similar to: setting par(fig) resets par(mfrow), par(mfcol)

many thanks to P. Dalgaard, J. Fox, J. Lemon, JE. Paradis and J. Polzehl for their quick replies. The original posting is at the end of this summary. I've not well explained myself but I don't wanted to use par(mfrow) or par(mfcol) because I wanted to plot very different graphics and this solution doesn't match my needs. E. Paradis and P. Dalgaard made me discover a new (for me!)

Dear friends of lattice, I know how to position trellis plots with print(...,split,more=T) or (...position). Sometimes I wish I had something like the old "par(mfcol=2, mfrow=3)" mechanism, where the next free viewport is automatically chosen. I tried fiddling with grid-viewports, but could not find an easy solution. Did I miss something? Dieter Menne

I am trying to make a nice 2x1 plot and add a timestamp with comment. The pstamp function from Hmisc works nicely when mfcol=c(1,1), but when mfcol=c(2,1), the stamp winds up in the wrong place: > require('Hmisc') > opar <- par(mfcol=c(2,1)) > plot(1:10) > title(main="MAIN Title") > plot(1:20) > title(main="Another Title") > pstamp("normal

At 11:57 25/10/00 +0100, Brian Ripley wrote: >> Date: mer., 25 oct. 2000 12:38:55 +0200 >> From: Emmanuel Paradis <paradis@isem.univ-montp2.fr> > >> I think it would be nice to have par(ask=T) set by default in termplot(), >> like it is in plot.lm(). > >Well, it isn't really the default in plot.lm, the default for `ask' being > >interactive()

hi everybody, I noticed the following: in one of my scripts 'layout' is used to generate a (approx. square) grid of variable dimensions (depending on no. of input files). if the no. of subplots (grid cells) becomes moderately large (say > 9) I use a construct like ###layout grid computation and set up occurs here### ... opar <- par(no.readonly = T);

help(par) says: 'mfcol, mfrow' ... In a layout with exactly two rows and columns the base value of '"cex"' is reduced by a factor of 0.83: if there are three or more of either rows or columns, the reduction factor is 0.66. In reality, par(mfrow =) *resets* par ('cex'), not reduces it as documented. To reproduce: par(cex = 0.5) par(mfrow = c(2,

hello R-users, I'd like to plot four graphics on the same page but with different sizes. I've tried to use : par(fig=c(0,0.5,0,0.6)) plot(fig1) par(fig=c(0.5,1,0,0.6)) plot(fig2) etc... but when a figure is plotted, it erase the previous. I've tried to pass 'new=T' to plot function but it's not possible. What can I do ? is it a bug ? I've already reported this a 2 or

There was some interest in the commands for creating an HTML file of 3D graphics that can be shown with a Java applet. Looking at things I discovered (of course) that I should really clean up quite a few things before releasing it for real. I hope to do some of that this weekend. In the meanwhile, here are a couple of pointers to the Java applet & documentation (apparently free for

I am trying to find a way to analyze a "simple" mixed model with two levels of a treatment, a random blocking factor, and (wait for it) negative binomial count distributions as the response variable. As far as I can tell, the currently available R offerings (glmmGibbs, glmmPQL in MASS, and Jim Lindsey's glmm code) aren't quite up to this. From what I have read (e.g.

This is off-topic (apologies), but I thought I might get a lead or two here. I'm interested in generating random deviates from a multivariate distribution which is a generalization of the beta distribution -- the Bayesian canonical distribution for the parameter estimates of a multinomial distribution. Given a vector (length n-1) of probabilities p and a vector (length n) of shape

I'm trying to answer a question from a student about memory use in R (I won't go into the details right here). I have a really vague memory of having read a document, possibly by Venables or Ripley, discussing the awfulness of memory allocation in S-PLUS, and giving (in the context of a bootstrapping analysis of shoe size data??) some general strategies for conserving memory in S-PLUS.

I'm having problems (or to be precise a student is having problems, which I'm having problems helping her with) trying to use glm.nb() from the MASS package to do some negative binomial fits on a data set that is, admittedly, wildly overdispersed (some zeros and some numbers in the hundreds). glm.nb is failing to converge, and furthermore is (to my surprise) producing values of theta

I want to add my two cents of congratulation to the R core team. I also want to encourage everyone who uses R to be an active, not a passive user -- the fastest way R will get better is if the folks who use it submit bug reports, suggestions, R code for their particular fields, documentation, even patches and code fixes. R is big and complicated enough now that we can't leave testing to

There are a few inconsistencies, at least, in some of the functions that generate random deviates from particular distributions (I think they're bugs because they're inconvenient, but maybe someone can make an argument for the current behavior). If people think these are really bugs I can submit them, together or separately. 1. rlnorm(n,mean,sd) gives NaN for sd=0, rather than always

For various reasons, I've opted to make my packages available from my own web page rather than submitting them to CRAN (mostly laziness -- for a long time I didn't have the packages quite cleaned up enough to pass all the tests). It occurred to me to wonder about the scripts used by CRAN maintainers to generate the PACKAGES file, and to generate PACKAGES.html from PACKAGES. Are

Does the nls package actually allow for weighted nonlinear regression? (i.e., I have data with individual variances associated, I'd like to use 1/var to weight the points.) The "nls" function does have a weights argument, but it doesn't seem to do anything as far as I can tell ... thanks ... Ben Bolker -- 318 Carr Hall bolker at

Some students of mine are trying to use gnls, the generalized non-linear least squares function within the nlme library, to study evolutionary questions where correlations between traits at the species level are non-independent because of the evolutionary relatedness of the species. Specifically, they're using a non-linear function (log(sexual dimorphism) ~ log(a + b*variation in mating

Just thought people might be interested to know that the latest version of R-win now runs under Wine, the windows emulator for Linux (ver. 20001202). (I originally tried this a couple of releases back because a student seemed to be having system-specific problems and I was attempting to be lazy.) The recent switch from crtdll to msvcrt seems to have helped with Wine compatibility. I

Some of my students were interested in a plot where the sizes of the symbols were proportional to the number of repeats in the data (I have them plotting discrete data, so there are often overlaps). Here's the solution I came up with, which seems clever (to me) but not necessarily the best way. Can anyone suggest improvements? sizeplot <- function(x,y,maxsize=0.2,

Just a quick question, in case I'm doing something really boneheaded that could be easily sorted out. I'm attempting to save() datasets on Linux (R 1.1.1) and load() them on Win2K (rw1011, fetched from CRAN today). I get the "restore file corrupted" message every time. I've tried saving with ascii=TRUE and FALSE, and the ASCII versions look OK (it's my impression