Thanks a lot for your answers,
I am concerned by your advice not to use polynomial constraints, or to use
QDA instead of RDA. My final goal is to perform variation partitioning using
partial RDA to assess the relative importance of environmental vs spatial
variables. For the spatial analyses, trend surface analysis (polynomial
constraints) is recommended in Legendre and Legendre 1998 (p739). Is there a
better method to integrate space as an explanatory variable in a variation
partitioning analyses?
Also, I don't understand this: when I test for the significant contribution
of monomials (forward elimination)
anova(rda(Helling ~ I(x^2)+Condition(x)+Condition(y)))
performs the permutation test as expected, whereas
anova(rda(Helling ~ I(y^2)+Condition(x)+Condition(y)))
Returns this error message:
Error in names-.default(`*tmp*`, value = Model) :
attempt to set an attribute on NULL
Thanks again for your help
Kind regards,
Helene
Helene MORLON
University of California, Merced
-Original Message-
From: Jari Oksanen [mailto:[EMAIL PROTECTED]
Sent: Monday, February 26, 2007 11:27 PM
To: r-help@stat.math.ethz.ch
Cc: [EMAIL PROTECTED]
Subject: [R] RDA and trend surface regression
'm performing RDA on plant presence/absence data, constrained by
geographical locations. I'd like to constrain the RDA by the extended
matrix of geographical coordinates -ie the matrix of geographical
coordinates completed by adding all terms of a cubic trend surface
regression- .
This is the command I use (package vegan):
rda(Helling ~ x+y+x*y+x^2+y^2+x*y^2+y*x^2+x^3+y^3)
where Helling is the matrix of Hellinger-transformed presence/absence data
The result returned by R is exactly the same as the one given by:
anova(rda(Helling ~ x+y)
Ie the quadratic and cubic terms are not taken into account
You must *I*solate the polynomial terms with function I (AsIs) so that
they are not interpreted as formula operators:
rda(Helling ~ x + y + I(x*y) + I(x^2) + I(y^2) + I(x*y^2) + I(y*x^2) +
I(x^3) + I(y^3))
If you don't have the interaction terms, then it is easier and better
(numerically) to use poly():
rda(Helling ~ poly(x, 3) + poly(y, 3))
Another issue is that in my opinion using polynomial constraints is an
Extremely Bad Idea(TM).
cheers, Jari Oksanen
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