similar to: problem with R-mathlib standalone

Sorry, forgot to switch the header to the R group.... --- Globe Trotter <itsme_410 at yahoo.com> wrote: > Date: Thu, 2 Mar 2006 19:35:21 -0800 (PST) > From: Globe Trotter <itsme_410 at yahoo.com> > Subject: Re: [R] calling R's library using C > To: Dirk Eddelbuettel <edd at debian.org> > > Hi, Dirk: > > Thanks for all the help. I thought I would

Dear People, I am trying to use R's Math library as standalone, as documented in /src/nmath/standalone. I am using C++ in Debian testing, and the versions are as follows: ii g++-3.0 3.0.3-1 The GNU C++ compiler. ii r-mathlib 1.4.0-1 `GNU S' - Standalone R math library I have a file (rand.cc) as follows. I don't think that lattice.hh or mh.hh are very

Hello, dear R experts! I run R on Debian 'sarge' platform. There is 'r-mathlib' package in Debian distribution, which is described as: $ dpkg --status r-mathlib ... This packages provides the libRmath shared and static libraries which can be called from standalone C or C++ code. Well, I use runif() function in test_runif.c: #include <Rmath.h> main() { // ...

Hello, I can't link a c code with Mathlib according to introduction of R manual "Writing R Extensions", page 60. It is written : "It is possible to build Mathlib, the R set of mathematical functions documented in 'Rmath.h?, as a standalone library 'libRmath? under Unix and Windows. (This includes the functions documented in Section 5.7 [Numerical analysis

Hello, I forgot to tell you that I am using Linux OS. And I can?t find directory "src/nmath/standalone". I will send you the test code I am using and the whole operation process. [credsim at confsys ~/src]$ gcc test1.c -o test1 -lRmath test1.c: In function `main': test1.c:18: warning: assignment makes pointer from integer without a cast test1.c:19: warning: assignment makes

Hi, I'm seeing something that may be a bug in R's standalone math library, which is packaged by Debian as r-mathlib. I reported it to the Debian BTS as http://bugs.debian.org/657573 I'm using Debian squeeze, and the code was tested with r-mathlib 2.11.1-6 (default on stable) and 2.14.1-1 (from testing/unstable). I summarize this report below. The following code with the R math

First of all I would like to join the chorus of approval over the release of R 1.0.0. It really is an excellent piece of software. I'm sure you will astonish us again with Omega. I have a query about Mathlib. It is such a nice collection of functions that it would be nice to use it in other software, not necessarily related to R. Is it possible to build Mathlib separately, and/or install

HI, Using c11<- 0.01 c12<- 0.01 c1<- 0.10 c2<- 0.10 One possible problem is that: dim(res5) #[1] 513? 20 res6<-aggregate(.~m1+n1+m+n,data=res5[,c(1:6,9:12,21:24)] ,max) #Error in `[.data.frame`(res5, , c(1:6, 9:12, 21:24)) : ?# undefined columns selected A.K. ________________________________ From: Joanna Zhang <zjoanna2013 at gmail.com> To: arun <smartpink111 at

Full_Name: Morten Welinder Version: 2 OS: Solaris/space/gcc2.95.2 Submission from: (NULL) (65.213.85.217) I changed src/nmath/standalone/test.c to read: --------------------------------------------------------------------------------- #define MATHLIB_STANDALONE 1 #include <Rmath.h> #include <stdio.h> int main() { double x; for (x = 99990; x <= 100009; x++) printf

In the hope of some meaningful response and ignoring the risk of further abuse, let me try to clarify the issue here. I have re-read the 'Writing R Extensions' manual. It seems to me that it clearly says R API functions can be called from from C++ programs, and the API includes the special values ISNAN() and R_FINITE() and the missing test ISNA(). R_FINITE is no problem. It is

Dear R-users, I would like to maximize the function g above which depends on 4 parameters (2 vectors, 1 real number, and 1 matrix) using optim() and BFGS method. Here is my code: # fonction to maximize g=function(x) { x1 = x[1:ncol(X)] x2 = x[(ncol(X)+1)] x3 = matrix(x[(ncol(X)+2):(ncol(X)+1+ncol(X)*ncol(Y))],nrow=ncol(X),ncol=ncol(Y)) x4 = x[(ncol(X)+1+ncol(X)*ncol(Y)+1):length(x)]

R versions 2.1.0 to present. Examples shown were computed under Windows R-devel, current SVN, but ix86 Linux shows similar behaviour (sometimes NaN or -Inf rather than Inf, depending on the compiler and optimization level used). The replacement pgamma algorithm used from R 2.1.0 has an inadequate design and no supporting documentation whatsoever. There is no reference given to support the

Dear R-help, I'd like ask for your opinion on choosing the "right" strategy for a particular dataset. We conducted 24-hour electric field measurements on 90 subjects. They are grouped by job (2 categories) and location (3 categories). There are four exposure metrics assigned to each subject. An excerpt from the data: n job location M OA UE all 0 job1 dist_200 0.297 0.072 0.171

Hi, I am new to clustering and was wondering why pvclust using "maximum" as distance measure nearly always results in p-values above 95%. I wrote an example programme which demonstrates this effect. I uploaded a PDF showing the results Here is the code which produces the PDF file: ------------------------------------------------------------------------------------- s <-

Dear R-list members, I have a problem with translating a mathematica script into R. The whole script is at the end of the email (with initial values for easy reproduction) and can be pasted directly into R. The problematic part (which is included below of course) is <--- Original Mathematica ---> (* p_svbar *) UiA = Ni (Dsi - 2Di A + A^2)/2; UiiA = Nii (Dsii - 2Dii A + A^2)/2; psvbar =

Hi, Thanks, everyone for all the help! So, here is my calling function in C (called test.c): #include<stdio.h> #include<stdlib.h> #include<Rmath.h> int main(void) { printf("%f \n",pchisq(2.,7., 1, 0)); printf("%f \n",pnchisq(2.,7.,0., 1, 0)); return EXIT_SUCCESS; } I compile using: gcc test.c -I/usr/lib/R/include

Full_Name: Version: 2.7.1 (2008-06-23) OS: windows vista Submission from: (NULL) (216.82.144.137) Hello, I have been working with various probability distributions in R, and it seems the gamma distribution is inaccurate for some inputs. For example, qgamma(1e-100, 5e-101, lower.tail=FALSE) gives: 1.0. However, it seems this is incorrect; I think the correct answer should be

Dear R-users I have a problem choosing initial points for the function arms() in the package HI I intend to implement a Gibbs sampler and one of my conditional distributions is nonstandard and not logconcave. Therefore I'd like to use arms. But there seem to be a strong influence of the initial point y.start. To show the effect I constructed a demonstration example. It is reproducible

Hello, I have been working with various probability distributions in R, and it seems the gamma distribution is inaccurate for some inputs. For example, qgamma(1e-100, 5e-101, lower.tail=FALSE) gives: 1.0. However, it seems this is incorrect; I think the correct answer should be 0.082372029620717283. When I check these numbers using pgamma, I get: pgamma(1,5e-101, lower.tail=FALSE) =

Hi Developers, The alpha, compiles successfully, but it is failing make check-all (on two seperate machines, both FreeBSD 6.1). Here is the version string: platform i386-unknown-freebsd6.1 arch i386 os freebsd6.1 system i386, freebsd6.1 status alpha major 2 minor 3.0 year 2006 month 03 day 27 svn rev