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.
