R: Stability Analysis for Principle Differential Analysis

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, 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)

[Package fda version 2.4.8 Index]