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Erschienen in:
Phase I Distribution-Free Analysis with the R Package dfphase1 Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Monitoring of Short Series of Dependent Observations Using a XWAM Control Chart

verfasst von : Olgierd Hryniewicz, Katarzyna Kaczmarek-Majer

Erschienen in: Frontiers in Statistical Quality Control 12

Verlag: Springer International Publishing

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Abstract

Many different control charts have been proposed during the last 30 years for monitoring processes with autocorrelated observations (measurements). The majority of them are developed for monitoring residuals, i.e., differences between the observed and predicted values of the monitored process. Unfortunately, statistical properties of these chart are very sensitive to the accuracy of the estimated model of the underlying process. In this chapter we consider the case when the information from the available data is not sufficient for good estimation of the model. Therefore, we use the concept of model weighted averaging in order to improve model prediction. The novelty of the proposed XWAM control chart consists in the usage of computational intelligence methodology for the construction of alternative models, and the calculation of their weights.

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Vorheriges Kapitel Control Charts for Time-Dependent Categorical Processes
Nächstes Kapitel Challenges in Monitoring Non-stationary Time Series
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Metadaten
Titel
Monitoring of Short Series of Dependent Observations Using a XWAM Control Chart
verfasst von
Olgierd Hryniewicz
Katarzyna Kaczmarek-Majer
Copyright-Jahr
2018
Buch
Frontiers in Statistical Quality Control 12

Print ISBN: 978-3-319-75294-5

Electronic ISBN: 978-3-319-75295-2

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-75295-2_13