similar to: Rgui crash under Windows

Dear R community, I have a question on how R manages memory allocation in .Fortran() calls under Windows. In brief, apparently, it is not possible to allocate large matrices inside a Fortran subroutine unless you pass them as arguments. If you do not act in this way RGUI crashes with a stack overflow error and acting on memory through vsize nsize ppsize and memory.limit does not help at all.

minimal reproducible example plot(1,1) identify(1,1) # or locator() now, trying to close the window by clicking on the cross of the upper right corner causes Rgui (and Rterm) to crash. I see the same behaviour on 2 different Windows PC (one with Win 8.1 and one with Win 10). I did not see the problem in linux (see below) WINDOWS ************** > sessionInfo() R version 3.3.0 beta

Dear All, I found the following under R 2.3.0 on WINXP (tested on 2 PCs, I do not have access to Linux from this PC, sorry ... ) > set.seed(10) > x <- ts(rnorm(6),frequency=7) > x Time Series: Start = c(1, 1) End = c(1, 6) Frequency = 7 [1] 0.01874617 -0.18425254 -1.37133055 -0.59916772 0.29454513 0.38979430 > x[24] <- NA > x Time Series: Start = c(1, 1) End = c(1, 6)

If of any help, I can reproduce this (on Windows 7) back to at least R 3.0.3 but it's not there in R 3.0.0. (I have *not* checked with R 3.0.1 and 3.0.2 which I don't have installed). /Henrik On Tue, Apr 5, 2016 at 8:23 AM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > Thanks, I'll track this down. > > Duncan Murdoch > > > On 05/04/2016 9:35 AM,

Dear all, I am managing a departmental purchase of an Opteron based workstation/server for scientific computing on which we will be running R. The environment will probably be either Unix/Linux or Solaris and the amount of RAM will be 8-16Gb, depending on the number of processors. My main concerns are the following: 1. How much does R benefit from passing from one processor to two/four

Dear all, following the thread http://tolstoy.newcastle.edu.au/R/e2/devel/07/09/4338.html regarding the bug in the partial autocorrelation function for multivariate time series. I have prepared a web page with patches and relevant information. http://www2.stat.unibo.it/giannerini/R/pacf.htm Please do not hesitate to contact me for further clarifications regards Simone --

Hi, This report deals with p-values coming from chisq.test using the simulate.p=TRUE option. The issue is numerical accuracy and was brought up in previous bug reports 3486 and 3896. The bug was considered fixed but apparently was only mostly fixed. Just the typical problem of two values that are mathematically equal not ending up numerically equivalent. Consider this series of three 2x2

According to ?parCapply: parRapply and parCapply always return a vector. This appears not to be the case in the following minimal reproducible example: > library(parallel) > nslaves <- 2 > cl <- makeCluster(nslaves) > X <- matrix(2,nrow=3,ncol=4) > X <- rbind(c(1,1,0,1),X) > tv <- parCapply(cl,X,FUN=function(x){ +

Dear all, I found the following behaviour > rf(5,Inf,Inf) [1] 1 1 1 1 1 but > qf(0.1,Inf,Inf) [1] NaN Warning messages: 1: In qf(0.1, Inf, Inf) : value out of range in 'lgamma' 2: In qf(p, df1, df2, lower.tail, log.p) : NaNs produced incidentally, > pf(1.00000000000001,Inf,Inf) [1] 1 > pf(1.0000000000000001,Inf,Inf) [1] 0.5 Is this the expected behaviour? Thanks

Dear list, I do not know what would be the 'correct' answer to the following but I think that they should return the same value to avoid potential problems and hard to debug errors. Regards, Simone --------------------------------------- > NCOL(NULL) [1] 1 > NROW(NULL) [1] 0 > sessionInfo() R version 4.3.1 RC (2023-06-08 r84523 ucrt) Platform: x86_64-w64-mingw32/x64 (64-bit)

Dear all, I encountered a problem when compiling the source of R patched 2.10.0 r50499 (19-11-2009) linked to ACML single threaded (4.2.0 or 4.3.0) OS: openSuSE 11.0 x86-64 make fails when it comes to installing mgcv with the following [snip] ** R ** inst ** preparing package for lazy loading Error in loadNamespace(i[[1L]], c(lib.loc, .libPaths())) : non esiste un pacchetto chiamato

Dear all, it looks like that something is wrong with the /bin/windows/base/rpatched.html page as it seems pointing to the 2.8.1rc version. Also, I do not know if it is relevant but notice the dates of the following files on ftp://ftp.stat.math.ethz.ch/Software/CRAN/bin/windows/base/ R-2.8.1pat-win32.exe 31963 KB 22/12/2008 16.15.00 R-2.8.1rc-win32.exe 31991 KB 25/12/2008 9.30.00 thank

Dear all, there seems to be a problem with displayed legends when a multiple figure environment is used, see the following example: par(mfrow=c(1,2)) curve(dnorm,col=4,from=-4,to=4); legend(-4,0.3,legend="curve",lty=1,col=4) legend(-4,0.2,legend="curve",lty=1,col=4) On my machines the first time the command legend() is issued the legend box stretches over the curve.

Dear all, I think I have found a buglet in plot.ts plot.ts(x=1,type="n") # correct: does not show the plot plot.ts(x=1,y=1,type="n") # not correct: does show the plot I did not investigate the problem in depth but it could be related to the switch xy.labels, in fact plot.ts(x=1,y=1,type="n",xy.labels=TRUE) # does show the plot

Full_Name: Bert De Boeck Version: R 2.2.0 OS: Windows Submission from: (NULL) (157.193.193.152) I think there is a bug when using integrate for integrating a function which is 0 in a whole sub-interval. For example: #define uniform function f<-function(x){ifelse(x<1,0,ifelse(x<3,1,0))} #this is the correct integral integrate(f,-10,10) #here there is a problem integrate(f,-50,50)

Dear all, switch() called with just the EXPR argument causes R to hang so that the only way to stop it is to kill R. Reproducible example: > switch(EXPR="a") the internal C subroutine behind switch is do_switch located in R/src/main/builtin.c For convenience I reproduce it below. ***************************************************************************** SEXP attribute_hidden

Dear all, it looks like fix() changes the class of mts objects, here is a reproducible example (tested both on WinXP and Linux): > x <- ts(cbind(1:5,1:5)) > x Time Series: Start = 1 End = 5 Frequency = 1 Series 1 Series 2 1 1 1 2 2 2 3 3 3 4 4 4 5 5 5 > class(x) [1] "mts" "ts" > edit(x)

Dear all, from the help page of quantile: "x ??? numeric vectors whose sample quantiles are wanted. Missing values are ignored." from the help page of IQR: "x ??? a numeric vector." as a matter of facts it seems that both quantile() and IQR() do not check for the presence of a numeric input. See the following: set.seed(11) x <- rbinom(n=11,size=2,prob=.5) x <-

Dear all, given two numeric vectors x and y, the ACF(x) at lag k is cor(x(t),x(t+k)) while the CCF(x,y) at lag k is cor(x(t),y(t-k)). See below for a simple example. > set.seed(1) > x <- rnorm(10) > y <- rnorm(10) > x [1] -0.6264538 0.1836433 -0.8356286 1.5952808 0.3295078 -0.8204684 0.4874291 0.7383247 0.5757814 -0.3053884 > y [1] 1.51178117 0.38984324

I recently started using R 2.7.2, and noticed a surprising change in the behavior of var() on NA data: R 2.6.1 (Patched), 2007-11-26, svn.rev 43541, x86_64-unknown-linux-gnu: > stdev(rep(NA,3), na.rm=F) [1] NA > stdev(rep(NA,3), na.rm=T) [1] NA > var(rep(NA,3), na.rm=T, use="complete.obs") [1] NA R 2.7.2 (Patched), 2008-09-02, svn.rev 46491,