My research focuses on the development of methodologies for the analysis of functional data. I am also interested to apply these methodologies to diverse areas, such as sport science and ecology. Here are a list of my publications, conference proceedings and thesis.
Publications
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Analysing kinematic data from recreational runners using functional data analysis
Edward Gunning, Steven Golovkine, Andrew J. Simpkin, Aoife Burke, Sarah Dillon, Shane Gore, Kieran Moran, Siobhan O'Connor, Enda Whyte and Norma Bargary
Aug. 2024
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A Multivariate Multilevel Longitudinal Functional Model for Repeatedly Observed Human Movement Data
Edward Gunning, Steven Golovkine, Andrew J. Simpkin, Aoife Burke, Sarah Dillon, Shane Gore, Kieran Moran, Siobhan O'Connor, Enda Whyte and Norma Bargary
Aug. 2024
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On the estimation of the number of components in multivariate functional principal components analysis
Steven Golovkine, Edward Gunning, Andrew J. Simpkin and Norma Bargary
Nov. 2023
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Adaptive estimation of irregular mean and covariance functions
Steven Golovkine, Nicolas Klutchnikoff and Valentin Patilea
Jul. 2023
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On the use of the Gram matrix for multivariate functional principal components analysis
Steven Golovkine, Edward Gunning, Andrew J. Simpkin and Norma Bargary
Jun. 2023
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Clustering multivariate functional data using unsupervised binary trees
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Computational Statistics & Data Analysis
Steven Golovkine, Nicolas Klutchnikoff and Valentin Patilea
Apr. 2022
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Learning the smoothness of noisy curves with application to online curve estimation
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Electronic Journal of Statistics
Steven Golovkine, Nicolas Klutchnikoff and Valentin Patilea
Jan. 2022
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FDApy: a Python package for functional data
Steven Golovkine
Jan. 2021
The emojis along the publications refer to:
- link to the journal publication.
- link to the arxiv publication.
- download the bibtex entry for this publication.
- link to the Github repository.
Conference proceedings
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Functional multilevel modeling of the influence of the menstrual cycle on the performance of female cyclists
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37th International Workshop on Statistical Modelling
Steven Golovkine, Tom Chassard, Alice Meignié, Emmanuel Brunet, Jean-François Toussaint and Juliana Antero
Jul. 2023
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Clustering multivariate functional data using unsupervised binary trees
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22nd European Young Statisticians Meeting
Steven Golovkine, Nicolas Klutchnikoff and Valentin Patilea
Sep. 2021
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Lissage de données fonctionnelles par estimation de leur régularité locale
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52èmes Journées de Statistiques de la Société Française de Statistique
Steven Golovkine, Nicolas Klutchnikoff and Valentin Patilea
May. 2020
The emojis along the proceedings refer to:
- link to the proceedings.
- download the bibtex entry for this proceedings.
Thesis
I completed a thesis in Statistics, Applied Mathematics, entitled “Statistical methods for multivariate functional data”. This work was supervised by Valentin Patilea (CREST, link) and Nicolas Klutchnikoff (IRMAR, link) and was realized part at Renault and part at ENSAI.