powered by
A wrapper around vegan::metaMDS.
NMDS(x, distance = "bray", k = 2, try = 20, trymax = 20, ...)
what is returned by vegan::metaMDS plus $fac. And prepend NMDS class to it.
$fac
NMDS
any Coe object
a dissiminarity index to feed vegan::vegdist (default: bray)
bray
numeric number of dimensions to feed vegan::metaMDS (default: 2)
numeric
numeric minimum number of random starts to feed vegan::metaMDS (default: 20)
additional parameters to feed vegan::metaMDS
For Details, see vegan::metaMDS
Other multivariate: CLUST(), KMEANS(), KMEDOIDS(), LDA(), MANOVA_PW(), MANOVA(), MDS(), MSHAPES(), PCA(), classification_metrics()
CLUST()
KMEANS()
KMEDOIDS()
LDA()
MANOVA_PW()
MANOVA()
MDS()
MSHAPES()
PCA()
classification_metrics()
x <- bot %>% efourier %>% NMDS # Shepard diagram # before a Momocs wrapper # vegan::stressplot(x)
Run the code above in your browser using DataLab