R: Plot Functional Canonical Correlation Weight Functions

plot.cca.fd {fda} | R Documentation

## Plot Functional Canonical Correlation Weight Functions

### Description

A canonical correlation analysis produces a series of pairs of functional data objects which, when used as weighting functions, successively maximize the corresponding canonical correlation between two functional data objects. Like functional principal component weight functions, successive weight within either side fo the pair are required to be orthogonal to all previous weight functions. Consequently, each successive canonical correlation will no larger than its predecessor, and more likely substantially smaller. This function plots an object of class `cca.fd` that results from the use of function `cca.fd`. Each pair of weight functions is plotted after a left mouse click indicating that you are ready for the next plot.

### Usage

    ## S3 method for class 'cca.fd'
    plot(x, cexval = 1, ...)

### Arguments

`x` | an object of class `cca.fd` produced by an invocation of function `cca.fd.R`.
`cexval` | A number used to determine label sizes in the plots.
`...` | other arguments for 'plot'.

### Details

Produces a plot of a pair of weight functions corresponding to each canonical correlation between two functional data objects.

### Value

invisible(NULL)

### See Also

`cca.fd`, `pda.fd` `plot.pca.fd`

### Examples

    #  Canonical correlation analysis of knee-hip curves

    gaittime  <- (1:20)/21
    gaitrange <- c(0,1)
    gaitbasis <- create.fourier.basis(gaitrange,21)
    lambda    <- 10^(-11.5)
    harmaccelLfd <- vec2Lfd(c(0, 0, (2*pi)^2, 0))
    gaitfdPar <- fdPar(gaitbasis, harmaccelLfd, lambda)
    gaitfd    <- smooth.basis(gaittime, gait, gaitfdPar)$fd
    ccafdPar  <- fdPar(gaitfd, harmaccelLfd, 1e-8)
    ccafd0    <- cca.fd(gaitfd[,1], gaitfd[,2], ncan=3, ccafdPar, ccafdPar)
    #  display the canonical correlations
    round(ccafd0$ccacorr[1:6],3)
    #  plot the unrotated canonical weight functions
    plot.cca.fd(ccafd0)
    #  compute a VARIMAX rotation of the canonical variables
    ccafd <- varmx.cca.fd(ccafd0)
    #  plot the rotated canonical weight functions
    plot.cca.fd(ccafd)

[Package fda version 2.4.8 Index]