Solved my own problem. If interested:
http://stackoverflow.com/questions/15563589/odd-error-error-in-predictmatobjectsmoothk-data-by-variable-must
On 03/21/2013 02:14 PM, Andrew Crane-Droesch wrote:
Dear List,
I'm getting an error in mgcv, and I can't figure out where it comes
from. The setup is the following: I've got a fitted GAM object
called "MI", and a vector of "prediction data" (with default values
for predictors). I feed this into predict.gam(object, newdata =
whatever) via the following function:
makepred = function(varstochange,val){
for (i in 1:length(varstochange)){
if (varstochange[i] == "pot.trial"){j=1}
if (varstochange[i] == "year"){j=2}
if (varstochange[i] == "crop.legume"){j=3}
if (varstochange[i] == "crop.fruit"){j=4}
if (varstochange[i] == "feedstock"){j=5}
if (varstochange[i] == "BCAR.imp"){j=8}
if (varstochange[i] == "INAR.imp"){j=9}
if (varstochange[i] == "bcph.imp"){j=10}
if (varstochange[i] == "phi.imp"){j=11}
if (varstochange[i] == "htt.imp"){j=12}
if (varstochange[i] == "bc.prc.C.imp"){j=13}
if (varstochange[i] == "CEC.imp"){j=14}
if (varstochange[i] == "soc.imp"){j=15}
if (varstochange[i] == "sand.imp"){j=16}
if (varstochange[i] == "clay.imp"){j=17}
if (varstochange[i] == "abslat.imp"){j=18}
preddat[j] = val[i]
}
predict.gam(MI,newdata=preddat,se.fit=TRUE)
}
I then make predictions that look like this:
a = makepred(c("phi.imp","bcph.imp","year"),c(4.5,7.25,1))
b = makepred(c("phi.imp","bcph.imp","year"),c(5.5,7.25,1))
c = makepred(c("phi.imp","bcph.imp","year"),c(6.5,7.25,1))
d = makepred(c("phi.imp","bcph.imp","year"),c(7.5,7.25,1))
makepHplot(a,b,c,d,title="1st harvest, BC pH = 7.25")
where "makepHplot" is a different function that I made.
This worked for quite some time. Then I added some data to the model
and changed the specification slightly. Now I'm getting this error
message:
1> a = makepred(c("bcph.imp","year"),c(7.5,1))
Error in PredictMat(object$smooth[[k]], data) :
`by' variable must be same dimension as smooth arguments
I never got this message with the old fitted model (and still don't).
What is happening? I can't figure out what about the new fitted model
is causing this problem. Typing "PredictMat" isn't helping me, nor is
google. The problem isn't that all of the variables aren't in the
prediction data.
Would appreciate any help here.
Thanks,
Andrew
______________________________________________
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.
