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- Title
A Bayesian approach to diagnosing covariance matrix shifts.
- Authors
Wang, Binhui; Xu, Feng; Shu, Lianjie
- Abstract
In addition to the quick detection of abnormal changes in a multivariate process, it is also critical to provide an accurate fault identification of responsible components following an out‐of‐control signal. In line with the work of Tan and Shi for diagnosing shifts in the mean vector, this paper develops a Bayesian approach for diagnosing shifts in the covariance matrix. The simulation comparisons favor the proposed approach. A real example is also presented to demonstrate the implementation of the proposed method.
- Subjects
COVARIANCE matrices; STATISTICAL process control; MIMO radar; GIBBS sampling
- Publication
Quality & Reliability Engineering International, 2020, Vol 36, Issue 2, p736
- ISSN
0748-8017
- Publication type
Article
- DOI
10.1002/qre.2601