Nonlinear profile monitoring with single index models
We consider change‐point detection and estimation in sequences of functional observations. This setting often arises when the quality of a process is characterized by such observations, called profiles, and monitoring profiles for changes in structure can be used to ensure the stability of the proce...
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Veröffentlicht in: | Quality and reliability engineering international 2021-11, Vol.37 (7), p.3004-3017 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | We consider change‐point detection and estimation in sequences of functional observations. This setting often arises when the quality of a process is characterized by such observations, called profiles, and monitoring profiles for changes in structure can be used to ensure the stability of the process over time. We propose a nonparametric approach using a single index model (SIM), where instead of monitoring the profile itself for a change, we monitor an l2‐based statistic on the coefficients generated by the SIM. Through simulation we show our novel method outperforms existing multivariate profile monitoring methods. |
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ISSN: | 0748-8017 1099-1638 |
DOI: | 10.1002/qre.2825 |