Thank you very much Jari,
Using weakties = FALSE it works very well. The results are similar to the
book.
Best,
Manuel
e.mds = metaMDS(especies, distance = bray, weakties = FALSE)
Run 0 stress 0.1088505
Run 1 stress 0.113103
Run 2 stress 0.1356066
Run 3 stress 0.1088552
... procrustes: rmse 0.1304834 max resid 0.4025236
Run 4 stress 0.1403525
Run 5 stress 0.3915359
Run 6 stress 0.1305611
Run 7 stress 0.1417557
Run 8 stress 0.1088584
... procrustes: rmse 0.001626811 max resid 0.007608109
*** Solution reached
Mensajes de aviso perdidos
In distfun(comm, method = distance, ...) :
you have empty rows: their dissimilarities may be meaningless in method
âbrayâ
2012/6/12 Jari Oksanen jari.oksa...@oulu.fi
On 13/06/2012, at 07:33 AM, Manuel SpÃnola wrote:
Dear list members,
I am working on an NMDS using metaMDS from vegan with the Doubs fish data
from the book Numerical ecology with R.
especies - read.csv(DoubsSpe.csv, row.names = 1)
e.mds = metaMDS(especies, distance = bray)
Run 0 stress 0.003706943
Run 1 stress 0.0004788424
... New best solution
... procrustes: rmse 0.009197047 max resid 0.01874812
Run 2 stress 0.0004600702
... New best solution
... procrustes: rmse 0.0002883791 max resid 0.0005590752
*** Solution reached
Mensajes de aviso perdidos
In distfun(comm, method = distance, ...) :
you have empty rows: their dissimilarities may be meaningless in method
âbrayâ°
My results are strange (stress is too low and different to the one on
the
book) and the plot is very different to the one that appears in the book.
Manuel,
I'm too lazy to go to have a look at the book now (I'm sitting in my
balcony sipping my morning coffee), but I assume that the difference is
that metaMDS in your book was still based on MASS::isoMDS(), but the
current vegan (from 2.0-0) uses its own monoMDS() function as a default.
One difference is that isoMDS() expresses the stress per cent, and
monoMDS() as parts of one, so that equal isoMDS() is 100x higher. Another
difference is that monoMDS() implements treatment of tied dissimilarity
values, and defaults to weak ties so that equal observed dissimilarities
can be allowed to be at different ordination distances. If I remember
correctly, these Doubs fish data are very simple so that monoMDS() really
may be able to have nearly zero stress (which is suspect in general).
For better correspondence to the book, you may first try setting 'weakties
= FALSE' which will force tie treatment that is closer to isoMDS(), but
still not identical. For true replication of the book results you should
set 'engine = isoMDS'.
As usual, these are documented features.
Cheers, Jari Oksanen
--
Jari Oksanen, Dept Biology, Univ Oulu, 90014 Finland
jari.oksa...@oulu.fi, Ph. +358 400 408593, http://cc.oulu.fi/~jarioksa
--
*Manuel SpÃnola, Ph.D.*
Instituto Internacional en Conservación y Manejo de Vida Silvestre
Universidad Nacional
Apartado 1350-3000
Heredia
COSTA RICA
mspin...@una.ac.cr
mspinol...@gmail.com
Teléfono: (506) 2277-3598
Fax: (506) 2237-7036
Personal website: Lobito de rÃo https://sites.google.com/site/lobitoderio/
Institutional website: ICOMVIS http://www.icomvis.una.ac.cr/
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