pda.overlay: Stability Analysis for Principle Differential Analysis

In fda: Functional Data 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, returnMatrix=FALSE,...)

Arguments

pdaList	a list object returned by pda.fd.
nfine	number of plotting points to use.
ncoarse	number of time markers to place along the plotted curve.
returnMatrix	logical: If TRUE, a two-dimensional is returned using a special class from the Matrix package.
...	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.

See Also

pda.fd plot.pda.fd eigen.pda

Examples

# 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)

fda documentation built on May 2, 2019, 5:12 p.m.