SVDplot {rainbow} | R Documentation |
The singular value decomposition (SVD) plot of Zhang et al. (2007) captures the changes in the singular columns as the number of curves gradually increases. Similarly, it also captures the changes in the singular rows as the number of covariates gradually increases.
SVDplot(object, order = 1, center = c("rowwise", "colwise", "double"), plot = TRUE)
object |
An object of fds . |
order |
Number of SVD components. The maximum order is 4. |
center |
Methods of removing functional mean. When center = "double" , the functional mean is determined
as: colmean(data) + rowmean(data) - mean(data) |
plot |
Is graphical display required? |
By using the SVD, Zhang et al. (2007) proposed a dynamic plot for visualizing patterns
of functional time series. They considered a set of curves as a two-way (p * n)
data matrix, where p
is the total number of covariates and n
is the total number of curves.
The main advantage of this dynamic plot is to visualize both column and row information of a two-way matrix simultaneously, relate the matrix to the corresponding curves, show local variations, and highlight interactions between columns and rows of a two-way matrix.
When plot = TRUE
, it returns a plot.
When plot = FALSE
, it returns the following:
datarowmean |
rowmean of functional data as the number of covariates gradually increases. |
datacolmean |
colmean of functional data as the number of curves gradually increases. |
svdrow |
Changes in the first SVD component as the number of covariates gradually increases. |
svdcol |
Changes in the first SVD component as the number of curves gradually increases. |
approx |
Approximation of the original functions. |
residual |
Residual functions. |
xname |
x label of the graph. |
yname |
y label of the graph. |
MATLAB code is available at http://www.unc.edu/~lszhang/research/network/SVDmovie/.
Using the animate package of Grahn(2009), a set of dynamic movies can be created to visualize the changes in singular rows and singular columns.
Han Lin Shang
L. Zhang, J. Marron, H. Shen and Z. Zhu (2007) "Singular value decomposition and its visualization", Journal of Computational and Graphical Statistics, 16(4), 833-854.
A. Grahn (2009) "The animate Package", http://ctan.unsw.edu.au/macros/latex/contrib/animate/animate.pdf.
SVDplot(ElNino)