similar to: error in qbeta (PR#1201)

>Date: Fri, 2 May 2003 10:03:23 -0400 (EDT) From: Morten Welinder <welinder@rentec.com> >To: p.dalgaard@biostat.ku.dk >CC: r-devel@stat.math.ethz.ch, R-bugs@biostat.ku.dk >Subject: Re: [Rd] qbeta hang (PR#2894) > >Ok, I can confirm that it does not, in fact, loop forever. Just a close >approximation. ... >There are lots of other places that worry me with respect to

The current development version dies in qbeta() when compiled with egcs -O, egcs 1.0.2 and glibc 2.0.7 (RedHat versions). Since this also kill the F and t distributions, it doesn't exactly do wonders for R's usefulness... Anyone else seeing this or has my setup just gone out of whack? It does look pretty much like a clear compiler bug when inlining math functions (storing temporaries

HI All: Does anyone know the code behind the qbeta function in R? I am using it to calculate exact confidence intervals and I am getting 'NaN' at places I shouldnt be. Heres the simple code I am using: k<-3 > x<-NULL > p<-rbeta(k,3,3)# so that the mean nausea rate is alpha/(alpha+beta) > min<-10 > max<-60 > n<-as.integer(runif(3,min,max)) > for(i in

Hi there, this is just to let you know that the qbeta function, which was copied from R into Gnumeric, has been confirmed to be miscompiled by gcc 2.96 on Linux. (That's Red Hat's compiler.) This shows by qbeta(0.025,4,0.5) ending up taking the wrong branch of "if (alpha <= 0.5)". We compile things in a different context, so this may or may not affect you. The qbeta

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.

I've discovered an infelicity (I guess) in qbeta(): it's not a bug, since there's a clear warning about lack of convergence of the numerical algorithm ("full precision may not have been achieved"). I can work around this, but I'm curious why it happens and whether there's a better workaround -- it doesn't seem to be in a particularly extreme corner of parameter

make check of R-alpha_2006-04-08_r37675 fails on Debian GNU/Linux 3.1 running on an Intel P4 computer. > version _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status

I came across the message below and decided to respond. I don't use R but I do use other FSF products and I am a believer in making high quality software freely available, particularly for basic mathematical and statistical functions. I can thorougly recommend TOMS Algorithm 708 but I believe there are a couple of problems from you point of view. Firstly there may be restrictions on how it

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

Full_Name: Morten Welinder Version: 1.6.1 OS: Solaris/sparc Submission from: (NULL) (65.213.85.144) qbeta(0.1, 1e-8, 0.5, TRUE, FALSE) seems to hang for me.

Hi, I sometimes play around with extreme parameters for distributions and found that qbeta is not always monotone as the following example shows. I don't know whether this is serious enough to submit a bug report (as this example is near to the limitations of floating point arithmetic). Josef > x <- qbeta((0:100)/100,0.01,5) > x [1] 0.000000e+00 1.253990e-201 1.589622e-171

Full_Name: Tim Massingham Version: 1.2.2 OS: Debian/Linux Submission from: (NULL) (131.111.8.68) In 1.2.2 sources (also in 0.90.1. I haven't been able to check other versions) Line 103 in qbeta.c should read: w = y * sqrt(h + r) / h - (t - s) * (r + 5. / 6. - 2 / (3 * h)); since otherwise the 5 / 6 will evaluate to zero (I think). The Statlib fortran code uses five / six instead. Cheers,

>>>>> Ben Bolker >>>>> on Wed, 25 Mar 2020 21:09:16 -0400 writes: > I've discovered an infelicity (I guess) in qbeta(): it's not a bug, > since there's a clear warning about lack of convergence of the numerical > algorithm ("full precision may not have been achieved"). I can work > around this, but I'm

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

>>>>> 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,

I need to run qbeta on a set of 500K different parameter pairs (with a fixed quantile). For most pairs qbeta finds the solution very quickly but for a substantial minority of the cases qbeta is very slow. This occurs when the solution is very close to zero. qbeta is getting answers to a precision of about 16 decimal places. I don't need that accuracy. Is there any way to set the precision of

> > Hi All: > > I am using R to calculate exact 95% confidence interval using Clopper > Pearson method. I am using the following code but it seems to get into a > loop and not get out of it, it goes on forever although I am looping it > only 10 times across 63 sites with 10 observations per site. I was hoping > to get some help. > > Thanks > Anamika >

I'm writing a C program and I'd like to include in it some R routine (quantile functions, typically). I found the functions I have to use (qnorm.c qbeta.c ecc) e some include (nmath.h rmath.h ecc). But I can't compile the project, I receive linker error. Somebody can help me? I say, if I want to include qbeta (for example) in a project of mine, what should I do?

Linking my VC++ application with the standalone Rmath library yields the following; ------ Build started: Project: Complex plugin, Configuration: Debug Win32 ------ Linking... Creating library .\../Debug/complex_plugin.lib and object .\../Debug/complex_plugin.exp libRmath.a(mlutils.o) : warning LNK4217: locally defined symbol __iob imported in function _REprintf libRmath.a(dbeta.o) :

(1) ...need to speed up a monte-carlo sampling...any suggestions about how I can get R to use all 8 cores of a mac pro would be most useful and very appreciated... (2) spent the last few hours trying to get pnmath to compile under os- x 10.5.4... using gcc version 4.2.1 (Apple Inc. build 5553) as downloaded from CRAN, xcode 3.0... ...xcode 3.1 installed over top of above after