# Linear discriminant analysis in R: how to choose the most suitable model?

The data set vaso in the robustbase library summarizes the vasoconstriction (or not) of subjects’ fingers along with their breathing volumes and rates.

> head(vaso)
Volume  Rate Y
1   3.70 0.825 1
2   3.50 1.090 1
3   1.25 2.500 1
4   0.75 1.500 1
5   0.80 3.200 1
6   0.70 3.500 1


I want to perform a linear discriminant analysis in R to see how well these distinguish between the two groups. And I consider two cases:

ld <- lda(Y ~ ., data=vaso)

ld1 <- lda(Y ~ log(Volume)+log(Rate), data=vaso)