[adegenet-forum] global rtest/ choice of spca axes of significance.
nevil.amos at gmail.com
Mon May 24 14:55:52 CEST 2010
The global.rtest gives a test of whether there is significant global (
ie cross-landscape) structure between sampled locations, correct?
In the spca tutorial example a single pca lambda1 clealy stands out .
How does one decide where more than one axis is involved, should it
stand out ( ie have substantially greater values) on both variance and
SA axes? or simply be an outlier on the variance axis?
Goes the global.rtest test just the first spca axis , or for any
significant global structure ( that may be across the first few axes)
If it does the latter is what objective approach can be taken to decide
how many axes should be considered as contributing to the structure?
School of Biological Sciences
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