plot.prcurve: Plot a fitted principal curve in PCA space
In gavinsimpson/analogue: Analogue and Weighted Averaging Methods for Palaeoecology

Description Usage Arguments Value Author(s) See Also Examples

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

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

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

`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.

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

Gavin L. Simpson

prcurve; rda for the code used to perform the PCA.

## 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)