Adaptive threshold computation for CUSUM-type procedures in change detection and isolation problems
| Autor: | Jean-Pierre Vila, Nadine Hilgert, Ghislain Verdier |
|---|---|
| Přispěvatelé: | Analyse des Systèmes et Biométrie (ASB), Institut National de la Recherche Agronomique (INRA) |
| Rok vydání: | 2008 |
| Předmět: |
Statistics and Probability
Supervisor Applied Mathematics [INFO.INFO-OH]Computer Science [cs]/Other [cs.OH] Order statistic CUSUM DYNAMIC SYSTEM ALGORYTHM PROBABILITY QUALITY CONTROL FAULT DETECTION CONTROL SYSTEM ARTIFICIAL INTELLIGENCE ROBOTIC ROBOTIQUE CONTROLE DE QUALITE INTELLIGENCE ARTIFICIELLE Computational Mathematics Computational Theory and Mathematics Test statistic Probability distribution False alarm Algorithm Change detection Statistical hypothesis testing Mathematics |
| Zdroj: | Computational Statistics and Data Analysis Computational Statistics and Data Analysis, Elsevier, 2008, 52 (9), pp.4161-4174. ⟨10.1016/j.csda.2008.01.026⟩ |
| ISSN: | 0167-9473 |
| Popis: | aeres : ACL; International audience; Statistical methods dealing with change detection and isolation in dynamical systems are based on algorithms deriving from hypothesis testing. As for any statistical test, the problem of threshold choice has to be addressed by taking into account the constraints fixed by the supervisors and the nonstationary nature of the stochastic systems under supervision. A procedure for obtaining adaptive thresholds in change detection or diagnosis algorithms of CUSUM-type rules is proposed. This procedure is carried out through a large number of simulations. The advantage of such an adaptive threshold, when compared with a fixed threshold, is its adaptation to the time evolution of the probability distribution of the test statistic, in order to guarantee constant rates of false alarm or false diagnosis, fixed by the supervisor. |
| Databáze: | OpenAIRE |
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