Parametric Change-Point Detection is a statistical methodology for identifying abrupt changes in the distribution of a stochastic process, distinguished by its reliance on explicit parametric assumptions about the underlying data-generating model.
94
Publications
8.2K
Citations
191
Authors
153
Institutions
Publications per year
2017–2026
19
Parents
Publications
94
1–5 of 94
Authors
191
- WN
4
h-index
- GJ
3
h-index
- WB
3
h-index
- VK
3
h-index
- NM
2
h-index
1–5 of 191
Institutions
153
Bowling Green State University
Bowling Green, United States
4 h-index
6 publications
90 citations
Centre National de la Recherche Scientifique
Paris, France
3 h-index
5 publications
290 citations
Imperial College London
London, United Kingdom
3 h-index
3 publications
394 citations
Laboratoire Traitement et Communication de l’Information
Palaiseau, France
2 h-index
4 publications
278 citations
Nanjing University
Nanjing, China
2 h-index
3 publications
36 citations
State Key Laboratory of Remote Sensing Science
Beijing, China
2 h-index
2 publications
54 citations
Western University
London, Canada
2 h-index
2 publications
74 citations
Télécom Paris
Palaiseau, France
2 h-index
4 publications
278 citations
1–8 of 153
Venues
- Communications in Statistics - Simulation and Computation
5 publications · 101 citations
5
h-index
- Communication in Statistics- Theory and Methods
4 publications · 105 citations
4
h-index
- The Annals of Statistics
4 publications · 181 citations
4
h-index
- Statistical Papers
3 publications · 71 citations
3
h-index
- Journal of Applied Statistics
3 publications · 38 citations
3
h-index
1–5