On Wed, 2009-08-19 at 13:49 -0700, Bert Gunter wrote: > Rolf: > > Not sure what "reasonably thorough" means but: > > ? boxplot says:
Exactly Bert, the info is there is you want to look and do so hard enough. However, it is perhaps expecting quite a lot of a new useR to put this together from ?boxplot or ?bxp, and ?boxplot.stats. Criticising correct, if cryptic or highlevel, responses to a list where people give their time for free, *and* not provide a more complete solution is unfair, Rolf. The OP is free to respond and ask for additional help once they've given it a go if they are still having trouble.. One solution, if you are prepared to bastardise the standard interpretation of the boxplot, is to compute the relevant boxplot statistics using boxplot.stats and alter argument 'coef' to some larger multiple of the box height to represent "extreme" outliers, whatever those might be. So here's the rope, try not to hang yourself 'Rnewbie'! set.seed(1234) dat <- rt(100, df = 2) bxp1 <- boxplot.stats(dat) bxp2 <- boxplot.stats(dat, coef = 2) ##Then you'd need to plot the boxplot without outliers boxplot(dat, outpch = NA) ##Then plot the points 1.5-2 x box height want <- bxp1$out %in% bxp2$out out <- bxp1$out out[want] <- NA points(rep(1, length(out)), out, pch = 1, col = "blue") ##Then the further outliers outout <- bxp2$out points(rep(1, length(outout)), outout, pch = 2, col = "red") How one decides what is an outlier or an extreme outlier is another matter...? By chance the dummy data here shows one problem; there isn't much difference between 'outliers' and 'extreme outliers' towards the bottom of the resulting plot so why should we distinguish them? (By the way 'Rnewbie', this isn't something I recommend you do, but you might know more about your real world use case than I.) HTH G Ps; is there a reason why you post anonymously, 'Rnewbie'? Do you not want us to know who you are, but want our help? > > ... > pars a list of (potentially many) more graphical parameters, e.g., boxwex > or outpch; these are passed to bxp (if plot is true); for details, see > there. > > > Well, that seems pretty clear to me, so I went to ?bxp to find in the pars > listing: > > outlty, outlwd, outpch, outcex, outcol, outbg: > outlier line type, line width, point character, point size expansion, color, > and background color. The default outlty= "blank" suppresses the lines and > outpch=NA suppresses points. > > > It seems to me that this (and other omitted excerpts + examples) is at least > a reasonable answer to the query (allowing the reader to at least infer that > bxp does not distinguish degrees of outlyingness), so I don't understand > your criticism. Feel free to respond privately if you prefer. > > -- Bert > > Bert Gunter > Genentech Nonclinical Biostatisics > > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On > Behalf Of Rolf Turner > Sent: Wednesday, August 19, 2009 1:27 PM > To: ottorino-luca.pant...@unifi.it > Cc: Rnewbie; ERRE > Subject: Re: [R] mild and extreme outliers in boxplot > > > On 20/08/2009, at 3:13 AM, Ottorino-Luca Pantani wrote: > > > Rnewbie ha scritto: > >> dear all, > >> > >> could somebody tell me how I can plot mild outliers as a circle(°) > >> and > >> extreme outliers as an asterisk(*) in a box-whisker plot? > >> > >> Thanks very much in advance > >> > > ?boxplot > > > > or > > > > help(bxp) > > This is the sort of response that gives R-help a bad name. > > I had a reasonably thorough look at these help files and saw > ***nothing*** > that would answer the OP's question. The information may be there > --- I'm > not sure about this --- but it is far from obvious. Explicit reference > to the appropriate lines of the help file(s) would be useful. > > cheers, > > Rolf Turner > ###################################################################### > Attention: > This e-mail message is privileged and confidential. 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