Well, I'd guess you have to first define what you mean by "prediction ellipse," as the confidence ellipses are for the bivariate distribution of 2 parameter estimates -- as I understand it -- whereas predictions depend on the covariate values and are for a single response value (unless you have fitted multiple responses, I suppose).
-- Bert On Sat, Jan 26, 2013 at 1:12 PM, Giuseppe Amatulli <giuseppe.amatu...@gmail.com> wrote: > Hi, > I'm using the R library(car) to draw confidence/prediction ellipses in a > scatterplot. > >From what i understood the ellipse() function return an ellipse based > parameters: shape, center, radius . > If i read dataEllipse() function i can see how these parameters are > calculated for a confidence ellipse. > > ibrary(car) > > a=c(12,12,4,5,63,63,23) > b=c(13,15,7,10,73,83,43) > > v <- cov.trob(cbind(a, b)) > shape <- v$cov > center <- v$center > > radius <- sqrt(2 * qf(0.95, 2, length(a) - 1)) # radius <- sqrt(dfn * > qf(level, dfn, dfd)) > > conf.elip = ellipse(center, shape, radius,draw = F) > plot(conf.elip, type='l') > points(a,b) > > My question is how I can calculate shape, center and radius to obtain a > prediction ellipses rather than a confidence ellipse? > Thanks in Advance > Giuseppe > > -- > Giuseppe Amatulli > Web: www.spatial-ecology.net > > [[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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ 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.
