Sorry for the wrong placing of my last email. Here a solution to my problem and incomprehension respectively:
# Example 95% x <- rnorm(1000, mean = 0, sd = 1) y <- rnorm(1000, mean = 1, sd = 1.3) kerneld <- kde2d(x, y, n = 100, lims = c(-5.0, 5.0, -5.0, 5.0)) pp <- array() for (i in 1:1000){ z.x <- max(which(kerneld$x < x[i])) z.y <- max(which(kerneld$y < y[i])) pp[i] <- kerneld$z[z.x, z.y] } confidencebound <- quantile(pp, 0.05, na.rm = TRUE) plot(x, y, pch = 19, cex = 0.5) contour(kerneld, levels = confidencebound, col = "red", add = TRUE) # Test test <- array() kerneld.xy <- contourLines(kerneld, levels = confidencebound) for (i in 1:1000) { test[i] <- inside(list(x = x[i], y = y[i]), list(x = kerneld.xy[[1]]$x, y = kerneld.xy[[1]]$y)) } sum(test)/1000 -- Pascal Hänggi Universität Bern Geographisches Institut, Gruppe für Hydrologie Hallerstrasse 12 CH-3012 Bern +41 (0)31 631 54 71 [EMAIL PROTECTED] http://www.hydrologie.unibe.ch -- -----Ursprüngliche Nachricht----- Von: Pascal Hänggi [mailto:[EMAIL PROTECTED] Gesendet: Mittwoch, 25. Juni 2008 17:38 An: 'r-help@r-project.org' Betreff: confidence bounds using contour plot Hello I'm trying to calculate 2d confindence bounds into a scatterplot using the function "kde2d" (package MASS) and a contour plot. I found a similar post providing a solution - unfortunatly I do not realy understand which data I have to use to calculated the named "quantile": Post URL: http://tolstoy.newcastle.edu.au/R/help/03b/5384.html > (...) > >> Is there a way to plot a contour (empirical?) containing, say, 95% of the >> values. > >Yes. You need a 2D density estimate (e.g. kde2d in MASS) then compute the >density values at the points and draw the contour of the density which >includes 95% of the points (at a level computed from the sorted values via >quantile()). > >-- >Brian D. Ripley >(...) -- Example: x <- rnorm(1000, mean = 0, sd = 1) y <- rnorm(1000, mean = 1, sd = 1.3) kerneld <- kde2d(x, y, n = 200, lims = c(-1.0, 1.0, 0.0, 2.0)) confidencebound <- quantile(kerneld$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.