Control charts for measurement error models

Golosnoy, Vasyl; Hildebrandt, Benno; Köhler, Steffen; Schmid, Wolfgang; Seifert, Miriam Isabel

doi:10.1007/s10182-022-00462-8

Cited by 2 publications

(2 citation statements)

References 41 publications

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“…The monitoring is commonly visualised using a control chart, where process scores are plotted against time. The EWMA procedure, introduced by Roberts ( 53 ) to detect mean changes across time, was used in this application. The procedure combines past and current information and tracks a weighted sum of the original observations, where more recent observations receive higher weights ( 54 ).…”

Section: Methodsmentioning

confidence: 99%

Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends

Porcu

Chen

Bonaugurio

et al. 2023

Front. Public Health

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IntroductionLarge-scale diagnostic testing has been proven insufficient to promptly monitor the spread of the Coronavirus disease 2019. Electronic resources may provide better insight into the early detection of epidemics. We aimed to retrospectively explore whether the Google search volume has been useful in detecting Severe Acute Respiratory Syndrome Coronavirus outbreaks early compared to the swab-based surveillance system.MethodsThe Google Trends website was used by applying the research to three Italian regions (Lombardy, Marche, and Sicily), covering 16 million Italian citizens. An autoregressive-moving-average model was fitted, and residual charts were plotted to detect outliers in weekly searches of five keywords. Signals that occurred during periods labelled as free from epidemics were used to measure Positive Predictive Values and False Negative Rates in anticipating the epidemic wave occurrence.ResultsSignals from “fever,” “cough,” and “sore throat” showed better performance than those from “loss of smell” and “loss of taste.” More than 80% of true epidemic waves were detected early by the occurrence of at least an outlier signal in Lombardy, although this implies a 20% false alarm signals. Performance was poorer for Sicily and Marche.ConclusionMonitoring the volume of Google searches can be a valuable tool for early detection of respiratory infectious disease outbreaks, particularly in areas with high access to home internet. The inclusion of web-based syndromic keywords is promising as it could facilitate the containment of COVID-19 and perhaps other unknown infectious diseases in the future.

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Section: Methodsmentioning

confidence: 99%

Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends

Porcu

Chen

Bonaugurio

et al. 2023

Front. Public Health

View full text Add to dashboard Cite

show abstract

“…Golosnoy et al [5] suggested using an EWMA control chart for monitoring a linear measurement error model. Mitra et al [6] designed an AEWMA-type control chart without prior knowledge about the shift magnitude.…”

Section: Introductionmentioning

confidence: 99%

Constructing a Sensitive Control Chart to Monitor Process Mean using Optimal Filter: Time-Frequency Analysis Approach

2023

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Control charts are one of the critical tools for process monitoring. Test statistics are computed as a function of sample means in control charts for monitoring the process mean. In this study, these functions are modeled by filters. These filters have essential properties in both time and frequency domains. In previous studies, only their properties in the time domain have been considered. Thus, the resulting filters have sub-optimal performance. This study investigates the optimal design of these filters for monitoring the process mean. The behavior of these filters is analyzed not only in the time domain but also in the frequency domain. Properties such as stability are considered in designing this filter. An optimization model is designed and solved using a Genetic Algorithm to minimize the Average Run Length. The proposed optimal filter is compared with other control charts using simulation studies. Results showed the high speed of the proposed filter in detecting shifts in the process mean. The proposed optimal filter is also used to monitor the oil price of the OPEC basket. The results showed that shifts were detected at the right time using the proposed optimal filter.

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Control charts for measurement error models

Cited by 2 publications

References 41 publications

Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends

Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends

Constructing a Sensitive Control Chart to Monitor Process Mean using Optimal Filter: Time-Frequency Analysis Approach

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