similar to: library(grid) : .First.lib fails (PR#3347)

Dear list, I have problems loading the grid library; running > library(grid) results in Error in .Call("L_initGrid"): Call function name not in load table Error in library(grid): .First.lib failed PC: Windows NT 4.0 SP6 on a Ghz-Pentium machine with 256 MB memory R: version 1.4.0 patched (23/01/02) grid: 0.5-1, built 26/01/02 I haven't found this on CRAN; any ideas would be

The write.csv() function is currently implemented as function (..., col.names=NA, sep=",", qmethod="double") { write.table(..., col.names=NA, sep=",", qmethod="double") } Surely, it should be function (..., col.names=NA, sep=",", qmethod="double") { write.table(..., col.names=col.names, sep=sep,

Dear r-bugs, I'd like to be able to draw boxplots with solid or dotted whisker lines. The lty argument is currently ignored by boxplot(), and indeed hardwired in bxp(). It's not very difficult to customize these functions to generate various types of boxplots, but generally it might be an idea to allow the user to pass a few more graphical arguments to boxplot(). The approach might as

Full_Name: Arni Magnusson Version: 1.6.2 OS: Windows XP Submission from: (NULL) (210.48.49.68) Hi there. I'm experiencing unexpected behaviour from as.POSIXct: > as.POSIXct("1969-12-24") [1] "1969-12-23 23:00:00 New Zealand Standard Time" > as.POSIXlt("1969-12-24") [1] "1969-12-24" > as.POSIXlt("1969-12-24")+1 [1] "1969-12-23

The audit trail indicates that PR#3663 is not reproducible and/or fixed, but I believe windows(record=T) is still not working as documented: windows(record=T) for(i in 1:5) plot(0, 0, cex=4, pch=as.character(i)) After cycling through the plots with PgUp and PgDn, the user finds out that plot 5 is lost. Indeed, .SavedPlots reports that only 4 plots were saved. I'm running the example in

Dear r-bugs, The 'see also' link in help(area,html=T) is broken, see line 91 in library/MASS/html/area.html: "../../integrate/html/integrate.html" should be "../../base/html/integrate.html" Regards, Arni OS: Windows XP R: 1.7.1 MASS: 7.1-8

I'd like to suggest changes to three help pages, regarding the use of pch=NA to suppress plotting symbols. See below. Arni R 2.0.1 on WinXP === help(bxp) === The argument outpch=" " needs to be replaced with outpch=NA in two places. I actually wrote this part of the documentation myself at one point, but have now realized that pch=NA and pch=" " are not the same:

In Windows XP, the matrix() function crashes the program when 'dimnames' is an empty list: matrix(1:4, nrow=2, dimnames=list()) # R has encountered a problem and needs to close ... This bug is specific to WinXP, as Linux64 handles this situation more gracefully: matrix(1:4, nrow=2, dimnames=list()) Error in matrix(1:4, nrow = 2, dimnames = list()) : invalid type

Dear r-bugs, When I create EPS files, they sometimes appear rotated in my LaTeX PDF document and sometimes they don't. Two examples: ## x1.eps is not rotated in LaTeX x <- seq(-1, 1, length=100) postscript("c:/x1.eps", height=3, width=4, horizontal=FALSE, onefile=FALSE, paper="special") plot(x, dnorm(x), type="l") dev.off() ## x2.eps is not

One descriptive statistic that is conspicuously missing from core R is the statistical mode - the most frequent value in a discrete distribution. I would like to propose adding the attached 'statmode' (or a similar function) to the 'stats' package. Currently, it can be quite cumbersome to calculate the mode of a distribution in R, both for experts and beginners. The lack of a

Unlike R 2.1.1, version 2.2.0 generates warnings when an 'oma' argument as passed to pairs(): A <- rnorm(100) B <- rnorm(100) pairs(cbind(A,B)) # no warning pairs(cbind(A,B), oma=c(6,8,10,12)) # warnings in R 2.2.0 I think pairs() should draw the plot quietly, without warnings. Can't see anything in the documentation indicating that an

The weighted.mean() function replaces NA values with 0.0 when the user specifies na.rm=TRUE: x <- c(101, 102, NA) mean(x, na.rm=TRUE) # 101.5, correct weighted.mean(x, na.rm=TRUE) # 67.66667, wrong weighted.mean(x, w=c(1,1,1), na.rm=TRUE) # 67.66667, wrong weighted.mean(x, w=c(1,1,1)/3, na.rm=TRUE) # 67.66667, wrong The weights are

Good question Rolf. Rui, thanks for pointing out dyn.unload. When I started using Rcpp a couple of years ago I got burned by stale .so enough times that I adopted a policy of recompile-then-start new R session. My workflow does not include Rolf's "brazillion" repeats, so the overhead of this approach has not been too painful. The documentation for dyn.unload (via ?dyn.unload)

I present you with a function that solves a problem that has bugged me for many years. I think the problem may be general enough to at least consider adding this function, or a revamped version of it, to the 'stats' package, with the other multinomial functions reside. I'm using R to export data to text files, which are input data for an external model written in C++. Parts of the

I am working on a SLES 10 cluster with R available on it. To better use my resources, I want to use Rmpi, but I am having a difficult time installing it. I have set the $R_LIBS variable correctly. The MPI libraries are available through the PGI compiler, but this R instance was compiled with GCC. The Rmpi package can be compiled and installed with %R CMD INSTALL Rmpi_0.5-5.tar.gz

The model frame shows the response and predictors in a data frame with nicely labelled columns: fm <- lm(wt~qsec+log(hp)+sqrt(disp), data=mtcars) model.frame(fm) # ok When the left hand side consists of more than one response, those response variables still look good, inside a matrix: fm <- lm(cbind(qsec,hp,disp)~wt, data=mtcars) model.frame(fm)[[1]] # ok A problem arises when

I have been reading about autocorrelation in linear models over the last couple of days, and I have to say the more I read, the more confused I get. Beyond confusion lies enlightenment, so I'm tempted to ask R-Help for guidance. Most authors are mainly worried about autocorrelation in the residuals, but some authors are also worried about autocorrelation within Y and within X vectors

Hello, I plan to use R with my cluster with OpenMPI. I need the packaged 'snow' and 'Rmpi' for that, however, I get an error while downloading and installing them: When I do a: install.packages("Rmpi", dependencies=T) I get this error: checking for mpi.h... no Try to find libmpi.so or libmpich.a checking for main in -lmpi... no libmpi not found.

Hi, apparently I sent my question about using R and C++ to the wrong list, ironically seeing as that list was called Rcpp. Anyway, I was directed to post my question here. To summarize my current question, I have found two commands that I want to be able to put into a package. The commands are 'R CMD SHLIB X.cc X_main.cc' and

This relates to a message from Christophe Pallier to r-help some time ago. Like myself, he finds aggregate very useful, but the interface a little cumbersome. I've implemented a more compact formula interface, found at the bottom of this message: data(ToothGrowth) # I used to aggregate like this: aggregate(list(len=ToothGrowth$len),