trackeR (version 1.5.2)

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

# S3 method for trackeRfpca
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

if (FALSE) {
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)
}