On Tue, 28 Oct 2003, Tanya Murphy wrote: > Hello, > > SAS' point and click interface has the option of produce a scatterplot with a > superimposed confidence ellipse for the correlation coefficient. Since I > generally like R so much better, I would like to reproduce this in R. I've > been playing with the ellipse package. In order to have the points and the > ellipse on the same graph I've done the following. > (Load ellipse package...) > > data(Puromycin) > > attach(Puromycin) > > my<-mean(rate) > > mx<-mean(conc) > > sdy<-sd(rate) > > sdx<-sd(conc) > > r<-cor(conc,rate) > > plot(ellipse(r,scale=c(sdx,sdy),centre=c(mx,my)),type='l') > > points(conc,rate) > > 1) Is my use of 'scale' and 'centre' theoretically correct?
Depends on whose theory you have in mind! This is not `a confidence ellipse for the correlation coefficient', as confidence ellipses are for pairs of parameters, not variables. It seems to be a plot of a contour of the fitted bivariate normal. > 2) Is there a more efficient way to get the 5 parameters? (I guess I could > write a little function, but has it already been done?) You could do things like mxy <- mean(Puromycin[c("rate", "conc")]) sxy <- sapply(Puromycin[c("rate", "conc")], sd) > The non-linear relationship between these variables brings up another point: > Is there a way to plot a contour (empirical?) containing, say, 95% of the > values. Yes. You need a 2D density estimate (e.g. kde2d in MASS) then compute the density values at the points and draw the contour of the density which includes 95% of the points (at a level computed from the sorted values via quantile()). -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help