similar to: How to menage decimals in order to obtain accurate estimates

Thank you Martin for giving to know and developing 'Rmpfr' library for unlimited size integers (GNU C GMP) and arbitrary precision floats (GNU C MPFR): https://cran.r-project.org/package=Rmpfr My question is: In the long term (For R3.7.0 or R3.8.0): Does it have sense that CMP substitutes INTSXP, and MPFR substitutes REALSXP code? With this we would achieve that an integer is always an

Hello. I have installed R with dnf. Also I have installed gmp and gmp-devel with dnf (I think gmp was already installed). In R I did > install.packages('Rmpfr') But then I get configure: error: GNU MP not found, or not 4.1.4 or up, see http://gmplib.org What must I do? [[alternative HTML version deleted]]

Thank you Gabriel for valuable insights on the 64-bit integers topic. In addition, my statement was wrong, as Python3 seems to have unlimited (and variable) size integers. Here is related CPython Code: https://github.com/python/cpython/blob/master/Objects/longobject.c Division between Int-32 and Int-64 seems to only happen in Python2. Best, Juan El mi?rcoles, 29 de mayo de 2019, Gabriel

Are integers strictly a signed 32 bit number on R even if I am running a 64 bit version of R on a x86_64 bit machine? I ask because I have integers stored in a hdf5 file where some of the data is 64 bit integers. When I read that into R using the hdf5 library it seems any integer greater than 2**31 returns NA. Any solutions? Thanks, Theo [[alternative HTML version deleted]]

Are integers strictly a signed 32 bit number on R even if I am running a 64 bit version of R on a x86_64 bit machine? I ask because I have integers stored in a hdf5 file where some of the data is 64 bit integers. When I read that into R using the hdf5 library it seems any integer greater than 2**31 returns NA. Any solutions? Thanks, Theo [[alternative HTML version deleted]]

If I have a package A whose NAMESPACE has ImportFrom(B, <B-syms>)) and a package B whose NAMESPACE has ImportFrom(A, <A-syms>) and we can assume that <A-syms> and <B-syms> are disjoint. The clue would be that I only import relatively little from one namespace to the other. I currently get an error Error in loadNamespace(imp[[1L]], c(lib.loc, .libPaths())) :

I've been asked in private, but am answering in public so others can comment / or find this answer in the future after a web search. This is about the package 'Rmpfr' (R interface to MPFR, the GNU C library for arbitrary precise numbers). > How can you build a vector of mpfr numbers sequentially? > Typically I would do something like the following (and try to > replace the

Despite the need to focus on pbeta, I'm still willing to put in some effort. But I find it really helps to have 2-3 others involved, since the questions back and forth keep matters moving forward. Volunteers? Thanks to Martin for detailed comments. JN On 2020-03-26 10:34 a.m., Martin Maechler wrote: >>>>>> J C Nash >>>>>> on Thu, 26 Mar 2020

Hi, I am working with large numbers and identified that R looses precision for such high numbers. The precision is lost exactly when the number is equal or larger than 53 bits. See the following output which shows that the numbers below 53 bit have proper precision: > 2^53 [1] 9007199254740992 > 2^53-1 [1] 9007199254740991 > 2^53-2 [1] 9007199254740990 Now, see the numbers above 53

Given that a number of us are housebound, it might be a good time to try to improve the approximation. It's not an area where I have much expertise, but in looking at the qbeta.c code I see a lot of root-finding, where I do have some background. However, I'm very reluctant to work alone on this, and will ask interested others to email off-list. If there are others, I'll report back.

Dear Team, Maybe somebody already tried to install mpfr and gsl packages for R on SLES. Exactly I try to install Rmpfr_0.6-1.tar.gz and gsl_1.9-10.3.tar.gz on SLES11 SP4. These are the available packages from official SLES SDK media: rtest:/home/ruser # rpm -qa | grep -i gsl gsl-devel-1.11-1.30 gsl-1.11-1.30 rtest:/home/ruser # As I understand gsl is from 1.11 till 1.30 level.

Hi, I have a data frame with one column containing string of the form "ABC...|XYZ..." where ABC etc are fields of 6 alphanumeric characters each and XYZ etc are fields of 8 alphanumeric characters each; "|" is a mandatory separator; I do not know in advance how many fields of each kind will each row contain. I need to extract these fields from the string. === How do I do that?

Hello list, I'm just getting started with R, and I'm trying to determine how R treats large numbers that have decimals. Take the following two examples: > x <- c(999999999999999.9) > sprintf("%.5f",x) [1] "999999999999999.87000" > y <- c(9999999999999999.9) > sprintf("%.5f",y) [1] "10000000000000000.00000" I realize that I have

Le 18/02/2023 ? 21:44, J C Nash a ?crit?: > I wrote first cut at unirootR for Martin M and he revised and put in > Rmpfr. > > The following extends Ben's example, but adds the unirootR with trace > output. > > c1 <- 4469.822 > c2 <- 572.3413 > f <- function(x) { c1/x - c2/(1-x) }; uniroot(f, c(1e-6, 1)) > uniroot(f, c(1e-6, 1)) > library(Rmpfr) >

I wrote first cut at unirootR for Martin M and he revised and put in Rmpfr. The following extends Ben's example, but adds the unirootR with trace output. c1 <- 4469.822 c2 <- 572.3413 f <- function(x) { c1/x - c2/(1-x) }; uniroot(f, c(1e-6, 1)) uniroot(f, c(1e-6, 1)) library(Rmpfr) unirootR(f, c(1e-6, 1), extendInt="no", trace=1) This gives more detail on the iterations,

>>>>> Juan Telleria Ruiz de Aguirre >>>>> on Thu, 30 May 2019 18:46:29 +0200 writes: >Thank you Gabriel for valuable insights on the 64-bit integers topic. >In addition, my statement was wrong, as Python3 seems to have unlimited >(and variable) size integers. .... If you are interested in using unlimited size integers, you could use the

I have been asked (by Roger; thank you for the good question, and I hope it's fine to answer to the public) : > with Pi a sparse matrix and x,y, and ones > compatible n-vectors ? when I do: >> c(t(x) %*% Pi %*% ones, t(ones) %*% Pi %*% y ) > [[1]] 1 x 1 Matrix of class "dgeMatrix" > [,1] [1,] > 0.1338527 >

>>>>> Juan Telleria Ruiz de Aguirre >>>>> on Mon, 3 Jun 2019 06:50:17 +0200 writes: > Thank you Martin for giving to know and developing 'Rmpfr' library for > unlimited size integers (GNU C GMP) and arbitrary precision floats (GNU C > MPFR): > https://cran.r-project.org/package=Rmpfr > My question is: In the long term

All, Martin: Thanks for this and all the other things you are doing to both drive R forward and engage more with the community about things like this. Apologies for missing this discussion the first time it came around and if anything here has already been brought up, but I wonder what exactly you mean when you want recycling behavior. Specifically, based on an unrelated discussion with Henrik

Hi: I'm trying to reproduce an arbitrary precision constant from 'Why and How to Use Arbitrary Precision' (Ghazi et al., COMPUTING IN SCIENCE & ENGINEERING May/June 2010; http://perso.ens-lyon.fr/philippe.theveny/cise.pdf): d = 173746a + 94228b ? 78487c where: a = sin(1022), b = log(17.1), and c = exp(0.42). Ghazi et al. report: d = ?1.341818958e?12 whit IEEE-754 quadruple