similar to: changes in R-devel and zero-extent objects in Rcpp

A change to R-devel (SVN r86629 or https://github.com/r-devel/r-svn/commit/92c1d5de23c93576f55062e26d446feface07250 has changed the handling of pointers to zero-length objects, leading to ASAN issues with a number of Rcpp-based packages (the commit message reads, in part, "Also define STRICT_TYPECHECK when compiling inlined.c.") I'm interested in discussion from the

The ASAN errors occur *even if the zero-length object is not actually accessed*/is used in a perfectly correct manner, i.e. it's perfectly legal in base R to define `m <- numeric(0)` or `m <- matrix(nrow = 0, ncol = 0)`, whereas doing the equivalent in Rcpp will (now) lead to an ASAN error. i.e., these are *not* previously cryptic out-of-bounds accesses that are now being

IMHO, this should be changed in both Rcpp and downstream packages: 1. Rcpp could check for out-of-bounds accesses in cases like these, and emit an R warning / error when such an access is detected; 2. The downstream packages unintentionally making these out-of-bounds accesses should be fixed to avoid doing that. That is, I think this is ultimately a bug in the affected packages, but Rcpp could

On Sat, 8 Jun 2024, Ben Bolker wrote: > The ASAN errors occur *even if the zero-length object is not actually > accessed*/is used in a perfectly correct manner, i.e. it's perfectly legal in > base R to define `m <- numeric(0)` or `m <- matrix(nrow = 0, ncol = 0)`, > whereas doing the equivalent in Rcpp will (now) lead to an ASAN error. > > i.e., these are *not*

Sorry to ask about a bit drifted topic, but will there be an alternative API to DATAPTR? > DATAPTR is not in the API and can't be at least in this form I believe it's vital for ALTREP to return the pointer to the expanded version of a SEXP just like the implementation in base R does [1]. At least, VECSXP has no other measure to expose the pointer if I understand correctly. Best,

dear members, I am using R to model stock prices but a slow "for" loop has stifled my research. I am using Rcpp to speed up my "for" loop. I am also using RcppEigen to implement block operations on xts objects..... how do I use RcppEigen? If I just load it by: > require(RcppEigen) it is not recognising the .block method in C++. If I include it inside

RHEL 6 installed R version 3.2.3 from EPEL installed Start R and use the following command, but got warnings! install.packages("rstan", dependencies = TRUE, repos = "http://cran.r-project.org/") ... g++ -m64 -shared -L/usr/lib64/R/lib -L/usr/local/lib64 -o RcppEigen.so RcppEigen.o RcppExports.o fastLm.o -L/usr/lib64/R/lib -lRlapack -L/usr/lib64/R/lib -lRblas -lgfortran -lm

Dear Rui; Many thanks for your reply. I have installed Rtools (rtools43-5958-5975) on my PC and I have R version 4.3.3 and 4.3.2 to install. Also I have installed Rstudio through Anaconda Navigator. But I do not know how to use Rtools for installing the R packages. I would be more than happy if you help me. Sincerely yours > Dear Rui; > I hope this email finds you well. I have a problem

Dear r-devel readers, I have a pretty deep problem with package loading and unloading in the development version of the lme4 package <https://github.com/lme4/lme4>; it's not boiled down to a properly minimal example yet (this has been difficult), but I am posting anyway in the hopes that someone has ideas about how to proceed farther, since I'm nearly stumped. Apologies in advance

Dear R-devel: The Cluster administrators at KU got enthusiastic about testing R-3.2.2 with Intel MKL when I asked for some BLAS integration. Below I forward a performance report, which is encouraging, and thought you would like to know the numbers. Appears to my untrained eye there are some extraordinary speedups on Cholesky decomposition, determinants, and matrix inversion. They had

Though Navigator may mess up any Rtools stuff because it handles the directory trees where packages and dependencies are located, does it not? If so, maybe just reinstall RStudio directly from its website to proceed. Just a guess obviously. Bert On Sat, Mar 16, 2024, 05:09 javad bayat <j.bayat194 at gmail.com> wrote: > Dear Rui; > Many thanks for your reply. I have installed Rtools

Dear all; I found a useful video on youtube that has explained how to install Rtools. I followed the instructions and the problem was solved. " Installing R version 4.0 + RTools 4.0 + RStudio For Data Science (#R #RTools #RStudio #DataScience) - YouTube <https://www.youtube.com/watch?v=h2IPWVXaUuU> " Sincerely On Sat, Mar 16, 2024 at 10:15?AM Bert Gunter <bgunter.4567 at

On 27 April 2017 at 12:01, Johannes Ranke wrote: | | > so it seems to me this must affect all packages in Debian sid that were | > built before the release of R 3.4.0! | | or rather before 14 April 2017, which is when R from revision r72510 was | uploaded to sid as pre-release candidate. Another example with KernSmooth: > library(KernSmooth) KernSmooth 2.23 loaded Copyright

---------- Forwarded message ---------- From: Akhil dua <akhil.dua.12@gmail.com> Date: Wed, Jul 4, 2012 at 10:33 AM Subject: To: r-help@r-project.org Hi everyone I have data on stock prices and market indices and I need to run a seperate regression of every stock on market so I want to write a "for loop" so that I wont have to write codes again and again to run the

When I install an R package with cpp codes such as rrcov via CRAN (under R 3.1.1, using no Makevars file and under Ubuntu 14.04 using GCC 4.8), the cpp code is compiled with the -o3 flag (in fact, looking at the Makeconf file this seem to again be the default since R 3.1.1) But when I install my own package via CRAN it is compiled with the -o2 flag. My questions are what is causing my

On 12 May 2016 at 13:11, Mark van der Loo wrote: | Charles, | | 1. Perhaps this question is better directed at the R-help or | R-pacakge-devel mailinglist. | | 2. It basically means that R itself can only evaluate one R expression at | the time. | | The parallel package circumvents this by starting multiple R-sessions and | dividing workload. | | Compiled code called by R (such as C++ code

Pues parece que el problema si es de lme4, cuya versión 1.0-4 se publicó en septiembre de este año. En la página en cran del paquete pone "The core computational algorithms are implemented using the Eigen C++ library for numerical linear algebra and RcppEigen "glue" " . El tema es que al utilizar esta versión junto con la librería boot, el tiempo de cálculo se incrementa

Am Dienstag, 25. April 2017, 11:21:31 schrieb Dirk Eddelbuettel: > On 25 April 2017 at 16:11, Johannes Ranke wrote: > | This looks similar to what I got this morning when I tested my > | (unreleased) > | backport of R 3.4.0 to Debian jessie. My test was > | > | library(MASS) > | example(rlm) > | > | and there was an object that was not found. I am on a train on the way

But you can easily fall back to R from within Julia; see http://juliastats.github.io/RCall.jl/latest/ On Aug 5, 2016 1:27 PM, "Hadley Wickham" <h.wickham at gmail.com> wrote: > No. > > Hadley > > On Fri, Aug 5, 2016 at 11:12 AM, Kenny Bell <kmbell56 at gmail.com> wrote: > > Is it conceivable that Julia could be ported to use R syntax in a way > that

la libreria lm4 cambio con la versón 3 de R. Fijate en las versiones Prof. Julio Di Rienzo Estadística y Biometría FCA- U.N. Córdoba IBS-RARG President http://sites.google.com/site/juliodirienzo "Biometry, the active pursuit of biological knowledge by quantitative methods." (R.A. Fisher, 1948) 2013/10/24 Carlos Ortega <cof@qualityexcellence.es> > Hola, > > Quizás para