R: Plot Functional Principal Components

plot.pca.fd {fda} | R Documentation

## Plot Functional Principal Components

### Description

Display the types of variation across a sample of functions. Label with the eigenvalues that indicate the relative importance of each mode of variation.

### Usage

    #plot.pca.fd(x, nx = 128, pointplot = TRUE, harm = 0,
    #                        expand = 0, cycle = FALSE, ...)

    #NOTE:  The following is required by CRAN rules that
    # function names like "as.numeric" must follow the documentation
    # standards for S3 generics, even when they are not.
    # Please ignore the following line:
    ## S3 method for class 'pca.fd'
    plot(x, nx = 128, pointplot = TRUE, harm = 0,
                            expand = 0, cycle = FALSE, ...)

### Arguments

`x` | a functional data object.
`nx` | Number of points to plot or vector (if length > 1) to use as `evalarg` in evaluating and plotting the functional principal components.
`pointplot` | logical: If TRUE, the harmonics / principal components are plotted as '+' and '-'. Otherwise lines are used.
`harm` | Harmonics / principal components to plot. If 0, plot all. If length(harm) > sum(par("mfrow")), the user advised, "Waiting to confirm page change..." and / or 'Click or hit ENTER for next page' for each page after the first.
`expand` | nonnegative real: If expand == 0 then effect of +/- 2 standard deviations of each pc are given otherwise the factor expand is used.
`cycle` | logical: If cycle=TRUE and there are 2 variables then a cycle plot will be drawn If the number of variables is anything else, cycle will be ignored.
`...` | other arguments for 'plot'.

### Details

Produces one plot for each principal component / harmonic to be plotted.

### Value

invisible(NULL)

### See Also

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

### Examples

    #  carry out a PCA of temperature
    #  penalize harmonic acceleration, use varimax rotation

    daybasis65 <- create.fourier.basis(c(0, 365), nbasis=65, period=365)

    harmaccelLfd <- vec2Lfd(c(0,(2*pi/365)^2,0), c(0, 365))
    harmfdPar     <- fdPar(daybasis65, harmaccelLfd, lambda=1e5)
    daytempfd <- smooth.basis(day.5, CanadianWeather$dailyAv[,,"Temperature.C"],
                         daybasis65, fdnames=list("Day", "Station", "Deg C"))$fd

    daytemppcaobj <- pca.fd(daytempfd, nharm=4, harmfdPar)
    #  plot harmonics, asking before each new page after the first:
    plot.pca.fd(daytemppcaobj)

    # plot 4 on 1 page
    op <- par(mfrow=c(2,2))
    plot.pca.fd(daytemppcaobj, cex.main=0.9)
    par(op)

[Package fda version 2.4.8 Index]