Open Access
2014 Analysis of juggling data: An application of $k$-mean alignment
Mara Bernardi, Laura M. Sangalli, Piercesare Secchi, Simone Vantini
Electron. J. Statist. 8(2): 1817-1824 (2014). DOI: 10.1214/14-EJS937A


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.


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Mara Bernardi. Laura M. Sangalli. Piercesare Secchi. Simone Vantini. "Analysis of juggling data: An application of $k$-mean alignment." Electron. J. Statist. 8 (2) 1817 - 1824, 2014.


Published: 2014
First available in Project Euclid: 29 October 2014

zbMATH: 1305.62012
MathSciNet: MR3273600
Digital Object Identifier: 10.1214/14-EJS937A

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

Rights: Copyright © 2014 The Institute of Mathematical Statistics and the Bernoulli Society

Vol.8 • No. 2 • 2014
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