Functional Outlier Detection
Functional Outlier Detection is a statistical methodology within functional data analysis that identifies observations whose functional patterns deviate significantly from the majority in a sample of curves, surfaces, or functions, thereby distinguishing them from typical functional data structures.
76
Publications
5.6K
Citations
149
Authors
105
Institutions
Publications per year
2017–2026
34
76
Ying Sun, Marc G. Genton · Journal of Computational and Graphical Statistics · 2011 · 417 citations
Functional data clustering: a survey
Julien Jacques, Cristian Preda · Advances in Data Analysis and Classification · 2013 · 400 citations · Full text
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149
King Abdullah University of Science and Technology, Saudi Arabia
7 publications · 742 citations
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6
h-index
King Abdullah University of Science and Technology, Saudi Arabia
5 publications · 628 citations
5
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King Abdullah University of Science and Technology, Saudi Arabia
5 publications · 235 citations
5
h-index
4
h-index
1–5 of 149
105

King Abdullah University of Science and Technology
Jeddah, Saudi Arabia
7 h-index
12 publications
538 citations

Universidad Carlos III de Madrid
Madrid, Spain
7 h-index
15 publications
1.8K citations

Universidade de Vigo
Vigo, Spain
6 h-index
15 publications
461 citations
KU Leuven
Leuven, Belgium
5 h-index
11 publications
1.2K citations
Centro Universitario de la Defensa en San Javier
San Javier, Spain
5 h-index
12 publications
374 citations

Universidad de Oviedo
Oviedo, Spain
4 h-index
4 publications
174 citations
Universidade de Santiago de Compostela
Santiago de Compostela, Spain
4 h-index
8 publications
1.4K citations
Politecnico di Milano
Milan, Italy
3 h-index
6 publications
188 citations
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JCGS · 6 publications · 901 citations
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5 publications · 161 citations
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4 publications · 170 citations
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4 publications · 356 citations
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CSDA · 4 publications · 240 citations
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