plot.prcurve: Plot a fitted principal curve in PCA space

Description

Projects the principal curve into PCA space and draws it and the underlying data in a biplot.

Usage

# S3 method for prcurve
plot(x, axes = 1:2, scaling = 0, segments = TRUE,
     col = "red", col.seg = "forestgreen", lwd = 2,
     lwd.seg = 1, ...)
# S3 method for prcurve
lines(x, axes = 1:2, scaling = 0, segments = TRUE,
      col = "red", col.seg = "forestgreen", lwd = 2,
      lwd.seg = 1, ...)

Value

A plot on the currently active device. The function does not return anything.

Arguments

x: an object of class "prcurve".
axes: numeric vector of length 2; this is passed to the choices argument of the scores function.
scaling: numeric; the scaling to use. See scores.rda for the available options. The default is not to scale the scores, but scaling = 1 might be a useful alternative.
segments: logical; should segments be drawn between the observed points to the location on the principal curve on to which they project.
col: The colour to draw the principal curve in.
col.seg: The colour to draw the segments in.
lwd, lwd.seg: The line thickness used to draw the principal curve and segments respectively.
...: additional arguments passed on to points when drawing the observations in PCA space.

Author

Gavin L. Simpson

Examples

Run this code

## Load the Abernethy Forest data
data(abernethy)

## Remove the Depth and Age variables
abernethy2 <- abernethy[, -(37:38)]

## Fit the principal curve using varying complexity of smoothers
## for each species
aber.pc <- prcurve(abernethy2, method = "ca", trace = TRUE,
                   vary = TRUE, penalty = 1.4)

## Plot the curve
plot(aber.pc)

## The lines() method can be used to add the principal curve to an
## existing plot
ord <- rda(abernethy2)
plot(ord, scaling = 1)
lines(aber.pc, scaling = 1)

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