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Theory and Methods
Anomaly Detection for a Large Number of Streams: A Permutation-Based Higher Criticism Approach
Ivo V. Stoepkera Department of Mathematics and Computer Science, Technische Universiteit Eindhoven, Eindhoven, The NetherlandsCorrespondence[email protected]
https://orcid.org/0000-0001-9579-7259
Rui M. Castroa Department of Mathematics and Computer Science, Technische Universiteit Eindhoven, Eindhoven, The Netherlands
https://orcid.org/0000-0003-4398-0718
Ery Arias-Castrob Department of Mathematics and Hal ic ioğlu Data Science Institute, University of California, San Diego, La Jolla, CA, USA
& Edwin van den Heuvela Department of Mathematics and Computer Science, Technische Universiteit Eindhoven, Eindhoven, The Netherlands
https://orcid.org/0000-0001-9157-7224
Pages 461-474
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Received 02 Nov 2020, Accepted 15 Sep 2022, Published online: 16 Nov 2022
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