Sequential Change-point Detection
Sequential Change-Point Detection is a statistical inference method that sequentially tests observed data streams to identify the point at which the underlying distribution of a stochastic process undergoes an abrupt change, distinguishing it from other sequential analysis techniques by its focus on detecting distributional shifts in real time.
197
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10.8K
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365
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211
Institutions
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2017–2026
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Inference about the change-point from cumulative sum tests
D. V. Hinkley · Biometrika · 1971 · 444 citations
1–5 of 197
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University of Southern California, United States
11 publications · 896 citations
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University of Southern California
Los Angeles, United States
11 h-index
22 publications
2.3K citations
Stanford University
Stanford, United States
11 h-index
12 publications
1.4K citations
Georgia Institute of Technology
Atlanta, United States
7 h-index
17 publications
467 citations
University of Illinois Urbana-Champaign
Urbana, United States
5 h-index
9 publications
210 citations
University of Utah
Salt Lake City, United States
5 h-index
6 publications
318 citations

University of Cologne
Cologne, Germany
5 h-index
5 publications
184 citations
University of Connecticut
Storrs, United States
5 h-index
6 publications
629 citations
Hebrew University of Jerusalem
Jerusalem, Israel
5 h-index
6 publications
168 citations
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14 publications · 1.1K citations
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14 publications · 502 citations
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9 publications · 297 citations
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7 publications · 394 citations
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Repository · 6 publications · 81 citations
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