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Functional Data Analysis in Sport Science: Example of Swimmers’ Progression Curves Clustering
- Source :
- Applied Sciences, Volume 8, Issue 10, Applied Sciences, MDPI, 2018, 8 (10), pp.1766. ⟨10.3390/app8101766⟩, Applied Sciences, Vol 8, Iss 10, p 1766 (2018)
- Publication Year :
- 2018
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2018.
-
Abstract
- International audience; Many data collected in sport science come from time dependent phenomenon. This article focuses on Functional Data Analysis (FDA), which study longitudinal data by modeling them as continuous functions. After a brief review of several FDA methods, some useful practical tools such as Functional Principal Component Analysis (FPCA) or functional clustering algorithms are presented and compared on simulated data. Finally, the problem of the detection of promising young swimmers is addressed through a curve clustering procedure on a real data set of performance progression curves. This study reveals that the fastest improvement of young swimmers generally appears before 16 years old. Moreover, several patterns of improvement are identied and the functional clustering procedure provides a useful detection tool.
- Subjects :
- Computer science
Longitudinal data
Sports science
detection
computer.software_genre
01 natural sciences
lcsh:Technology
lcsh:Chemistry
010104 statistics & probability
03 medical and health sciences
0302 clinical medicine
General Materials Science
0101 mathematics
swimming
Cluster analysis
Instrumentation
lcsh:QH301-705.5
functional data analysis
Fluid Flow and Transfer Processes
Functional principal component analysis
[STAT.AP]Statistics [stat]/Applications [stat.AP]
lcsh:T
Process Chemistry and Technology
General Engineering
Functional data analysis
030229 sport sciences
curve clustering
lcsh:QC1-999
Computer Science Applications
Data set
lcsh:Biology (General)
lcsh:QD1-999
lcsh:TA1-2040
Simulated data
Data mining
lcsh:Engineering (General). Civil engineering (General)
sport
computer
lcsh:Physics
Subjects
Details
- Language :
- English
- ISSN :
- 20763417
- Database :
- OpenAIRE
- Journal :
- Applied Sciences
- Accession number :
- edsair.doi.dedup.....e6e013bd57fa89008d2824961f6da6bc
- Full Text :
- https://doi.org/10.3390/app8101766