Hi all, I have been looking for means of add a contour around some points in a scatterplot as a means of representing the center of density for of the data. I'm imagining something like a 95% confidence estimate drawn around the data.
So far I have found some code for drawing polygons around the data. These look nice, but in some cases the polygons are strongly influenced by outlying points. Does anyone have a thought on how to draw a contour which is more along the lines of a 95% confidence space? I have provided a working example below to illustrate the drawing of the polygons. As I said I would rather have three "ovals"/95% contours drawn around the points by "level" to capture the different density distributions without the visualization being heavily influenced by outliers. I have looked into the code provided here from Hadley https://groups.google.com/forum/?fromgroups=#!topic/ggplot2/85q4SQ9q3V8 using the mvtnorm package and the dmvnorm function, but haven't been able to get it work for my data example. The calculated densities are always zero (at this step of Hadley's code: dgrid$dens <- dmvnorm(as.matrix(dgrid), ex_mu, ex_sigma) ) I appreciate any assistance. Thanks, Nate x<-c(seq(0.15,0.4,length.out=30),seq(0.2,0.6,length.out=30), seq(0.4,0.6,length.out=30)) y<-c(0.55,x[1:29]+0.2*rnorm(29,0.4,0.3),x[31:60]*rnorm(30,0.3,0.1),x[61:90]*rnorm(30,0.4,0.25)) data<-data.frame(level=c(rep(1, 30),rep(2,30), rep(3,30)), x=x,y=y) find_hull <- function(data) data[chull(data$x, data$y), ] hulls <- ddply(data, .(level), find_hull) fig1 <- ggplot(data=data, aes(x, y, colour=(factor(level)), fill=level))+geom_point() fig1 <- fig1 + geom_polygon(data=hulls, alpha=.2) fig1 [[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.
