Dear Jeffrey,
I might be wrong, but I am affraid you will have to define the
similarity you want by yourself,
calculate it separately and combine with the similarity obtained from
other traits.
That will not be difficult, since the Gower's coeficient is just a
(weighted) average of partial
Hi Thiago,
I am not familiar with the diversity measure you are trying to calculate
and your example code is not complete - one can not simulate your comm
and dist objects.
But at the first sight one can see that in your loop you are trying to
select columns 1, 2, 3,... 1000 from the comm
Hi Kendra,
I am just forwarding your message to the list so that it is clear the
problem is solved.
You are welcome :)
Vit
Dne 2013-10-29 19:59, Mitchell, Kendra napsal:
Thank you. that is exactly what I wanted to do.
Kendra
--
Kendra Maas Mitchell, Ph.D.
Post Doctoral Research Fellow
Dear Kendra,
I am not sure I understand your question exactly. Maybe the R code you
already have would help.
Below is a sample of the data as returned by dput() so that anyone can
follow or extend this reply.
First, I would create a variable distinguishing all levels, for which
the mean is
Hi Elaine,
Maybe an easier way is to create a factor that will assign the islands
into groups.
If you want to classify the islands manually, then it might be better
to use Excel or another tabular processor.
Following your example:
groups- factor(c('site2', 'site1', 'site1', 'site1',
Dear Jonas,
I've just had a look into the paper (Friberg et al (2013)), but there
is no information on what kind of ordination they used (at least it is
very well hidden). Hard to believe, maybe I am wrong, but can't find
anything about that. And they used different ordination techniques to
seem to have that right, though the cmdscale()
call
might take a little bit more effort if you want to handle negative
Eigenvalues that arise with some dissimilarity metrics.
On 10 August 2013 06:33, Vít Syrovátka syro...@sci.muni.cz wrote:
Dear Jonas,
I've just had a look into the paper
