pda.overlay {fda} | R Documentation |
Stability Analysis for Principle Differential Analysis
Description
Overlays the results of a univariate, second-order principal differential analysis on a bifurcation diagram to demonstrate stability.
Usage
pda.overlay(pdaList,nfine=501,ncoarse=11,...)
Arguments
pdaList |
a list object returned by |
nfine |
number of plotting points to use. |
ncoarse |
number of time markers to place along the plotted curve. |
... |
other arguments for 'plot'. |
Details
Overlays a bivariate plot of the functional parameters in a univariate second-order principal differential analysis on a bifurcation diagram.
Value
None.
References
Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), Functional data analysis with R and Matlab, Springer, New York.
Ramsay, James O., and Silverman, Bernard W. (2005), Functional Data Analysis, 2nd ed., Springer, New York.
Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York.
See Also
Examples
oldpar <- par(no.readonly=TRUE)
# This example looks at a principal differential analysis of the lip data
# in Ramsay and Silverman (2005).
# First smooth the data
lipfd <- smooth.basisPar(liptime, lip, 6, Lfdobj=int2Lfd(4),
lambda=1e-12)$fd
names(lipfd$fdnames) <- c("time(seconds)", "replications", "mm")
# Now we'll set up functional parameter objects for the beta coefficients.
lipbasis <- lipfd$basis
lipfd0 <- fd(matrix(0,lipbasis$nbasis,1),lipbasis)
lipfdPar <- fdPar(lipfd0,2,0)
bwtlist <- list(lipfdPar,lipfdPar)
xfdlist <- list(lipfd)
# Call pda
pdaList <- pda.fd(xfdlist, bwtlist)
# And plot the overlay
pda.overlay(pdaList,lwd=2,cex.lab=1.5,cex.axis=1.5)
par(oldpar)