.413.

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A classical Demerit control chart is used to monitor the process through which various types of defects in complex products, such as automobiles, computers, mobile phones, etc. are found in general. As a technique for rapidly detecting small shifts of the process mean in the control chart, the EWMA(exponentially weighted moving average) technique is very effective. This study suggested the Demerit-GWMA control chart, combining the GWMA(generally weighted moving average) technique, which shows better performance than EWMA technique in detecting small shifts of process mean, into the classical Demerit control chart, and evaluated its performance. Through the evaluation of its performance, it was found that the Demerit-GWMA control chart is more sensitive than both the classical Demerit control chart and the Demerit-EWMA control chart in detecting small shifts of process mean.

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Cisar, Petar, Saša Bošnjak, and Sanja Maravic Cisar. "EWMA Algorithm in Network Practice." International Journal of Computers Communications & Control 5, no. 2 (June 1, 2010): 160. http://dx.doi.org/10.15837/ijccc.2010.2.2471.

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Intrusion detection is used to monitor and capture intrusions into computer and network systems which attempt to compromise their security. Many intrusions manifest in changes in the intensity of events occuring in computer networks. Because of the ability of exponentially weighted moving average (EWMA) control charts to monitor the rate of occurrences of events based on their intensity, this technique is appropriate for implementation in control limits based algorithms. The paper also gives a review of a possible optimization method. The validation check of results will be performed on authentic network samples.

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Bohn Stafleu van Loghum. "4 Vragen over: De EWMA." Nursing 23, no. 9 (August 28, 2017): 51. http://dx.doi.org/10.1007/s41193-017-0139-1.

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Holloway, Samantha. "Patients-Wounds-Rights: EWMA 2016." British Journal of Community Nursing 21, Sup6 (June 2016): S5. http://dx.doi.org/10.12968/bjcn.2016.21.sup6.s5.

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Clasie, Benjamin M., Hanne M. Kooy, and Jacob B. Flanz. "PBS machine interlocks using EWMA." Physics in Medicine and Biology 61, no. 1 (December 16, 2015): 400–412. http://dx.doi.org/10.1088/0031-9155/61/1/400.

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Amin, Raid W., and Kuiyuan Li. "The MaxMin EWMA tolerance limits." International Journal of Quality & Reliability Management 17, no. 1 (February 2000): 27–41. http://dx.doi.org/10.1108/02656710010283351.

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Flanagan, M. "The EWMA educational development project." Journal of Tissue Viability 15, no. 1 (January 2005): 21–22. http://dx.doi.org/10.1016/s0965-206x(05)51013-1.

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Zhang, Lingyun, and Gemai Chen. "An Extended EWMA Mean Chart." Quality Technology & Quantitative Management 2, no. 1 (January 2005): 39–52. http://dx.doi.org/10.1080/16843703.2005.11673088.

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Gottrup, F. "The EWMA Patient Outcome Group." Journal of Wound Care 18, no. 11 (November 2009): 460. http://dx.doi.org/10.12968/jowc.2009.18.11.44986.

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Maravelakis, Petros, John Panaretos, and Stelios Psarakis. "EWMA Chart and Measurement Error." Journal of Applied Statistics 31, no. 4 (May 2004): 445–55. http://dx.doi.org/10.1080/02664760410001681738.

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Haq, Abdul, and Michael B. C. Khoo. "An adaptive multivariate EWMA chart." Computers & Industrial Engineering 127 (January 2019): 549–57. http://dx.doi.org/10.1016/j.cie.2018.10.040.

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Khan, Hina, Saleh Farooq, Muhammad Aslam, and Masood Amjad Khan. "Exponentially Weighted Moving Average Control Charts for the Process Mean Using Exponential Ratio Type Estimator." Journal of Probability and Statistics 2018 (October 1, 2018): 1–15. http://dx.doi.org/10.1155/2018/9413939.

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This study proposes EWMA-type control charts by considering some auxiliary information. The ratio estimation technique for the mean with ranked set sampling design is used in designing the control structure of the proposed charts. We have developed EWMA control charts using two exponential ratio-type estimators based on ranked set sampling for the process mean to obtain specific ARLs, being suitable when small process shifts are of interest.

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Baker, Arthur W., Salah Haridy, Joseph Salem, Iulian Ilieş, Awatef O. Ergai, Aven Samareh, Nicholas Andrianas, James C. Benneyan, Daniel J. Sexton, and Deverick J. Anderson. "Performance of statistical process control methods for regional surgical site infection surveillance: a 10-year multicentre pilot study." BMJ Quality & Safety 27, no. 8 (November 24, 2017): 600–610. http://dx.doi.org/10.1136/bmjqs-2017-006474.

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BackgroundTraditional strategies for surveillance of surgical site infections (SSI) have multiple limitations, including delayed and incomplete outbreak detection. Statistical process control (SPC) methods address these deficiencies by combining longitudinal analysis with graphical presentation of data.MethodsWe performed a pilot study within a large network of community hospitals to evaluate performance of SPC methods for detecting SSI outbreaks. We applied conventional Shewhart and exponentially weighted moving average (EWMA) SPC charts to 10 previously investigated SSI outbreaks that occurred from 2003 to 2013. We compared the results of SPC surveillance to the results of traditional SSI surveillance methods. Then, we analysed the performance of modified SPC charts constructed with different outbreak detection rules, EWMA smoothing factors and baseline SSI rate calculations.ResultsConventional Shewhart and EWMA SPC charts both detected 8 of the 10 SSI outbreaks analysed, in each case prior to the date of traditional detection. Among detected outbreaks, conventional Shewhart chart detection occurred a median of 12 months prior to outbreak onset and 22 months prior to traditional detection. Conventional EWMA chart detection occurred a median of 7months prior to outbreak onset and 14 months prior to traditional detection. Modified Shewhart and EWMA charts additionally detected several outbreaks earlier than conventional SPC charts. Shewhart and SPC charts had low false-positive rates when used to analyse separate control hospital SSI data.ConclusionsOur findings illustrate the potential usefulness and feasibility of real-time SPC surveillance of SSI to rapidly identify outbreaks and improve patient safety. Further study is needed to optimise SPC chart selection and calculation, statistical outbreak detection rules and the process for reacting to signals of potential outbreaks.

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Patev, Plamen, Nigokhos Kanaryan, and Katerina Lyroudi. "Modelling and Forecasting the Volatility of Thin Emerging Stock Markets: the Case of Bulgaria." Comparative Economic Research. Central and Eastern Europe 12, no. 4 (December 30, 2009): 47–60. http://dx.doi.org/10.2478/v10103-009-0021-8.

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Modern Portfolio Theory associates the stock market risk with the volatility of return. Volatility is measured by the variance of the returns’ distribution. However, the investment community does not accept this measure, since it weights equally deviations of the average returns, whereas most investors determine the risk on the basis of small or negative returns. In the last few years the measure Value at Risk (VaR) has been established and adopted widely by practitioners. The issue of modelling and forecasting thin emerging stock markets’ risk is still open. The subject of this present paper is the risk of the Bulgarian stock market. The aim of this research is to give the investment community a model for assessing and forecasting the Bulgarian stock market risk. The result of this research shows that the SOFIX index has basic characteristics that are observed in most of the emerging stock markets, namely: high risk, significant autocorrelation, non-normality and volatility clustering. Three models have been applied to assess and estimate the Bulgarian stock market risk: RiskMetrics, EWMA with t-distributed innovations and EWMA with GED distributed innovations. The results revealed that the EWMA with t-distributed innovations and the EWMA with GED distributed innovations evaluate the risk of the Bulgarian stock market adequately.

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Journal articles on the topic 'EWMA'

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