Dear list,
I would like to easily compute the adjusted R-square in a lm model without
intercept (excluding the intercept is essential for my analysis)
I found that RsquareAdj() in vegan returns NA if the argument is a
multiple-multivariate lm model thus including multivariate responses and
Specific reason is that nobody has implemented this. These things don't come by
automatic writing, but somebody must do them.
What would you expect to get? Is this what was on your mind:
sapply(summary(lm(yy~xx-1)), function(x) c(r.squared = x$r.squared,
adj.r.squared = x$adj.r.squared))
Thankyou very much Jari!
I think that it is nearly ok
what I would like to have is the same as in
RsquareAdj(vegan::rda(yy,xx))
that is a GLOBAL measure of the association
BUT...I want it for a multiple-multivariate lm model that does not include the
intercept;
an alternative could be to build a
Paolo,
See ?RsquareAdj for the call interface. The default method can be called as
RsquareAdj(x, n, m), and in the default method x is the unadjusted correlation,
n is the number of observations and m is the number of parameters (degrees of
freedom) in the fitted model. Specific methods for
Thanks Jari, I understand
Before going trough the code of rda I would prefer to see if I can do this
using RsquareAdj
When you say The default method can be called as RsquareAdj(x, n, m), and in
the default method x is the unadjusted correlation...etc..
my problem is to extract the global
