Electronic Journal of Statistics

Analysis of juggling data: An application of $k$-mean alignment

Mara Bernardi, Laura M. Sangalli, Piercesare Secchi, and Simone Vantini

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Abstract

We analyze the juggling data by means of the $k$-mean alignment algorithm using cycles as the experimental units of the analysis. Allowing for affine warping, we detect two clusters distinguishing between mainly-planar trajectories and trajectories tilted toward the body of the juggler in the lower part of the cycle. In particular we detect an anomalous presence of tilted trajectories among the trial third cycles. We also find warping functions to be clustered according to trials suggesting that each trial is performed at a different pace and thus associated to a different typical cycle-duration.

Article information

Source
Electron. J. Statist., Volume 8, Number 2 (2014), 1817-1824.

Dates
First available in Project Euclid: 29 October 2014

Permanent link to this document
https://projecteuclid.org/euclid.ejs/1414588168

Digital Object Identifier
doi:10.1214/14-EJS937A

Mathematical Reviews number (MathSciNet)
MR3273600

Zentralblatt MATH identifier
1305.62012

Keywords
$k$-mean alignment registration functional clustering juggling data

Citation

Bernardi, Mara; Sangalli, Laura M.; Secchi, Piercesare; Vantini, Simone. Analysis of juggling data: An application of $k$-mean alignment. Electron. J. Statist. 8 (2014), no. 2, 1817--1824. doi:10.1214/14-EJS937A. https://projecteuclid.org/euclid.ejs/1414588168


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References

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See also

  • Related item: Ramsay, J. O., Gribble, P., and Kurtek, S. (2014). Description and processing of functional data arising from juggling trajectories. Electron. J. Statist. 8 1811–1816.