If cm is a similarity matrix, why are you taking its Euclidean distance?
(The usage I'm familiar with has similarity as a pairwise measure of
association.)
Otherwise, if you feel the stress is too high, that implies that a 2-dimensional
solution is inadequate for your data and you should consider
Hello everyone!
metaMDS(cm, distance = euclidean, k = 2, trymax = 50, autotransform
=TRUE,trace = 1, plot = T)
(cm is a similarity matrix, in which values are positive integers or 0)
I use this command to run NMDS on my matrix cm. But the stress is very
high after analysis. About 14.
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