Analysis of Juggling Data: an Application of K-mean Alignment
Keywords
Statistical learning
Code:
42/2013
Title:
Analysis of Juggling Data: an Application of K-mean Alignment
Date:
Saturday 5th October 2013
Author(s):
Bernardi, M.; Sangalli, L.M.; Secchi, P.; Vantini, S.
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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 record third cycles. We also find warping functions to be clustered according to records suggesting that each record is performed at a di fferent pace and thus associated to a diff erent typical cycle-duration.
This report, or a modified version of it, has been also submitted to, or published on
Mara Bernardi, Laura M. Sangalli, Piercesare Secchi, Simone Vantini (2014), Analysis of Juggling Data: an Application of K-mean Alignment, Electronic Journal of Statistics, Special Section on "Statistics of Time Warpings and Phase Variations", Vol. 8, No. 2, 1817-1824.
Mara Bernardi, Laura M. Sangalli, Piercesare Secchi, Simone Vantini (2014), Analysis of Juggling Data: an Application of K-mean Alignment, Electronic Journal of Statistics, Special Section on "Statistics of Time Warpings and Phase Variations", Vol. 8, No. 2, 1817-1824.