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trackeR (version 0.0.3)

plot.trackeRfpca: Plot function for functional principal components analysis of distribution and concentration profiles.

Description

Plot function for functional principal components analysis of distribution and concentration profiles.

Usage

"plot"(x, harm = NULL, expand = NULL, pointplot = TRUE, ...)

Arguments

x
An object of class trackeRfpca as returned by funPCA.
harm
A numerical vector of the harmonics to be plotted. Defaults to all harmonics.
expand
The factor used to generate suitable multiples of the harmonics. If NULL, the effect of +/- 2 standard deviations of each harmonic is plotted.
pointplot
Should the harmonics be plotted with + and - point characters? Otherwise, lines are used.
...
Currently not used.

References

Ramsay JO, Silverman BW (2005). Functional Data Analysis. Springer-Verlag New York.

See Also

plot.pca.fd

Examples

Run this code
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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