similar to: R-beta: CI for median in funtion boxplot

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Hello, I know this has been covered on here before, but as a complete novice, I need a little more guidance. I would like to produce boxplots with the whiskers extending to the 10 and 90th percentiles. I found this code: myboxplot.stats <- function (x, coef = NULL, do.conf = TRUE, do.out = TRUE) { nna <- !is.na(x) n <- sum(nna) stats <- quantile(x, c(.1,.25,.5,.75,.9), na.rm

I really like the ease of use with the boxplot command in R. I would rather have a boxplot that shows the average value and the standard deviation then the median value and the quartiles. Is there a way to do this? Chad Junkermeier, Graduate Student Dept. of Physics West Virginia University PO Box 6315 210 Hodges Hall Morgantown WV 26506-6315 phone: (304) 293-3442 ext. 1430 fax: (304)

Sorry to repost this, but it looks like it's getting buried in r-help (originally posted October 5: my experience says that if it hasn't been answered by then it won't be). I wouldn't bother, but I'm worried that r-devel might be better, *and* a previous e-mail of mine on the subject in January also seemed to get buried. Synopsis: boxplot notches look weird when notches are

Hello to all users and wizards. I am regulary using 'boxplot' function or its analogue - 'bwplot' from the 'lattice' library. But they are, as far as I understand, totally flawed in functionality: they miss ability to select what they would draw 'in the middle' - median, mean. What the box means - standard error, 90% or something else. What the whiskers mean -

Dear guRus, I want to do some boxplots, but the median sould appear in another line-thickness and another color. I do not know, what to do in order to realise my wishes. Sorry for that question, but I am new to R. cheers steph -- Linux: the operating system with a CLUE... Command Line User Environment. -------------------------------------- Stephan Holl GnuPG Key-ID: 11946A09 ICQ#

Dear list members, Can anyone tell me how the notches in boxplot(Y~X,notch=T) are calculated? What do these notches represent exactly? I?d suppose they are Conficence Intervals for the median, but I?ve also been told they might show Least Significant Difference (LSD) equivalents. I would very much appreciate any help from you. Best regards Chris.

Hi all, I'm just getting started with R and I would appreciate some help. I'm having trouble creating a boxplot with whiskers at the 95th and 5th percentiles instead of at 1.5 * IQR. I have read the relevant documentation, and checked existing mails on this topic. I found a small modification that should work : https://stat.ethz.ch/pipermail/r-help/2001-November/016817.html and tried to

Hi, set.seed(45) test1<-data.frame(columnA=rnorm(7,45),columnB=rnorm(7,10)) #used an example probably similar to your actual data apply(test1,2,function(x) sprintf("%.1f",median(x))) #columnA columnB # "44.5"? "10.2" par(mfrow=c(1,2)) lapply(test1,function(x) {b<-

Is there a way to modify the choice of notch size [1] in R's boxplot routine from outlining a 5% significance region, to say 1% or lower? Thanks, Alex [1] McGill, Tukey, and Larsen. "Variations of Box Plots", The American Statistician, Vol. 32, No. 1, 12-16.

dear R experts: I am playing with boxplots for the first time. most of it is intuitive, although there was less info on the web than I had hoped. alas, for some odd reason, my R boxplots have some fat black dots, not just the hollow outlier plots. Is there a description of when R draws hollow vs. fat dots somewhere? [and what is the parameter to change just the size of these dots?] Also, let

PR #7690 points out that if the confidence intervals (+/-1.58 IQR/sqrt(n)) in a boxplot with notch=TRUE are larger than the hinges -- which is most likely to happen for small n and asymmetric distributions -- the resulting plot is ugly, e.g.: set.seed(1001) npts <- 5 X <- rnorm(2*npts,rep(3:4,each=npts),sd=1) f <- factor(rep(1:2,each=npts)) boxplot(X~f) boxplot(X~f,notch=TRUE) I can

Dear all, I constructed this function called my.boxplot.stats by replacing fivnum() with quantile() in function boxplot.stats(). So I can try different quantile methods in bwplot(). The problem is I couldn't pass different values to the "type" argument to my.boxplot.stats, which in turn is an argument in bwplot(). Now I just have to manually change the "type" value in

Dear R-users, Does anyone knows how I can order my serie of boxplots from lowest to highest median (which is much better for visualization purposes). thanks in advance, willem [[alternative HTML version deleted]]

Dear List, I'd like to make boxplots of a large number of observations (+/- 20.000), which are distributed log-normal and right skewed. The problem is that with standard boxplots a too large number of observations are displayed as outliers. I also tried to display the log of the observations, but even then there are to may outliers to my taste. So I'd like to change the standard IQR box

A function I've been using for a while returned a surprising [to me, given the data] error recently: Error in plot.window(xlim, ylim, log, asp, ...) : Logarithmic axis must have positive limits After some digging I realized what was going on: x <- c(10460.97, 10808.67, 29499.98, 1, 35818.62, 48535.59, 1, 1, 42512.1, 1627.39, 1, 7571.06, 21479.69, 25, 1, 16143.85, 12736.96,

How are the lower/upper whiskers defined in the default version of boxplot {graphics}? I tried help(boxplot) and searching www.rseek.org, but I was unable to determine an absolute answer. I checked out the definition of boxplot according to Wikipedia (http://en.wikipedia.org/wiki/Box_plot), but it also had several approaches listed for how the whiskers could be determined, so I'm just

Hello R-Help, Could anybody tell me how the boxplot-function calculates the upper and lower extremes of the notch contained in $conf which I assume is the confidence interval? Is it reliable for data which is not normally distributed? If not, how can I calculate and boxplot a specific confidence interval for not normally distributed data in R (increasing the sample size does not normalize the

I am trying to draw a plot like Matlab does: The upper extreme whisker represents 95% of the data; The upper hinge represents 75% of the data; The median represents 50% of the data; The lower hinge represents 25% of the data; The lower extreme whisker represents 5% of the data. It looks like: --- 95% | | ------- 75% | | |-----| 50% | | | | -------

I am very new to R so forgive me if this seems basic but I have done extensive searching and failed to come up with the answer for myself. I am trying to label a boxplot I have created with the values for the median, upper and lower quartiles and max and min values. I have been unable to do this or find anything on the net to say how it might be done. Is this possible and if so how? Regards,