Hello I'm trying to calculate 2d confindence bounds into a scatterplot using the function "kde2d" (package MASS) and a contour plot.
I found a similar post providing a solution - unfortunatly I do not realy understand which data I have to use to calculated the named "quantile": Post URL: http://tolstoy.newcastle.edu.au/R/help/03b/5384.html > (...) > >> 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 >(...) -- Example: x <- rnorm(1000, mean = 0, sd = 1) y <- rnorm(1000, mean = 1, sd = 1.3) kerneld <- kde2d(x, y, n = 200, lims = c(-1.0, 1.0, 0.0, 2.0)) confidencebound <- quantile(kerneld$z, probs= 0.95) plot(x, y, pch=19, cex=0.5) contour(kerneld, levels = confidencebound, col="red", add = TRUE) -- How can I calculate the right contour containing 95% of the values? Thank's for your help. Pascal R 2.7.0, Win XP -- Pascal Hänggi Universität Bern Geographisches Institut, Gruppe für Hydrologie Hallerstrasse 12 CH-3012 Bern +41 (0)31 631 54 71 [EMAIL PROTECTED] http://www.hydrologie.unibe.ch -- ______________________________________________ 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.
