try it better this way:
XX <- matrix(runif(8), ncol = 2)
DF <- as.data.frame(XX)
DF$yy <- runif(4)
model <- lm(yy ~ ., DF)
XX.pred <- as.data.frame(matrix(runif(6), ncol = 2))
predict(model, XX.pred)
I hope it helps.
Best,
Dimitris
On 8/17/2010 2:24 PM, Stephan Kolassa wrote:
Dear all,
I am stumped at what should be a painfully easy task: predicting from an lm
object. A toy example would be this:
XX<- matrix(runif(8),ncol=2)
yy<- runif(4)
model<- lm(yy~XX)
XX.pred<- data.frame(matrix(runif(6),ncol=2))
colnames(XX.pred)<- c("XX1","XX2")
predict(model,newdata=XX.pred)
I would have expected the last line to give me the predictions from the model based on
the new data given in XX.pred... but all I get are in-sample fits along with a warning
"'newdata' had 3 rows but variable(s) found have 4 rows". Why would predict.lm
worry about the number of rows in the model matrix?
Unfortunately, ?predict.lm does not seem to be helpful, and neither RSiteSearch
nor rseek.org have been useful. I'm sure that I am making an elementary error
somewhere (am I misunderstanding the lm(yy~XX) part?) and would appreciate a
gentle nudge in the right direction.
Thank you,
Stephan
--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014
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