I'm wondering how to find the correct eigen values and % of explain variances of my distatis plot. I'm using the package DistatisR.
I have the following code now:
DistanceCube <- DistanceFromSort(*owndata*)
testDistatis <- distatis(DistanceCube)
summary(testDistatis)
# 4.1 Get the bootstrap factor scores (with default 1000 iterations)
BootF <- BootFactorScores(testDistatis$res4Splus$PartialF)
# 4.2 Get the boostrap from full bootstrap (default niter = 1000)
F_fullBoot <- BootFromCompromise(DistanceCube,niter=1000)
# creat graphic
rv.graph.out <- GraphDistatisRv(testDistatis$res4Cmat$G)
compromise.graph.out <- GraphDistatisCompromise(testDistatis$res4Splus$F)
partial.scores.graph.out <- GraphDistatisPartial(testDistatis$res4Splus$F,testDistatis$res4Splus$PartialF)
boot.graph.out.ell <- GraphDistatisBoot(testDistatis$res4Splus$F,BootF)
I don't know if it's correct to do the following afterwards to find the eigen values and % of explained variance.
# print eigenvalues and % of expl. variance.
summary(prcomp(testDistatis$res4Splus$F))
Here is an article which shows the information I need in the graph: example pictures showing eigenvalues and % of explained variances in graph
https://www.sciencedirect.com/science/article/pii/S0950329310000972
Secondly, I also need to know how I can plot dim2 vs dim3 besides just dim1 and dim2. While using the output from the distatis. I hope someone can help me.
