Hi again,
Just to clarify my question from previous email...
Example script:
A <- data[, c(1,2,3,4)]
B <- data[, c(5,6,7,8)]
library(vegan)
vare.proc <- procrustes(A,B, scale=FALSE, symmetric=FALSE)
vare.proc
summary(vare.proc)
plot(vare.proc)
#plot(vare.proc, kind=2)
residuals(vare.proc)
protest
Hi Tara,
Providing a simple example script that reproduces your case and using
it to support your question would increase your chances to obtain an
answer.
Best,
Pierrick
On Thu, Feb 19, 2015 at 5:43 PM, Tara Dirilgen
wrote:
> I have been using R to calculate the significance of Procrustes
> co
I have been using R to calculate the significance of Procrustes
correlations. With one series of data, where there are five cases, the
value returned for the correlation coefficient is one although there are
differences as shown by the procrustes error graph. Is there a statistical
reason for this?
On 2012-05-23 08:19, Juan Antonio Balbuena wrote:
Hello
This is a simple question but I couldn't google an answer.
In the procrustes function of the vegan package, one uses
plot(procrustes_object, kind=2) to obtain a plot of the residual
differences. For in
Hello
This is a simple question but I couldn't google an answer.
In the procrustes function of the vegan package, one uses
plot(procrustes_object, kind=2) to obtain a plot of the residual
differences. For instance:
data(varespec)
vare.dist <- vegdist(wisconsin(var
On Fri, 2010-12-03 at 09:58 +, Gavin Simpson wrote:
> On Thu, 2010-12-02 at 11:19 -0600, Christine Dolph wrote:
> > Hi, Thanks very much for your response.
>
> Thanks Christy,
>
> Apologies if I sounded off-hand or dismissive yesterday. It was a busy
> day, and as your mail lacked a reproduci
On Thu, 2010-12-02 at 11:19 -0600, Christine Dolph wrote:
> Hi, Thanks very much for your response.
Thanks Christy,
Apologies if I sounded off-hand or dismissive yesterday. It was a busy
day, and as your mail lacked a reproducible example nor the code you
ran, I wanted to deal with the low-hangin
Hi, Thanks very much for your response.
Unfortunately, using the set.seed() call does not seem to solve my problem.
If I do not use set.seed(), I do indeed get some small differences in
protest() results due to the effect of random starts. But with my sites in a
given order in the input files, and
On Wed, 2010-12-01 at 14:19 -0600, Christine Dolph wrote:
> Dear All,
>
> I am using a Procrustes analysis to compare two NMDS ordinations for the
> same set of sites. One ordination is based on fish data, the other is based
> on invertebrate data. Ordinations were derived using metaMDS() from the
Dear All,
I am using a Procrustes analysis to compare two NMDS ordinations for the
same set of sites. One ordination is based on fish data, the other is based
on invertebrate data. Ordinations were derived using metaMDS() from the
{vegan} library as follows:
fish.mds<-metaMDS(fish.data, distance=
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