[R-sig-eco] non-metric MDS comparison - vegan vs. ecodist packages

[Gavin Simpson]

On Mon, 2012-02-20 at 16:28 +0100, Gian Maria Niccolò Benucci wrote:
> Hi r-sig-ecology Members,
> 
> I would please you to examine the differences I found in metaMDS() and
> nmds() outputs and possibly draw some conclusions. As I wrote in past
> emails I have 24 samples of ectomycorrhizal fungi grouped into two
> different communities (12 natural and 12 cultivated).
> 
> here is the code:
> 
> > metaMDS(data_matrix2, distance="bray", k=2, autotransform=F) -> metaMDS
> > metaMDS
> 
> Call:
> metaMDS(comm = data_matrix2, distance = "bray", k = 2, autotransform = F)
> 
> global Multidimensional Scaling using monoMDS
> 
> Data:     data_matrix2
> Distance: bray
> 
> Dimensions: 2
> *Stress:     0.04536661 *
> Stress type 1, weak ties
> No convergent solutions - best solution after 20 tries

Perhaps you could try running metaMDS with random starts until it does
find convergent solutions?! Why expect metaMDS() to do better in 20
tries than nmds() with 100 random tries?

add `trymax = 100` and `halfchange = FALSE` to try to make the two
functions more comparable.

HTH

G

> Scaling: centring, PC rotation, halfchange scaling
> Species: expanded scores based on data_matrix2
> 
> > nmds <- nmds(dist_bray, mindim = 2, maxdim = 2, nits = 100)
> Using random start configuration
> Using random start configuration
> ...
> > nmds_min
>             X1          X2
> 1  -0.66226262  0.16392824
> 2  -0.68844987 -0.20891993
> 3  -0.47717515  0.55323693
> 4  -0.67213392 -0.09195847
> 5   0.03305172  0.41844232
> 6   0.31992006  0.53887910
> 7  -0.61944875  0.34411146
> 8   0.07013849  0.65723057
> 9   0.53053436  0.37444633
> 10  0.26704705  0.39849341
> 11 -0.20981416  0.70391983
> 12 -0.61620355 -0.43568743
> 13  0.14219660 -0.69571194
> 14  0.42365981 -0.43308767
> 15  0.15840330 -0.12872863
> 16 -0.00492407 -0.06889680
> 17 -0.20513513 -0.58052156
> 18  0.46546214  0.12019775
> 19  0.36753709 -0.25048256
> 20 -0.09446486 -0.61943616
> 21  0.15010553 -0.31995009
> 22  0.41540872 -0.29507200
> 23  0.42573367 -0.12321584
> 24  0.48081354 -0.02121688
> > min(nmds$stress)
> [*1] 0.2787161*
> > nmds$r2[which.min(nmds$stress)]
> [1] 0.6338372
> 
> Is it possible I got so different stress values??
> 
> Thanks for replying,
> 
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