Functional Covariance Estimation
Functional Covariance Estimation is a statistical method that characterizes the second-order dependence structure of functional time series by estimating the covariance operator between random functions observed over time, distinguishing it from multivariate or scalar covariance estimation through its treatment of infinite-dimensional functional observations and temporal dependencies.
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4.6K
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108
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2017–2026
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Weakly dependent functional data
Siegfried Hörmann, Piotr Kokoszka · The Annals of Statistics · 2010 · 362 citations · Full text
Hans‐Georg Müller, Fang Yao · Journal of the American Statistical Association · 2008 · 245 citations
STATISTICAL INFERENCES FOR FUNCTIONAL DATA
2004 · 234 citations
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University of California, Davis
Davis, United States
6 h-index
9 publications
2.1K citations
National University of Singapore
Singapore, Singapore
5 h-index
7 publications
521 citations
University of Pennsylvania
Philadelphia, United States
3 h-index
6 publications
177 citations
Université Libre de Bruxelles
Brussels, Belgium
3 h-index
4 publications
421 citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
3 publications
50 citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
2 h-index
3 publications
187 citations
University of California, Irvine
Irvine, United States
2 h-index
3 publications
219 citations

The University of Melbourne
Melbourne, Australia
2 h-index
4 publications
91 citations
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8 publications · 2.4K citations
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CSDA · 2 publications · 45 citations
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