similar to: too-large notches in boxplot (PR #7690)

Dear all, I am a total beginner in R, so sorry if this is the wrong place. I am using R 2.10.1 on a Mac (Mac OS 10.6.2). I have this small dataset : growth sugar 75 C 72 C 73 C 61 F 67 F 64 F 62 S 63 S I have no problem reading the table, or getting the summary, but if I try boxplot(growth~sugar, ylab="growth", xlab="sugar", data=Dataset), I have the following error :

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

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,

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

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

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,

Hi all, I would like to draw a side by side bar plot.  How can I adjust the the font size for the x-axis?  Furthermore, I'm not sure what to write for 'at=?'.  I tried cex.axis and cex.lab but still fail.  Here is my data and code:   > t(all)            0-100 100-150  150-200 200-250 250-300 300-350 350-400 400-620 obs_data 382.000 177.000 156.0000    93.0 69.0000  45.000

[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

Was there ever a convenient method provided to add boxplots to the current plot at specified x values? There was a question by Martin Maechler some time ago here, but I could seem to find any satisfactory resolution of it. I see that there is an add=T option to boxplot and bxp, but I don't see how to set the x-values. url: http://www.econ.uiuc.edu Roger Koenker email roger at

Dear All - The problem: comment lines in an R function (lines beginning with # ) are *sometimes* removed on leaving the R default editor (same with notepad). I'm working on a Windows machine with R version 2.14.1. An example is below. Couldn't find anything that seemed to relate to this in the Changelog. I don't recall encountering this behavior with previous versions of R. Any

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 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

Hi all! I would like to import a matlab or gauss code to R. Could you help me? Bye, Sebasti?n. 2007/6/23, r-help-request en stat.math.ethz.ch <r-help-request en stat.math.ethz.ch>: > Send R-help mailing list submissions to > r-help en stat.math.ethz.ch > > To subscribe or unsubscribe via the World Wide Web, visit >

Hi, I'm using the R library(car) to draw confidence/prediction ellipses in a scatterplot. >From what i understood the ellipse() function return an ellipse based parameters: shape, center, radius . If i read dataEllipse() function i can see how these parameters are calculated for a confidence ellipse. ibrary(car) a=c(12,12,4,5,63,63,23) b=c(13,15,7,10,73,83,43) v <-

Im trying to ascertain whether or not the facilities of R are sufficient for solving an optimization problem I've come accross. Because of my limited experience with R, I would greatly appreciate some feedback from more frequent users. The problem can be delineated as such: A utility function, we shall call g is a function of x, n ... g(x,n). g has the properties: n > 0, x lies on the

Hi! I just started to use R recently, and would like to ask a help about automating the job. I need to use "kmeans" function with my own 300 data files, and wonder if it's possible to do it automatically. For example, > library (mva) > mydata <- read.table ("data1") > cl <- kmeans(mydata, 5, 20) and I just need to save "cl" info (i.e. the center

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 below ... If I can I will try to hack the code, but I will probably start by redefining my function with

HI everyone, I''m trying to assign colors to multiple lines in a graph. Problem is I don''t want to type in as many colors as there are lines....is there a way around this? In brief, I''m plotting the logratio for up to 60 samples and want a different color for each sample. Here is the code I''m using now.. Any help is greatly appreciated.. Best LT data <-

Hi, We are testing a SIP solution * + ser solution for a large implementation. All the clients are nated. When a client is dialing outside the domain (to a FWD sip account for example) all is perfect ! ;-) But ,when a call is done to a sip account, the client is ringing, then the caller can hear the nated client very well, but the nated client does'nt hear anything. RTP issue no ? I've