That sounds like a job for path analysis or for structural equation
modeling, depending on the level of sophistication desired and the
hypotheses to be tested.
There are plenty of good resources for both, in and out of R.
Sarah
On Wednesday, March 6, 2013, Jay Kerns wrote:
Hello,
I'm
Hi all,
I would like to use ordipointlabel() to plot a RDA but the function
only displays species and sites. How can I include environmental
variables as vectors?
Thanks!
--
---
A. CAROLINA MONMANY
Universidad de Puerto Rico
Departamento de Biologia - CN 235
POBOX
Dear all
I want to find regression between fish larva abundance and some
abiotic factor ,i used this code:
glm(formula = mychto ~ po4 + No3 + Si + Tn)
result:
Deviance Residuals:
Min 1Q Median 3Q Max
-26.586 -18.262 -12.296 -2.949 226.229
Coefficients:
There's probably something off the shelf, but
I use a little function written in R:
#A function for doing an xyz bubbleplot.
bubbleplot - function(x, y, z, bmax=4, bmin=.5) {
plot(x,y, type=n)
z - z-min(z); z - z/max(z)
for (i in 1:length(x)) {
On 03/07/2013 04:24 PM, Mahnaz Rabbaniha wrote:
Dear all
I want to find regression between fish larva abundance and some
abiotic factor ,i used this code:
glm(formula = mychto ~ po4 + No3 + Si + Tn)
result:
Deviance Residuals:
Min 1Q Median 3Q Max
-26.586 -18.262
Hi Mahnaz,
First of all check whether you're using the right family error
distribution according to tour respinse varia le. If you use team
abundancea from counts you need to specify family = poisson in your
model.
Then AIC is used to select the best from a set of candidate models, it
is not
On Thu, 2013-03-07 at 10:48 -0400, carolina monmany wrote:
Hi all,
I would like to use ordipointlabel() to plot a RDA but the function
only displays species and sites. How can I include environmental
variables as vectors?
Thanks!
You can use
text(ord, display = bp)
(where `ord` is
On Thu, 2013-03-07 at 15:37 +, Mark Fulton wrote:
There's probably something off the shelf, but
I use a little function written in R:
#A function for doing an xyz bubbleplot.
bubbleplot - function(x, y, z, bmax=4, bmin=.5) {
plot(x,y, type=n)
z - z-min(z); z - z/max(z)
for (i in
Jay--
I'm not sure how one would combine SEM / graphical models with
compositional dissimilarity as a response. You might be able to fit a
series of models in adonis() or capscale(), comparing just direct factors
to direct + intermediate, etc.. I don't have any good ideas on how you
might test
Hi,
I'm not sure how one would combine SEM / graphical models with compositional
dissimilarity as a response. You might be able to fit a series of models in
adonis() or capscale(), comparing just direct factors to direct +
intermediate, etc.. I don't have any good ideas on how you might
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