[R-sig-eco] ordination and clustering with continous and categorical variables

[Mario Brusadin]

Dear all,

Apologies in advance for the total beginner's question. I would like
to perform a simple ordination on a dataset of species traits,
contaning both continous and categorical variables, as well as a
cluster analysis on the same dataset. My aim is to identify, species
niche-breadth using the ordination and identify any clusters of
similar species, with the cluster analysis. I would possibly like to
overlay the results of the cluster analysis results onto an ordination
plot.

I have seen from previous discussions on this mailing list that it is
possible to apply hierchical clustering to a distance matrix, created
with the function daisy from the cluster package. This function can be
set to use the Gower dissimilarity coefficient (1971), to create a
distance matrix, from a dataset that contains both continous and
categorical variables.  Is the best option available? As for the
ordination, I am not entirely sure about which ordination method which
I should use. Is Correspondence Analysis suitable or would it be
better to use Principal coordinates analysis? Any suggestions/help
would be greatly appreciated!

Gower, J. C. (1971) A general coefficient of similarity and some of
its properties, Biometrics 27, 857–874.


Cheers

Mario

--
Padova
Italy