Rbeginner wrote: > > Hi everyone! > I'm new to R, and I've sent this message as a non-member, but since it's > pretty urgent, I'm sending it again now I'm on the mailing list (Thanks > Daniel for your suggestion nevertheless). > > 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 sets of M, > D, > O, and S at a time(I actually have 2000 sets, so it's probably not > efficient > to make each a separate set and then index). Since I'll need to test the > regression for 400 groups, I thought a for loop might be necessary. I've > put > everything into a data frame already. Can anyone tell me how to write the > code? I'm especially not sure about how to do the for loop. > 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. > > > > > One option (out of the many): > > for (i in 1:2000) { > > M <- lm(M ~ D + O + S, subset = blah blah, data = YourData) > print(summary(M)) > } > > The "blah blah" select your rows of data for iteration i. > > See also: > > A Beginner's Guide to R (2009). Zuur, Ieno, Meesters. > > for something very similar. You can dump everything in a text file, or > just extract the required info from the summary function (like R^2 etc). > > Alain > > > Dr. Alain F. Zuur > First author of: > > 1. Analysing Ecological Data (2007). > Zuur, AF, Ieno, EN and Smith, GM. Springer. 680 p. > > 2. Mixed effects models and extensions in ecology with R. (2009). > Zuur, AF, Ieno, EN, Walker, N, Saveliev, AA, and Smith, GM. Springer. > > 3. A Beginner's Guide to R (2009). > Zuur, AF, Ieno, EN, Meesters, EHWG. Springer > > > > > > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. > >
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