Description Usage Arguments Details Value References Examples
Functional principal components analysis of distribution or concentration profiles.
Generic function for functional principal components analysis
1 2 3 4 5 6 7 |
object |
The object to which a functional principal components analysis is applied. |
what |
The variable for which the profiles should be analysed. |
nharm |
The number of principal components estimated. |
... |
Arguments to be passed to methods. |
The ...
argument is passed on to pca.fd
.
An object of class trackeRfpca
.
Ramsay JO, Silverman BW (2005). Functional Data Analysis. Springer-Verlag New York.
1 2 3 4 5 6 7 8 9 10 11 | ## Not run:
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, harm = 1)
## time spent above speed = 0 is the characteristic distinguishing the profiles
sumRuns <- summary(runs)
plot(sumRuns$durationMoving, dp.pca$scores[,1])
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.