data("runs", package = "trackeR")
dp <- distributionProfile(runs, what = "speed")
dp.pca <- funPCA(dp, what = "speed", nharm = 4)
## 1st harmonic captures vast majority of the variation
plot(dp.pca)
plot(dp.pca, harm = 1, pointplot = FALSE)
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