Le lundi 12 mars 2012 à 14:48 +0000, aoife doherty a écrit :
> Hey guys,
>
> if i do a correspondance analysis, e.g.:
>
> table <- structure(c(4, 7, 0.2, 3, .1, 7, 222, 3, 10, 5, 11,
> 8, 8, 10, 7), .Dim = c(5L, 3L), .Dimnames = list(c("gene1",
> "gene2", "gene3", "gene4", "gene5"), c("codon1", "codon2",
> "codon3")))
>
> Library(ca)
>
> plot(ca(table))
>
> is there a way that i can see the "second principal axis" of this analysis?
You're joking, right? :-p How many dimensions are you able to represent
on a screen? Two, isn't it? So the vertical axis is your second
dimension.
You can get details as this:
summary(ca(table))
Principal inertias (eigenvalues):
dim value % cum% scree plot
1 0.394553 92.8 92.8 *************************
2 0.030431 7.2 100.0
-------- -----
Total: 0.424984 100.0
Here you see the second axis accounts for only 7.2% of the total
variance.
Cheers
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