Functional Data Interpolation
Functional Data Interpolation is a functional data analysis technique that belongs to the class of methods for reconstructing continuous functions from discrete observations, distinguished by its specific focus on estimating unobserved segments of a functional trajectory while preserving the inherent smoothness and structure of the underlying stochastic process.
11
Publications
316
Citations
37
Authors
26
Institutions
Publications per year
2017–2026
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11
Support vector regression for functional data in multivariate calibration problems
Noslen Hernández, Isneri Talavera, R. Biscay et al. · Analytica Chimica Acta · 2008 · 27 citations · Full text
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Advanced Technologies Application Center
Havana, Cuba
1 h-index
3 publications
81 citations
Universidad Nacional de Colombia
Bogotá, Colombia
1 h-index
1 publications
76 citations

Andrássy University Budapest
Budapest, Hungary
1 h-index
3 publications
63 citations
Politecnico di Milano
Milan, Italy
1 h-index
1 publications
25 citations

Universidad de Oriente
Santiago de Cuba, Cuba
1 h-index
1 publications
27 citations

Universidade Estadual de Campinas (UNICAMP)
Campinas, Brazil
1 h-index
1 publications
27 citations
Northern University of Malaysia
Jitra, Malaysia
1 h-index
1 publications
22 citations

Ton Duc Thang University
Ho Chi Minh City, Vietnam
1 h-index
1 publications
22 citations
1–8 of 26
2 publications · 86 citations
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Repository · 1 publications · 13 citations
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1 publications · 27 citations
1
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1 publications · 76 citations
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CSSP · 1 publications · 15 citations
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