similar to: boxplot, notches, etc.

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,

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 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.

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

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

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

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

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.

Hey hey, I`m analyzing a data set containing the element contentrations of various samples... I wanted to construct notched boxplots and got quite ugly results for some of the boxplots. The notches are often larger then the hinges which resulted in weird looking edges (even though I`m using a log-boxplot). To avoid this problem I thought about using "normal" log-boxplots and adding some

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!

Hi, I have data that looks like this: ASA1 ASA2 C1_C2 C M 9.0225 S S 2.4315 M C 3.4894 M S 4.5282 C M 1.3183 C S 1.3735 S C 1.0488 S M 7.948 M C 4.5827 I need to plot Boxplots for a given ASA1 (either C,S, or M) with respect to C1_C2. However, instead of one boxplot I want to plot

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

I need to find the area under a trapezoid for a research-related project. I was able to find the area under the trapezoid in MATLAB using the code: function [int] = myquadrature(f,a,b) % user-defined quadrature function % integrate data f from x=a to x=b assuming f is equally spaced over the interval % use type % determine number of data points npts = prod(size(f)); nint = npts -1; %number of

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.

I have found some "issues" (bugs?) with nls confidence intervals ... some with the relatively new "port" algorithm, others more general (but possibly in the "well, don't do that" category). I have corresponded some with Prof. Ripley about them, but I thought I would just report how far I've gotten in case anyone else has thoughts. (I'm finding the code

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 <-

Hi, I have two questions want to ask. 1. If I have a matrix like this, and I want to figure out the rows whose value in the 3rd column are less than 0.05. How can I do it with R. hsa-let-7a--MBTD1 0.528239197 2.41E-05 hsa-let-7a--APOBEC1 0.507869409 5.51E-05 hsa-let-7a--PAPOLA 0.470451884 0.000221774 hsa-let-7a--NF2 0.469280186 0.000231065 hsa-let-7a--SLC17A5

[posted to R-devel, no discussion: resubmitting it as a bug, just so it gets logged appropriately] Sorry to report further difficulties with nls and profiling and constraints ... the problem this time (which I didn't check for in my last round of testing) is that the nls profiler doesn't seem to respect constraints that have been set when using the port algorithm. See test code

Dear R Users, I've never used R before and my professor has asked us to do some pretty intense programming (or it's intense to me at least). Here is the question: Modify the function myquadrature inside the script so that it returns the quadrature of descrete data using the trapezoidal rule. Modify the call to the function at the bottom of the script so that is uses your modifies

I have a seasonal time series. I want to calculate the annual mean value of the time series at its peak (say the mean of the three values before the peak, the peak, and the three values after the peak). The peak of the time series might change cycle slightly from year to year. # E.g., nPts <- 254 foo <- sin((2 * pi * 1/24) * 1:nPts) foo <- foo + rnorm(nPts, 0, 0.05) bar <- ts(foo,