similar to: suggestion for ?factor

Hi Folks, Maybe I've missed it already being available somehow, but if the following isn't available I'd like to suggest it. If you're happy to let plot() choose its own limits, then of course plot(x,y) will do it. If you know what limits you want, then plot(x,y,xlim=c(x0,x1),ylim(y0,y1) will do it. But sometimes one would like to a) make sure that (e.g.) the y-axis has a

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 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

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,

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

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, Compare print(1234567890,digits=4) # [1] 1.235e+09 print(1234567890,digits=5) # [1] 1234567890 Granted that digits: a non-null value for 'digits' specifies the minimum number of significant digits to be printed in values. how does R decide to switch from the "1.235e+09" (rounded to 4 digits, i.e. the minumum, in "e" notation) to

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

Hi Folks, I'm a bit puzzled by the following (example): N<-factor(sample(c(1,2,3),1000,replace=TRUE)) unique(N) # [1] 3 2 1 # Levels: 1 2 3 So far so good. Now: contrasts(N)<-contr.treatment(3, base=1, contrasts=FALSE) contrasts(N) # 1 2 # 1 1 0 # 2 0 1 # 3 0 0 whereas: contr.treatment(3, base=1, contrasts=FALSE) # 1 2 3 # 1 1 0 0 # 2 0 1 0 # 3 0 0 1 contr.treatment(3, base=1,

Hi Folks, This must be easy but I've not managed to locate the solution! Basically: I'm using sink() to save successively obtained results, e.g. I construct a set of regression coefficients etc. with names rows and columne (I want to see the names in the output) as an object (say "Object"), and then I emit it with print(Object) So far so good. But I also want to print a

Hi Folks, I have been using contour() to produce some contour plots (of a spatially-smooted density produced by kde2d()), with very satisfactory results. I now want access to the coordinates of the points on the contours, and it would seem that contour() does not return a value, so there is nothing from which these could be extracted. However, apparently contourLines() does, and it seems to be

Greetings all! I have been searching the Site for a function, say "subsets", such that for instance subsets(10) would return a (say) matrix of indices to the 2^10 subsets of N items -- perhaps in the form of 2^10 rows each of which is 10 entries each either TRUE or FALSE. Or 1 or 0. Or ... I can of course write my own, using good old looping technology or similar, but it would be

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

Greetings Moderators! I moderated the message below just now (one of two identical test messages). I rejected it, with a covering note to the author (John Munroe <munddr at gmail.com>, who does not appear to be subscribed to the list) that I was doing so because approving it would serve no useful purpose, and pointing out that it had been held because the message headers matched a filter

Greetings, All! I want to draw contour lines in red, using contour(), but also have the contour labels (for the level-values) in black so that they will stand out against a coloured background already generated using filled.contour() (the background shades from green at low levels of "risk" to red at high levels). In any case, contour labels in red are already somewhat inconspicuous

Hi Folks, Say I have 2 continuous variables X,Y. I can of course plot (X,Y) with plot(X,Y,pch="+",col="blue") say, and add the regression line from lm(Y~X) by extracting the coefficients 'a' of Intercept and 'b' of X from Y.lm <- lm(Y~X). Now, however, I want to have not only a general explanatory title such as main="Plot of Y against X"

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

A follow-up to my previous query. Say one of the results returned by contourLines() is C.W <- contourLines(....) Then C.W is a list of (in this case 28) lists, each of which is a list with components $level (a single number), $x (the x coords of the points on a contour at that level) and $y (the y coords). I can of course get these individually with, for the 5th one for instance,