On 21/09/10 17:40 PM, "Nevil Amos" <nevil.a...@gmail.com> wrote:

>   I am trying to use the cca/rda/capscale functions in vegan to analyse
> genetic distance data ( provided as a dist object calculated using
> dist.genpop in package adegenet) with geographic distance partialled out
> ( provided as a distance object using dist function in veganthis method
> is attempting to follow the method used by Geffen et al 2004  as
> suggested by Legendre and . FORTIN (2010).
> 
> I cannot see how to introduce the Conditioning ( partialled) second dist
> matrix.  as you can see from the code snippet below, the two dist
> objects are of the same dimensions. - I get an error using capscale:
>          Error in qr.fitted(Q, Xbar) :
>                'qr' and 'y' must have the same number of rows
> or cca
>          Error in weighted.mean.default(newX[, i], ...) :
>                 'x' and 'w' must have the same length
> when using a conditioning distance object instead of a variable (Clade)
> of the same length as  the constraints ( Latitude and Longitude)
> 
> I would be grateful, for any pointers on this, ie which test is the
> appropriate one to use ( I believe capscale since it is "similar to
> distance-based redundancy analysis (Legendre & Anderson 1999)") and
> whether this test is indeed equivalent to the approach suggested by
> Legendre &Fortin, (Geffen et al used DISTLM).
> 

Nevil,

You cannot use cca() for dissimilarity data. If you have dissimilarity data,
you must use capscale() which runs db-RDA. Even there, your constraints
(variables on the right hand side of the formula) must be rectangular data
and not dissimilarities. AFAIK, people have changed their dissimilarities
into a PCNM structure when they want to partial out the distance effect.
That is one of the few original possibilities since data must be rectangular
(rows and columns).

Cheers, jari oksanen

______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Reply via email to