similar to: "open-ended" plot limits?

Greetings, Folks. I'd appreciate being shown the way out of this one! I've been round the documentation in ever-drecreasing circles, and along other paths, without stumbling on the answer. The background to the question can be exemplified by the example (no graphics window open to start with): set.seed(54321) X0 <- rnorm(50) ; Y0 <- rnorm(50)

Hi, I would like to draw 10 uniformly distributed sample points from a circle with redius one and centered at (0,0). Is there any R function to do that?   Thanks, [[alternative HTML version deleted]]

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Greetings! I would like to be able to specify a fixed (say) lower limit for plotting, while leaving the upper limit "floating, when plotting. The context is that the maximum in the data to be plotted is unpredictable, being the consequence of a simulation, whereas I know that it cannot be less than (say) 0; and I want to fix the lower limit at 0 in any plot, leaving the upper limit to be

Hi all, all.equal is generally very useful when you want to find the differences between two objects. It breaks down however, when you have two long strings to compare: > all.equal(a, b) [1] "1 string mismatch" Does any one know of any good text diffing tools implemented in R? Thanks, Hadley -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / Rice

I've looked long and hard for this, but maybe I am missing something... There is a nice module that displays histograms reflected in the y axis, i.e. http://addictedtor.free.fr/graphiques/RGraphGallery.php?graph=136 but is it possible to reflect in the x-axis, so to have two datasets, one pointing up and one down rather than left and right? I haven't been able to find a way to plot this

Hi Folks, I'm wondering if there's a compact way to achieve the following. The "dream" is that, by analogy with rep(c(0,1),times=c(3,4)) # [1] 0 0 0 1 1 1 1 one could write rep(c(0,1),times=c(3,4,5,6)) which would produce # [1] 0 0 0 1 1 1 1 0 0 0 0 0 1 1 1 1 1 1 in effect "recycling" x through 'times'. The objective is to produce a vector of

Hello all, This is something that I am sure has a really suave solution in R, but I can't quite figure out the best (or even a basic) way to do it. I have a simple linear regression that is fit with lm for which I would like to estimate the x intercept with some measure of error around it (confidence interval). In biology, there is the concept of a developmental zero - a temperature under

Hello, This is a problem for which there seem to be several solutions online, but not really. My question was about plotting a curve over the histogram. All the previous posts and messages talk about generating a *density histogram*using (freq=F) and then plotting the density curve. However, I find that that seriously distorts my data and the plot becomes confounding to the viewer. I was

Greetings All, Out of curiosity, I've just done a very primitive experiment: Obj <- list(Fun=sum, Dat=c(1,2,3,4)) Obj$Fun(Obj$Dat) # [1] 10 That sort of thing (much more sophisticated) must be documented mind-blowingly somewhere. Where? Where I stand right now: The above (and its immediately obvious generalisations, like Obj$Fun<-cos) is all I know about it so far. Ted.

Hi Folks, I'm running Debian-4.0 Etch, installed last September from a DVD, and regularly updated as things arise. I have R version 2.4.0 Patched (2006-11-25 r39997) installed (initially at the time of first installation of Debian, as provided by Debian), along with a variety of packages. I'd like to be able to connect to the CRAN repositories for Debian R, for updates etc. When I visit

I am interested in studying the binary representation of numerics (doubles) in R, so am looking for possibilities of output of the internal binary representations. sprintf() with format "a" or "A" is halfway there: sprintf("%A",pi) # [1] "0X1.921FB54442D18P+1" but it is in hex. The following illustrate the sort of thing I want: 1.1001 0010 0001 1111

Hi Folks, I'm comparing some output from R with output from SPSS. The coefficients of the independent variables (which are all factors, each at 2 levels) are identical. However, R's Intercept (using default contr.treatment) differs from SPSS's 'constant'. It seems that the contrasts were set in SPSS using /CONTRAST (varname)=Simple(1) I can get R's Intercept to match

sorry but how do i accsess r archives __________________________________________________ [[alternative HTML version deleted]]

Hi Folks, I'm advising someone who's a beginner with R, and therefore wants the simplest answer possible. The issue is to produce a plot using plot(x,y,...) where, on the X-axis, the tick-marks should be on the lines of: -- Range of X-axis: 0:1000 -- tick-marks labelled "0","200",...,"800","1000" -- unlabelled tick-marks every 50 from 0 to

I just installed R on my 64 bit SUSE Linux system -- I compiled with the default x windows support on.. This may be a newbie question (apologies in advance)-- but how does this show up in X? I have SSH'd in to my box and set my display -- I can run xcalc OK -- but when I hit the R binary it just goes to the command line -- if does not give me an x-window. I suspect I need another

Hi again! Following up my previous posting below (to which no response as yet), I have located a report which situates this type of question in a longitudinal modelling context. http://www4.stat.ncsu.edu/~dzhang2/paper/glm.ps Generalized Linear Models with Longitudinal Covariates Daowen Zhang & Xihong Lin (This work seems to originally date from around 1999). They consider an outcome Y,

Hi Folks, Apologies to anyone who'd prefer not to see this query on this list; but I'm asking because it is probably the forum where I'm most likely to get a good answer! I'm interested in the provenance of the name "normal distribution" (for what I'd really prefer to call the "Gaussian" distribution). According to Wikipedia, "The name "normal

Hi Folks, Quick question. I have the following line in an R code file which runs fine on Linux: if(PNG) png(GraphName,width=12,height=15,units="cm",res=200) I learn that, when the same code was run on a Windows machine, there was the following error: Error in png(GraphName,width=12,height=15,units="cm",res=200): unused argument(s) (units = "cm") Sorry to

Hi Folks, I'd like to know how hist() decides how many cells to use when it ignores my "suggestion" to use say 'hist(...,breaks=50)'. More specifically, I have the results of 10000 simulations, each returning an 8-vector, therefore 8 variables each with 10000 values. Some of these 8 have somewhat skew distributions. Say one of these 8 variables is X. I ask for H <-