Stability Analysis for Principle Differential Analysis
Overlays the results of a univariate, second-order principal differential analysis on a bifurcation diagram to demonstrate stability.
pda.overlay(pdaList,nfine=501,ncoarse=11,...)
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'. |
Overlays a bivariate plot of the functional parameters in a univariate second-order principal differential analysis on a bifurcation diagram.
None.
# 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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.