similar to: Inferring dimensions on bitmap device from par()

Dear all, the help of par() claims that cin and cra are c(width, height) but it appears to be rather c(height, width) Best regards Jens Oehlschl?gel > plot.new() > strheight("W", unit="inches") [1] 0.1354167 > par("cin") [1] 0.1354167 0.1875000 > version _ platform i386-pc-mingw32 arch i386 os mingw32

I'm getting a lot of warning having to do with setting graphic parameters. I don't recall actually setting any of these, so I would guess they are being set by something I am calling. Has anyone already figured out where this is happening? Paul Gilbert _____ All dse3 tests ... ok All dse4 tests ...Warning: skipping test 4 (requires stepwise). ok dse2 graphics tests ...completed dse3

I often use something like old.par <- par(set someting) on.exit(par(old.par)) but in R 1.7.0. I now get warnings: > old.par <- par() > par(old.par) Warning messages: 1: parameter "cin" can't be set in: par(args) 2: parameter "cra" can't be set in: par(args) 3: parameter "csi" can't be set in: par(args) 4:

Hi, I have a dataset called 'fish'. fish$Species returns extract 1. When I use fish$Species != c("CRA","PHC"), i.e. I want all species except "CRA" and "PHC", I get extract 2 which is blatantly wrong. Can anyone see what I'm doing wrong? Regards, James EXTRACT 1 > fish$Species [1] ALB ALB ALB ALB ALB ALB ALB ALB ALB ALB ALB ALB ALB

Dear R-help community, I am working with multidimensional contingency tables and I am having trouble getting loglm to run on all dimensions without typing out each dimension. I have generated random data and provided output for the results I want below: d1.c1 <- rnorm(20, .10, .02) d1.c2 <- rnorm(20, .10, .02) d2.c1 <- rnorm(20, .09, .02) d2.c2 <- rnorm(20, .09, .02) d3.c1 <-

Dear R listers, I am trying to create a new variable that uniquely identifies groups of observations in a dataset. So far I couldn't figure out how to do this in R. In Stata I would simply type: egen newvar = group(dim1, dim2, dim3) Please, find below a quick example to show what I am dealing with: I have a dataset with 4 variables: var <- runif(50) ## a variable that I want to group

Hi, I would like to use the multinomRob function to test election results. However, depending on which independent variables I include and how many categories I have in the dependent variable, the model cannot be estimated. My data look like this (there are 68 observations): > head(database) RESTE09 GAUCHE09 PDC09 PLR09 UDC09 MCG09 RESTE05 GAUCHE05 PDC05 D1 1455

"contour" can't return a list of contours (it would be nice) "arrows" has different options from S-PLUS (no "open" or "rel" options, no "lwd" parameter or graphics parameter pass-through; "size" in S corresponds to "length" in R). [I know we needn't follow S-PLUS syntax slavishly, but it would be nice at least to

Dear R-help, I'm using 63.3 on windows NT. The improved graphics device has a problem in that the default par settings produce text that is way too small (63.2 seemed fine). I've compared the parameters between 63.3 and 63.2 and the ones that differ are : cin, cra, csi, mai, pin, plt. In the par help file, cin and cra have no documentation other than that they are read only, the last

Full_Name: Manuel L?pez-Ib??ez Version: R version 2.6.2 (2008-02-08) OS: linux-gnu Submission from: (NULL) (164.15.10.156) This is only relevant for CPU intensive child processes. Otherwise, the problem is not obvious. Therefore, we need a CPU intensive program like this one: /************************************/ /*** Compile with: gcc -o timer-test -O0 timer-test.c -lm */ #include

Dear all, I had to extracts/set elements from/in a matrix. Let say I have two vectors dim1 and dim2 of indices in the respective two dimensions of a matrix: I want to extract all the corresponding elements. I the case of a nxn matrix, dim1 <- 1:n and dim2 <- 1:n would extract the diagonal. I know one way would be to use the functions 'row' and 'col', but the matrixes I

Hello all, I have been using the function ordirgl to plot 3D dynamic ordinations. The ordirgl function works just fine. IN fact, I was even able to write a function that allows me to identify points in the 3D plot: identify.rgl<-function(env_var,ord,dim1,dim2,dim3) { tmp<-select3d(button="left") tmp.keep<-tmp(ord[,dim1],ord[,dim2],ord[,dim3])

Hi R friends, I havent asked a silly question in a long time so here it is: Reading the last issue of Stat Can J. there is an article in a single degree of freedom test for non aditivity of interactions in anova tables with 1 obs per cell. The authors claim it is more powerfull than Tukey but for the case of multiplicative interaction, which is the alternative studied by Tukey. I tried to

I have a data in the following form : CIN TRN_TYP 9079954 1 9079954 2 9079954 3 9079954 4 9079954 5 9079954 4 9079954 5 9079954 6 9079954 7 9079954 8 9079954 9 9079954 9 . . . . . . there are 100 types of CIN (9079954,12441087,15246633,...) and respective TRN_TYP first of all, I want this data to be

>>>>> "Marc" == Marc Schwartz <mschwartz@medanalytics.com> >>>>> on Wed, 13 Nov 2002 11:01:49 -0600 writes: Marc> Marc Schwartz wrote: >> SNIP >> >> I am guessing that this may be the result of par("ylog") >> and par("xlog") being read only and perhaps impacting the >>

Hi all, I have some problems inserting data into a legacy table. the key field of this table is a field named CIN which is a varchar(15). when I try insert into this table using a form (generated by the scaffold generator) I get this Error : _____________________________________________________________________ undefined method `CIN_before_type_cast'' for #<Candidat:0x370d8c8> |

Hi, I would like to get from a plot the size of the symbols plotted. Imagine I have the following plot function : plot(1:2,1:2, pch=15, cex=4) I would like the get the values SIZE1 and SIZE2 so that if I plot the following rectangle : rect(1.5,1.5, 1.5+SIZE1, 1.5+SIZE2) then the size of this square is exactely the same as the one of the symbols that have been plotted. Thanks for any idea. --

Dear R users, I'am using marray and Limma packages to analyze genepix output. 1) how can I filter bad spots from my data (data contains 3 types of bad spots). my experiment contains 12 samples and the bad spot are not associated to the same probes 2) how can I remove control probes from my data ? I'm sorry, i'm new with R and I can't find answer in packages doc. best regards,

On my home (Windows 98) machine I find: > par()$cra [1] 42 16 > par()$csi [1] 0.1666667 > On my work machine I believe I had par()$cra [1] 17 16 So it looks as though R is reading the width wrongly, and that it is the width that is somehow used to determine the plot character size. Incidentally I noted Brian's comment that R had misread his character dimension information wrongly.

Hello R experts, I've used metaMDS to run NMDS on some fish abundance data, and am also working on correlating environmental data to the NMDS coordinates. I'm fairly new to metaMDS and NMDS in general, so I have what are probably some very basic questions. My fish abundance data consists of 66 sites for which up to 20 species of fish were identified and counted. I ran metaMDS on this data