I wish to compare the observed values to the fitted ones. To do so, I decided to use a plot in R. What I want to do is to plot X vs Y and X vs Y.fitted on the same plot. I have written some code, but it is incomplete. My plot needs to look like this one below. On the plot, circles and crosses represent the observed and fitted values respectively
set.seed(1) x <- runif(8,0,1) y <- runif(8,0,1) y.fitted <- runif(8,0,1) plot(x,y,pch=1) plot(x,y.fitted,pch=5) In your code, the second plot will not add points to the existing plot but create a new one. You can + use the function points to add points to the existing plot.
plot(x, y, pch = 1) points(x, y.fitted, pch = 4) 
running plot the second time will create a new one. You could use points
set.seed(1) x <- runif(8,0,1) y <- runif(8,0,1) y.fitted <- runif(8,0,1) plot(x,y,pch=1) points(x,y.fitted,pch=5) 
A solution with ggplot2 giving a better and neat graph outlook:
library(ggplot2) df = data.frame(x=runif(8,0,1),y=runif(8,0,1),y.fitted=runif(8,0,1)) df = melt(df, id=c('x')) ggplot() + geom_point(aes(x=x,y=value, shape=variable, colour=variable), df) 
aes in the geom_points layer, I think the better habit is to put it in the ggplot call, thereby making it accessible to any other layer you might want to add. In this case you get the same result though.melt a library is needed, reshape2 ?