On 12/18/2007 12:44 PM, Antony Unwin wrote: > On 18 Dec 2007, at 4:49 pm, Duncan Murdoch wrote: > >>> One good alternative here is the fluctuation diagram variant of a >>> mosaic plot: >>> xx<-as.factor(x) >>> yy<-as.factor(y) >>> imosaic(xx,yy, type="f") >> >> That plot is better than jittering, but there's the problem in the >> mosaic plot of understanding the scale of the rectangles: is it >> area or diameter that encodes the count? > > Area is used. > >> With a jittered plot, you lose resolution when the number of points >> gets too high because you just see a mess of ink, but at least you >> only require the viewer to count in order to get a close numerical >> reading from the plot. > > If someone needs a count, they should be given a table. Graphics > are for qualitative conclusions not details. Anyway, counting will > only work for really small datasets. > >> I could also claim that while imperfect, at least jittering is >> widely applicable. For example, if the data were not on a regular >> grid, perhaps because they had been generated like this: >> >> xloc <- rnorm(50) >> yloc <- rnorm(50) >> index <- sample(1:50, 5000, rep=TRUE, prob = abs(xloc)) >> x <- xloc[index] >> y <- yloc[index] >> >> then jittering still works as well (or as poorly), but the imosaic >> would not work at all. > > That's right and that's (almost) the sort of example I was thinking > of. For a limited number of locations like this a bubble plot would > be best (which has already been suggested in this thread, I think). > For many locations and few replications I would still go for varying > pointsize and transparency. > > Incidentally, to check your suggestion I ran your code and discovered > that the transparency in iplot does not seem to like replications. > Very strange, we'll have to check why. I then looked closely at the > numbers of replications generated and discovered that case 25 was > picked 325 times and case 40 only once. Rather too extreme for my > liking! Running it again gave very similar results, though not > exactly the same: this time it was 325 times for case 25 and case 40 > was not picked at all. Other numbers varied slightly. This is not > what I expected, any ideas?
abs(xloc) typically varies by a factor of about 100 from smallest to largest, but sometimes the small end is really small, and so the ratio is really big. Duncan Murdoch > >> P.S. iplots 1.1-1 may have an init problem in Windows: in my first >> attempt, the plot made the boxes too large to fit in their cells, >> but it fixed itself when I resized the window, and the bug doesn't >> seem to be repeatable. > > Thanks. This happens occasionally on the Mac too. Refreshing solves > it in practice, but we need to find out why it can happen (and stop > it happening!). > > Antony Unwin > Professor of Computer-Oriented Statistics and Data Analysis, > University of Augsburg, > Germany ______________________________________________ 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.
