The origin of this problem was that a plain scatter plot with too many points with high dispersion generated too many points flying all over places.
We are trying to smooth the charts a bit... Any good recommendations? Thanks a lot! On Fri, Mar 9, 2012 at 8:59 PM, Michael <comtech....@gmail.com> wrote: > Sorry for the confusion Michael. > > I myself am trying to figure out what my boss is requesting: > > I am certain that I need to "plot the quantiles of each bin. " ... > > But how are the quantiles plotted? Shall I specify 50% quantile, etc? > > Being a diligent guy I am trying my hard to do some homework and figure it > out myself... > > I thought there is a standard statistical prodedure that everybody knows... > > Any more thoughts? > > Thanks a lot! > > > On Fri, Mar 9, 2012 at 8:51 PM, R. Michael Weylandt < > michael.weyla...@gmail.com> wrote: > >> On Fri, Mar 9, 2012 at 9:28 PM, Michael <comtech....@gmail.com> wrote: >> > Thanks a lot Mike! >> > >> >> Michael if you don't mind. (Though admittedly it leads to some degree >> of confusion in a conversation like this) >> >> > Could you please explain your code a bit? >> >> Which part? >> >> > >> > My imagination is that for each bin, I am plotting a line which is the >> > quantile of the y-values in that bin? >> >> Oh, so you want a qqnorm()-esque line? How is that like a scatterplot? >> >> ....yes, that's something else entirely (and not clear from your first >> post -- to my ear the "quantile" is a statistic tied to the [e]cdf) >> This is actually much easier in ggplot (and certainly doable in base >> as well) >> >> Try this, >> >> DAT <- data.frame(x = runif(1000, 0, 20), y = rnorm(1000)) # Not so >> volatile this time >> DAT$xbin <- with(DAT, cut(x, seq(0, 20, 5))) >> >> library(ggplot2) >> p <- ggplot(DAT) + facet_wrap( ~ xbin) + stat_qq(aes(sample = y)) >> >> print(p) >> >> If this isn't what you want, please spend some time to show an example >> of the sort of graph you desire (it can be a bit of code or a link to >> a picture or even a hand sketch hosted somewhere online) >> >> Out on a limb, I think you might really be thinking of something more >> like this: >> >> p <- ggplot(DAT) + facet_wrap( ~ xbin) + geom_step(aes(x = >> seq_along(y), y = sort(y))) >> >> and see this for more: http://had.co.nz/ggplot2/geom_step.html >> >> Michael Weylandt >> >> > >> > I ran your program but couldn't figure out the meaning of the dots in >> your >> > plot? >> > >> > Thanks again! >> > >> > On Fri, Mar 9, 2012 at 7:07 PM, R. Michael Weylandt >> > <michael.weyla...@gmail.com> wrote: >> >> >> >> That doesn't really seem to make sense to me as a graphical >> >> representation (transforming adjacent y values differently), but if >> >> you really want to do so, here's what I'd do if I understand your goal >> >> (the preprocessing is independent of the graphics engine): >> >> >> >> DAT <- data.frame(x = runif(1000, 0, 20), y = rcauchy(1000)^2) # Nice >> >> and volatile! >> >> >> >> # split y based on some x binning and assign empirical quantiles of >> each >> >> group >> >> >> >> DAT$yquant <- with(DAT, ave(y, cut(x, seq(0, 20, 5)), FUN = >> >> function(x) ecdf(x)(x))) >> >> >> >> # BASE >> >> plot(yquant ~ x, data = DAT) >> >> >> >> # ggplot2 >> >> library(ggplot2) >> >> >> >> p <- ggplot(DAT, aes(x = x, y = yquant)) + geom_point() >> >> print(p) >> >> >> >> Michael Weylandt >> >> >> >> PS -- I see Josh Wiley just responded pointing out your requirements >> >> #1 and #2 are incompatible: I've used 1 here. >> >> >> >> On Fri, Mar 9, 2012 at 7:37 PM, Michael <comtech....@gmail.com> wrote: >> >> > Hi all, >> >> > >> >> > I am trying hard to do the following and have already spent a few >> hours >> >> > in >> >> > vain: >> >> > >> >> > I wanted to do the scatter plot. >> >> > >> >> > But given the high dispersion on those dots, I would like to bin the >> >> > x-axis >> >> > and then for each bin of the x-axis, plot the quantiles of the >> y-values >> >> > of >> >> > the data points in each bin: >> >> > >> >> > 1. Uniform bin size on the x-axis; >> >> > 2. Equal number of observations in each bin; >> >> > >> >> > How to do that in R? I guess for the sake of prettyness, I'd better >> do >> >> > it >> >> > in ggplot2? >> >> > >> >> > Thank you! >> >> > >> >> > [[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<http://www.r-project.org/posting-guide.html> >> >> > and provide commented, minimal, self-contained, reproducible code. >> > >> > >> > > [[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.
