Ross, You can store the lm() results in a list, if you like. For example:
DV <- c("mpg", "drat", "gear") IV <- list(c("cyl", "disp", "hp"), c("wt", "qsec"), c("carb", "hp")) fits <- vector("list", length(DV)) for(i in seq(DV)) { fit <- lm(formula=paste(DV[i], paste(IV[[i]], collapse="+"), sep="~"), data=mtcars) plot(fit$fitted, fit$resid, main=paste("DV", DV[i], sep="=")) lapply(fit$model[, -1], function(x) plot(x, fit$resid)) fits[[i]] <- fit } Jean Ross Ahmed <rossah...@googlemail.com> wrote on 11/06/2012 09:25:13 AM: > > Thanks Jean > > This works for the plots, but it only stores the last lm() computed > > Ross > > From: Jean V Adams <jvad...@usgs.gov> > Date: Tuesday, 6 November 2012 14:12 > To: Ross Ahmed <rossah...@googlemail.com> > Cc: <r-help@r-project.org> > Subject: Re: [R] Apply same linear model to subset of dataframe > > Ross, > > Here's one way to condense the code ... > > DV <- c("mpg", "drat", "gear") > IV <- list(c("cyl", "disp", "hp"), c("wt", "qsec"), c("carb", "hp")) > > for(i in seq(DV)) { > fit <- lm(formula=paste(DV[i], paste(IV[[i]], collapse="+"), > sep="~"), data=mtcars) > plot(fit$fitted, fit$resid, main=paste("DV", DV[i], sep="=")) > lapply(fit$model[, -1], function(x) plot(x, fit$resid)) > } > > Jean > > > > Ross Ahmed <rossah...@googlemail.com> wrote on 11/04/2012 09:57:34 AM: > > > > I have applied the same linear model to several different subsets of a > > dataset. I recently read that in R, code should never be repeated.I feel my > > code as it currently stands has a lot of repetition, which could be > > condensed into fewer lines. I will use the mtcars dataset to replicatewhat > > I have done. My question is: how can I use fewer lines of code (for example > > using a for loop, a function or plyr) to achieve the same output as below? > > > > data(mtcars) > > > > # Apply the same model to the dataset but choosing different combinations of > > dependent (DV) and independent (IV) variables in each case: > > lm.mpg= lm(mpg~cyl+disp+hp, data=mtcars) > > lm.drat = lm(drat~wt+qsec, data=mtcars) > > lm.gear = lm(gear~carb+hp, data=mtcars) > > > > # Plot residuals against fitted values for each model > > plot(lm.mpg$fitted,lm.mpg$residuals, main = "lm.mpg") > > plot(lm.drat$fitted,lm.drat$residuals, main = "lm.drat") > > plot(lm.gear$fitted,lm.gear$residuals, main = "lm.gear") > > > > # Plot residuals against IVs for each model > > plotResIV <- function (IV,lmResiduals) > > { > > lapply(IV, function (x) plot(x,lmResiduals)) > > } > > > > plotResIV(lm.mpg$model[,-1],lm.mpg$residuals) > > plotResIV(lm.drat$model[,-1],lm.drat$residuals) > > plotResIV(lm.gear$model[,-1],lm.gear$residuals) > > > > Many thanks > > Ross Ahmed [[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.