similar to: Rmpfr question

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

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.

Hi, I'm working on an S4 class that is expected to behave like an array. I have some difficulties when defining '[' and I wonder if someone could point me to the right direction: 1) Call the S4 object "obj" 2) Assume dim(obj) = c(10, 4, 2) 3) Suppose someone calls: obj[1:3,] , which is a mistake, given dim(obj); how do I detect such situations? Thank you very much for

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

Dear R users, I have to calculate gamma functions for negative numbers beyond -171.4. e.x. gamma(-500.4) I got following: > gamma(-170.4) [1] -5.824625e-308 > gamma(-171.4) [1] 0 Warning message: underflow occurred in 'gammafn' I have tried to use a recursion getting values a little futher -180. How could I solve this problem? Thank you beforehand. Chuse.

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

Hello R-Experts, I want to calculate values like 15^200 or 17^300 in R. In normal case it can calculate the small values of b (a^b). I have fixed width = 10000 and digits = 22 but still answers are Inf. How to deal the cases like these? Thanks in advance. Regards, rehena [[alternative HTML version deleted]]

Normal 0 21 false false false MicrosoftInternetExplorer4 Dear R-helpers,   I was wondering whether there are any good books and/or website links that introduce mark-recapture analysis in R. In

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?

As a side note, Splus makes sin(x) NA, with a warning, for abs(x)>1.6*2^48 (about 4.51e+14) because more than half the digits are incorrect in sin(x) for such x. E.g., in R we get: > options(digits=16) > library(Rmpfr) > sin(4.6e14) [1] -0.792253849684354 > sin(mpfr(4.6e14, precBits=500)) 1 'mpfr' number of precision 500 bits [1]

Hi all. I tried to subclass FXSettings in order to add some functionality to it but I ran into the following problem. The code which shall be executed looks like this: def test reg = Registry.new("test.reg") reg.Parse end The Registry class basically looks this way: require "fox12" include Fox class Registry < FXSettings

This question is more out of curiosity than a complaint or suggestion, but I'm just wondering. The behavior of R on calculations that result in NaN seems a bit inconsistent. # this is expected: > 0/0 [1] NaN # but this gives a warning > sin(Inf) [1] NaN Warning message: In sin(Inf) : NaNs produced # and this again does not > exp(NaN) [1] NaN Conceptually, I like to think that R

I could swear that this was working just last week, but now when I run the Adobe Acrobat reader, it hangs. If I run it "directly" (/usr/bin/acroread) with -DEBUG as the first argument, I get an infinite loop of: expr: syntax error I tried removing and reinstalling it, but no change. Any ideas? -- Mark Hull-Richter DATAllegro (www.datallegro.com) 85 Enterprise, Second Floor, Aliso

>>>>> J C Nash >>>>> on Thu, 26 Mar 2020 09:29:53 -0400 writes: > 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,

Dear list, I would like to export a matrix to a TXT-File by using write.csv (not necessarily). Is there a way to add a header (with additional informations concerning the project) spanning multiple lines to this file before the actual data are listed up? Should look like this: date: filename: number of permutations: ------------ data (as a matrix) Any suggestions? Thnx in advance.

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

This is also strange: qbeta <- function (p, shape1, shape2, ncp = 0, lower.tail = TRUE, log.p = FALSE) { if (missing(ncp)) .Call(C_qbeta, p, shape1, shape2, lower.tail, log.p) else .Call(C_qnbeta, p, shape1, shape2, ncp, lower.tail, log.p) } Since the default value is 0 for non-centrality, it seems like the logic above is wrong. When ncp=0, C_qnbeta would be called

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]]

On Wed, Apr 29, 2015 at 8:12 PM, Paul Gilbert <pgilbert902 at gmail.com> wrote: > > As I recall, several packages mask the simulate generic in stats, if you > are looking for examples. > FWIW, here is a list of base* functions masked** by CRAN packages: https://github.com/gaborcsardi/rfunctions/blob/master/rfunctions.md Look at the long table in the end. simulate indeed comes up