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Erschienen in:
Optimal Weighted Wilcoxon–Mann–Whitney Test for Prioritized Outcomes Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

6. Wavelet-Based Profile Monitoring Using Order-Thresholding Recursive CUSUM Schemes

verfasst von : Ruizhi Zhang, Yajun Mei, Jianjun Shi

Erschienen in: New Frontiers of Biostatistics and Bioinformatics

Verlag: Springer International Publishing

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Abstract

With the rapid development of advanced sensing technologies, rich and complex real-time profile or curve data are available in many processes in biomedical sciences and manufacturing. These profile data provide valuable intrinsic information about the performance or properties of the process, subject, or product, and it is often desirable to utilize them to develop efficient methodologies for process monitoring and fault diagnosing. In this article, we propose a novel wavelet-based profile monitoring procedure that is based on the order-thresholding transformation of recursive CUSUM statistics of multiple wavelet coefficients. Extensive simulation studies and a case study of tonnage profile data demonstrate that our proposed procedure is efficient for detecting the unknown local changes on the profile.

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Vorheriges Kapitel Mammogram Diagnostics Using Robust Wavelet-Based Estimator of Hurst Exponent
Nächstes Kapitel Estimating the Confidence Interval of Evolutionary Stochastic Process Mean from Wavelet Based Bootstrapping
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Metadaten
Titel
Wavelet-Based Profile Monitoring Using Order-Thresholding Recursive CUSUM Schemes
verfasst von
Ruizhi Zhang
Yajun Mei
Jianjun Shi
Copyright-Jahr
2018
Buch
New Frontiers of Biostatistics and Bioinformatics

Print ISBN: 978-3-319-99388-1

Electronic ISBN: 978-3-319-99389-8

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-99389-8_6