Point Process Approach
The "Point Process Approach" is a stochastic modeling framework within extreme value theory that characterizes the occurrence of extreme events in continuous space or time by modeling their locations as a point process, distinguished from alternative methods by its ability to jointly model the frequency, magnitude, and spatial or temporal clustering of extremes.
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11.4K
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374
Authors
226
Institutions
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2017–2026
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176
The coincidence approach to stochastic point processes
Odile Macchi · Advances in Applied Probability · 1975 · 590 citations
Engineering, Mathematics, Physics +13
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University of California, Los Angeles
Los Angeles, United States
6 h-index
9 publications
598 citations
Massachusetts General Hospital
Boston, United States
5 h-index
8 publications
1K citations
Columbia University
New York, United States
5 h-index
8 publications
354 citations
Stanford University
Stanford, United States
4 h-index
5 publications
361 citations
Georgia Institute of Technology
Atlanta, United States
4 h-index
15 publications
494 citations
Massachusetts Institute of Technology
Cambridge, United States
4 h-index
8 publications
709 citations
University of Arizona
Tucson, United States
4 h-index
4 publications
84 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
4 h-index
4 publications
600 citations
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AAP · 11 publications · 995 citations
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Repository · 6 publications · 135 citations
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3 publications · 99 citations
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3 publications · 70 citations
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3 publications · 148 citations
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