Hi Soyeon, Here are a few options: ## Use get() to find the predictor r <- rep(0, 13) for(i in 1: 13) { r[i] <- summary(lm(MEDV ~ get(name[i]), data = boston))$r.squared }
## Use as.formula(paste()) to construction the model for(i in 1: 13) { r[i] <- summary(lm(as.formula(paste("MEDV ~ ", name[i], sep="")), data = boston))$r.squared } ## Just square the correlations (this is how I would do it) r <- cor(boston)["MEDV",]^2 Best, Ista On Mon, Sep 20, 2010 at 1:03 PM, Soyeon Kim <yunni0...@gmail.com> wrote: > Dear All, > > I have data which contains 14 variables. And I have to regress one of > variables on each variable (simple 13 linear regressions) > > I try to make a loop and store only R-squared > > colnames(boston) > [1] "CRIM" "ZN" "INDUS" "CHAS" "NOX" "RM" "AGE" > [8] "DIS" "RAD" "TAX" "PTRATIO" "B" "LSTAT" "MEDV" > > name <- colnames(boston) > > r <- rep(0, 13) > for(i in 1: 13) { > r[i] <- summary(lm(MEDV ~ name[i], data = boston))$r.squared > } > > but this doesn't work because name have " " for each variable. How to > remove " " for name of each variable? > Or do you know the way I can do regression MEDV on each variable? > > Thank you ahead, > Soyeon > > ______________________________________________ > 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. > -- Ista Zahn Graduate student University of Rochester Department of Clinical and Social Psychology http://yourpsyche.org ______________________________________________ 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.