Dear R friends-
I'm attempting to generate a regression tree with one gradient predictor and
multiple responses, trying to test if change in size (turtle.data$Clength) acts
as a single predictor of ten multiple diet taxa abundances (prey.data) Neither
rpart or mvpart seem to allow me to do multiple responses. (Or if they can,
I'm not using the functions properly.)
> library(rpart)
> turtle.rtree<-rpart(prey.data~., data=turtle.data$Clength, method="anova",
> maxsurrogate=0, minsplit=8, minbucket=4, xval=10); plot(turtle.rtree);
> text(turtle.rtree)
Error in terms.formula(formula, data = data) :
'.' in formula and no 'data' argument
When I switch response for predictor, it works. But this is the opposite of
what I wanted to test and gives me splits at abundance values, not carapace
length values.
> turtle.rtree<-rpart(turtle.data$Clength~., data=prey.data, method="anova",
> maxsurrogate=0, minsplit=8, minbucket=4, xval=10); plot(turtle.rtree);
> text(turtle.rtree)
>
I've heard polymars recommended for this sort of situation. I've downloaded
the polyspline library, but get bogged down in the equation. Also, it doesn't
seem like polymars will generate a tree even if I do get it working. Can rpart
be modified in some way to accomodate multiple response parameters? If
anyone's ever come across this situation before, pointers would be much
appreciated. Thanks.
Sincerely,
Jeff Bardwell
Jeff H Bardwell, M.S.
Biology Department
ENV 1101 Lab Coordinator
Goebel 115, OH: Thu 1pm-4pm
710-6596 (e-mail preferred)
______________________________________________
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.
