for a beginner, it's probably even easier to it by hand if it is just five
datasets.
bind the 5 datasets together in one dataset and create and index variable (1
to 5) for each of the observations according to the dataset the obersvation
comes from
then run five regressions using
reg1=lm(M~D+O+S,subset=c(index==1))
.
.
.
reg5=lm(M~D+O+S,subset=c(index==5))
and then predict from each regression
predict(reg1,newdata=data.frame(D,O,S))
.
.
.
predict(reg5,newdata=data.frame(D,O,S))
You can then assess how well the prediction from each of the datasets fits
the respective other datasets...
Daniel
-------------------------
cuncta stricte discussurus
-------------------------
-----Urspr?ngliche Nachricht-----
Von: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] Im
Auftrag von Rbeginner
Gesendet: Sunday, July 19, 2009 9:49 PM
An: r-help at r-project.org
Betreff: [R] Re gression for loop test HELP! URGENT!
Hi everyone!
I'm new to R, and I'm stuck on a problem I don't know how to
approach.
I have calculated a regression in the form of M ~ D + O + S, and I would
like to take this regression and test it with other samples, 5 at a time(5
meaning 5 set, each consisting M, D, O, and S of a specific date). I assume
I'll need a for loop. Right now, My data of M, D, O, and S are all stored in
separate txt files, but should I just put them into a table or something?
And then how would I calculate the error of how well the test samples fit
the original regression?
This is for my internship, so it's very urgent.
THANKS A LOT!!!!!
RBeginner
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