similar to: Development version of R fails tests and is not installed

>>>>> Berwin A Turlach >>>>> on Tue, 5 Mar 2019 16:54:09 +0800 writes: > G'day all, > I have daily scripts running to install the patched version of the > current R version and the development version of R on my linux box > (Ubuntu 18.04.2 LTS). > The last development version that was successfully compiled and >

I get the failure message. To be specific: adcomp.git>R CMD BATCH --quiet test_nlminb.R adcomp.git>cat test_nlminb.Rout > f <- function(x) sum( log(diff(x)^2+.01) + (x[1]-1)^2 ) > opt <- nlminb(rep(0, 10), f, lower=-1, upper=3) > xhat <- rep(1, 10) > abs( opt$objective - f(xhat) ) < 1e-4? ## Must be TRUE [1] FALSE My system is described by: adcomp.git>uname

> On 1 Feb 2019, at 10:00, Martin Maechler <maechler at stat.math.ethz.ch> wrote: > > ........ >>> sessionInfo() >> R version 3.5.2 (2018-12-20) >> Platform: x86_64-pc-linux-gnu (64-bit) >> Running under: Scientific Linux release 6.4 (Carbon) > >> Matrix products: default >> BLAS/LAPACK:

Hello, R 3.5.2 on ubuntu 18.04. sessionInfo() at the end. Works with me, same results, cannot reproduce the error. f <- function(x) sum( log(diff(x)^2+.01) + (x[1]-1)^2 ) opt <- nlminb(rep(0, 10), f, lower=-1, upper=3) str(opt) xhat <- rep(1, 10) all.equal(opt$par, xhat, tol=0) # good: 5.53 e-7 #[1] "Mean relative difference: 5.534757e-07" all.equal(opt$objective,

A table without names displays like a vector: > unname(table(2:3)) [1] 1 1 1 and preserves the table class (as with unname in general): > dput(unname(table(2:3))) structure(c(1L, 1L), .Dim = 2L, class = "table") Does that make sense? R is not consistent in its treatment of such unname'd tables: In plot, they are considered erroneous input: >

I ran into strange behavior when removing names. Two ways of removing names: i <- rep(1:4, length.out=20000) k <- c(a=1, b=2, c=3, d=4) x1 <- unname(k[i]) x2 <- k[i] x2 <- unname(x2) Are they identical? identical(x1,x2) # TRUE but no identical(serialize(x1,NULL),serialize(x2,NULL)) # FALSE But problem is with serialization type 3, cause:

Hi all, Very surprising (to me!) and mystifying result from predict.glm(): the predictions vary depending on whether or not I use ns() or splines::ns(). Reprex follows: library(splines) set.seed(12345) dat <- data.frame(claim = rbinom(1000, 1, 0.5)) mns <- c(3.4, 3.6) sds <- c(0.24, 0.35) dat$wind <- exp(rnorm(nrow(dat), mean = mns[dat$claim + 1], sd = sds[dat$claim + 1])) dat <-

I've noticed unstable behavior of nlminb on some Linux systems. The problem can be reproduced by compiling R-3.5.2 using gcc-8.2 and running the following snippet: f <- function(x) sum( log(diff(x)^2+.01) + (x[1]-1)^2 ) opt <- nlminb(rep(0, 10), f, lower=-1, upper=3) xhat <- rep(1, 10) abs( opt$objective - f(xhat) ) < 1e-4 ## Must be TRUE The example works perfectly when

i use tapply and by often, but i always end up banging my head against the wall with the output. is there a simpler way to convert the output of the following tapply to a dataframe or matrix than what i have here: # setup data for tapply dt = data.frame(bucket=rep(1:4,25),val=rnorm(100)) fn = function(x) { ret = c(unname(quantile(x,probs=seq(.25,.75,.25),na.rm=T)),mean(x,na.rm=T)) } a =

Sorry to append, but I just realised that of course ``` x |> ? pmap(c) |> ? reduce(c) |> ? unname() ``` also works and is a general solution in case your list has more than three elements. Here, we map in parallel over all elements of the list, always combining the current set of elements into a vector, and then reduce the resulting list into a vector by combining the elements

Just noticed these two functions (clearNames is stats and unname in base) that do the same thing. Hadley -- http://had.co.nz/

I didn't do the compile; is there a way to check whether that was used? If not, I'll inquire with our sysadmin and report back. In any case, my suggestion was motivated by the fact that some parts of R use OpenMP while others do not, in the hope that the former could have their OpenBLAS omelet without breaking the OpenMP eggs, so to speak. On 01/09/2018 06:41 PM, Keith O'Hara

Hello, macosx 10.13.6, Rdevel r76458 I'm trying to compile against openblas to reproduce an error on the CRAN check page (my package is clean under winbuilder and all but one of the checks). I've downloaded and installed openblas 0.3.7 but I am not 100% sure that it is being used by R. Using ./configure --with-blas="-lopenblas" Then running R to discover the PID I get:

Hi, Our department has detected a bug in the implementation of the Kinderman-Ramage generator for normal random variates in version 1.7.0, which can be seen from the below R session. (Consecutive calls for chisq.test(...) always gives p-values very close to 0.) We have already encountered this bug in version 1.6.2 The error is in file R-1.7.0/src/nmath/snorm.c Here is a patch for this file to

Please pardon my ignorance, but doesn't OpenBLAS still not always play nicely with multi-threaded OpenMP? (for example, don't race conditions sometimes crop up)? If so, it might be nice to have the ability to temporarily disable multi-threaded OpenMP (effectively: omp_set_num_threads(1)) for the duration of operations using OpenBLAS. Regards Ben > Julia using OpenBLAS is *very*

On Wed, 8 May 2019 at 04:52, Peter Langfelder <peter.langfelder at gmail.com> wrote: > > (CCing the R-devel list, maybe someone will have a better answer.) > > To be honest, I don't know how to. I wasn't able to configure R to use > OpenBLAS using the configure script and options on my Linux Fedora system. > I configure it without external BLAS, then replace the

Dear list, What is the recommended incantation on Fedora 32 to swap out the openblas BLAS that the packaged (rpm) version of R-core installs for ATLAS? I'm running into some problems with some big models I want to fit using the mgcv package, and openblas is apparently not thread safe and is causing problems. I have the following installed: $ dnf list installed | grep ^R R-core.x86_64

Dear R useRs, with the following piece of code i try to find the first value which can be calculated without warnings `test` <- function(a) { repeat { ## hide warnings suppressWarnings(log(a)) if (exists("last.warning", envir = .GlobalEnv)) { a <- a + 0.1 ## clear existing warnings rm("last.warning", envir = .GlobalEnv) }

Hello, I thought that I should try openblas when building a CRAN package containing lots of old (twentieth century) C-code with frequent calls to blas and lapack routines. I have the following options on my Ubuntu 20.04 machine: Selection Path Priority Status ------------------------------------------------------------ * 0

I see a book coming: "666 ways to do the same thing in R ranked by sexiness." Kidding aside, if you look under the covers of some of the functions we are using, we may find we are taking steps back as some of them use others and perhaps more functionality than we need. But for a new reader , looking at many approaches may open up other ways and ideas and see the problem space as quite