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You should supply either a distance object or data. If you supply a matrix, it is regarded as data and dissimilarities are calculated. So the following should be equivalent:
Several functions accept either 'dist' object or raw data from
which they calculate distances. If users supply their distances
as square matrices (or data frames) these may be taken as raw
data and we end up calculateing distances of distances. Most
such functions had a test for symmetric square matrices that
probably hold distances, but now these tests are made more
consistent and robust.
Should fix problems like issue #147
i am trying to use the adonis function in vegan to run the permanova analysis. but i am getting very different results depending on how i call adonis.
if i call adonis using a distance object such as the following:
bc=vegdist( data, method='bray')
adonis(bc~var)
i get a very different result than if i convert bc (a dist object) into a matrix:
bc=as.matrix( vegdist(data, method='bray') )
adonis(bc~var)
what is causing this difference and which is correct?
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