On Wed, Nov 23, 2011 at 10:48 PM, Doran, Harold <hdo...@air.org> wrote: > Given the following data, I want a scatterplot with the data points and the > predictions from the regression. > > Sigma <- matrix(c(1,.6,1,.6), 2) > mu <- c(0,0) > dat <- mvrnorm(5000, mu, Sigma) > > x <- dat[,1] * 50 + 200 > y <- dat[,2] * 50 + 200 > > fm <- lm(y ~ x) > > ### This gives the regression line, but not the data > xyplot(y ~ x, > type = c('g', 'p'), > panel = function(x, y){ > panel.lines(x, predict(fm)) > } > ) > > ### This gives both data but as point > xyplot(y + predict(fm) ~ x, > type = c('g', 'p'), > ) > > I know I can add an abline easily, but my problem is a bit more complex and > the code above is just an example. > What is the best way for the predicted data to form a solid line and let the > data points remain as points
See http://lattice.r-forge.r-project.org/Vignettes/src/lattice-tricks/regression-lines.pdf (This is a work in progress, so feedback would be appreciated.) -Deepayan ______________________________________________ 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.