R: plotting posterior classification probabilities of a linear discriminant analysis in ggplot2

Question

Using ggord one can make nice linear discriminant analysis ggplot2 biplots (cf chapter 11, Fig 11.5 in \"Biplots in practice\" by M. Greenacre), as

Answer 1

I suppose the easiest way will be to show the posterior probabilities. It is pretty straightforward for your case:

datPred$maxProb <- apply(predict(fit)$posterior, 1, max)
ggplot(datPred, aes(x=LD1, y=LD2) ) +
  geom_raster(data=df, aes(x=x, y=y, fill = factor(class)),alpha=0.7,show_guide=FALSE) +
  geom_contour(data=df, aes(x=x, y=y, z=classnum), colour="red2", alpha=0.5, breaks=c(1.5,2.5)) +
  geom_point(data = datPred, size = 3, aes(pch = Species,  colour=Species, alpha = maxProb)) +
  scale_x_continuous(limits = ld1lim, expand=c(0,0)) +
  scale_y_continuous(limits = ld2lim, expand=c(0,0)) +
  scale_fill_manual(values=colorslight, guide=F)

You can see the points blend in at blue-green border.