similar to: boxplot notches

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

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

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.

Hi I'm getting a weird result when I try to switch from a normal box plot to a notched one. The ends of the box fold down toward the median giving a horned appearance. Is just the sample itself? It is small, but the un-notched plot looks okay. Anyway to fix this? e7=as.vector(c(234,37,98,116,47)) boxplot(e7, plot=TRUE, notch=TRUE) Thanks very much.

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,

Dear R-list, In the R-book, p.464, Michael Crawley recommends that error bars for bar plots of normally distributed continuous response variables with categorical explanatory variables be given by 1/2 of the least significant difference, where the least significant difference is defines as qt(0.975,degrees_of_freedom)*standard_error_of_the_difference. The idea is that the above quantity

Dear r-helpers, tst <- data.frame(as.numeric(x <- 1:20), f <- rep(c('hi','lo'), times = 10)) with(tst, bwplot(f ~ x, panel = function(x, y){panel.bwplot(x, y, pch = '|', stats = boxplot.stats, fill = 8, varwidth = T)})) I can't figure out from the documentation how to tell stats that I would like to see notches or (even bands). Here is what I've

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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

Another naive stats question. I'm trying to better understand what boxplots are telling me. I think what I see is the median and the boundaries of the 1st and 3rd quartiles. The whiskers represent the range of the data unless there are points which are outside "range" (default: 1.5) times the distance from the median to that quartile. Is that right? I've read the

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

Dear List, I just googled to find out if notched box plots are possible with ggplot2, but couldn't find a answer to it. boxplot() has the option: notch = TRUE, e.g.: boxplot(mpg$hwy, notch=TRUE) My example code (taken from the net) is: require(ggplot2) qplot(class, hwy, fill=factor(year), data=mpg, geom="boxplot", position="dodge")+theme_bw() Thank you for you help!

I noticed that boxplot computes a 95% CI for the median by using median +/- 1.58*IQR./sqrt(n) Where does the 1.58 constant come from? -- Rick White Statistical Consultant U.B.C. Vancouver B.C. Canada rick at stat.ubc.ca -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

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)

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

Hello, I'm using the code below to generate some notched box plots. The issue is whenever I use log scale, the sides of the bottom part of the box plots don't plot. I've tried it in RStudio Ver 1.1.419 and R version 3.4.3 and I get the same result. The code and link to my data is below. Thank you for your time David MyData <-

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

Hello, I have a set of one-liners (many thanks to previous responses from this list) that I use to look at newly imported data sets with functions like dim(), names(), str(), etc. within lapply(). Generally, these commands work for me but, I am apparently still missing some aspect of list manipulation. I don't understand why I get a set of NULL list elements at the end of each output as

Thanks a lot for the suggestions! I will look into using vld1/vst1, sounds good. I am custom lowering the bitcasts, that's now the only place where FP_TO_FP16 and FP16_TO_FP nodes are created to avoid inefficient code generation. I will double check if I can't achieve the same without using these nodes (because I really would like to get completely rid of them). Cheers, Sjoerd.

Hello, I have count data that illustrate the presence or absence of individuals in my study population. I created a grid cell across the study area and calcuated a count value for each individual per season per year for each grid cell. The count value is the number of time an individual was present in each grid cell. For illustration my data columns look something like this and are repeated for