Dear Gavin, Thank you very much. I tried with your advice but the result is almost unchanged...
> metaMDS(data_matrix2, distance="bray", k=2, autotransform=F, trymax=100, halfchange=F) -> metaMDS_new Run 0 stress 0.05172131 Run 1 stress 0.04877468 ..... Run 47 stress 0.04663743 Run 48 stress 0.05066009 Run 49 stress 0.04525287 ... New best solution ... procrustes: rmse 0.001156733 max resid 0.002525323 *** Solution reached > metaMDS_new Call: metaMDS(comm = data_matrix2, distance = "bray", k = 2, trymax = 100, autotransform = F, halfchange = F) global Multidimensional Scaling using monoMDS Data: data_matrix2 Distance: bray Dimensions: 2 Stress: 0.04525287 Stress type 1, weak ties Two convergent solutions found after 49 tries Scaling: centring, PC rotation Species: expanded scores based on data_matrix2 Any further advice?? Gian 2012/2/20 Gavin Simpson <gavin.simp...@ucl.ac.uk> > 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, > > > > _______________________________________________ > > R-sig-ecology mailing list > > R-sig-ecology@r-project.org > > https://stat.ethz.ch/mailman/listinfo/r-sig-ecology > > -- > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% > Dr. Gavin Simpson [t] +44 (0)20 7679 0522 > ECRC, UCL Geography, [f] +44 (0)20 7679 0565 > Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk > Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ > UK. WC1E 6BT. [w] http://www.freshwaters.org.uk > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% > > > *----- Do not print this email unless you really need to. Save paper and protect the environment! -----* [[alternative HTML version deleted]]
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