Hi,
I have a linear model ("mod1 <- lm(V3~V1+V2) and I would like to get the
model's prediction at values of V1 and V2 not included in the original
sample.
samp <- read.table("data.dat",nrows=100)
attach(samp)
out.poly <- lm(V3 ~ V1 + V2)
If I try to use out.poly to predict values for the function I run into
problems. It seems that it isn't possible to use a new data frame for the
predict() or fitted() functions.
predict(out.poly, data.frame(x=V1, y=V2)) uses the original data
predict(out.poly, data.frame(x=V1, y=V2), newdata=gene.dat)
- uses the original data also, complaining of the decrease in rows.
If any one could point me in the correct direction, it would be appreciated.
Thanks
[[alternative HTML version deleted]]
______________________________________________
[email protected] 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.
