similar to: The old Fortran underscore problem

Dear R Developers, I should have had the Design library running in R by now but have kept putting off changing some calls to LINPACK routines to use those builtin to R. Specifically I call dqrsl1 and dqr. Would it be an easy task to put those in the next release of R? If not I'll finally bite the bullet and get back into reading LINPACK documentation (which I have but haven't examined

Hi everybody. I'm studying the Harrell's book on regression modeling strategies, and I'd like to replicate the examples using R (instead of S+). So how's going the porting of the hmisc and design libraries? Are there available, though in beta version? TIA, Stefano Calza -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hello, I'm trying to install a package that requires a Fortran compiler (Hmisc) using R CMD INSTALL. I downloaded the package source onto my Desktop, unzipped it, and then typed: R CMD INSTALL /Users/brianbeckage/Desktop/Hmisc * Installing *source* package 'Hmisc' ... ** libs g77 -fno-common -g -O2 -c cidxcn.f -o cidxcn.o g77 -fno-common -g -O2 -c cidxcp.f -o cidxcp.o g77

Under Ubuntu dapper, after installing packages gcc and g77, under platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 2.1 year 2005 month 12 day 20 svn rev 36812 language R I get an error when trying to update.packages('Hmisc'): gcc -I/usr/lib/R/include -fPIC -g -O2 -c ranksort.c -o ranksort.o In file included

In my package 'glmmML' I'm using old C code and linpack in the optimizing procedure. Specifically, one part of the code looks like this: F77_CALL(dpoco)(*hessian, &bdim, &bdim, &rcond, work, info); if (*info == 0){ F77_CALL(dpodi)(*hessian, &bdim, &bdim, det, &job); ........ This usually works OK, but with an ill-conditioned data

Hi, I've recently purchased PowerBookG4 (panther) and installed RAqua 1.8.1. I also installed gcc version 3.3 through Xcode tools. But, for some reason, I'm having a hard time getting gcc work with R. For example, I get the following error while installing Hmisc package. I would appreciate any suggestion to fix this problem. Thanks Kosuke * Installing *source* package

I upgraded my system to Fedora Core 7 and got a compilation problem when installing Hmisc package. According to the error messages (shown below), I have tried to updated all of my glibc, gcc, automake rpm packages, but that did not help. Could you help me pointed out what package I have missed? Thank you. > version _ platform i386-redhat-linux-gnu arch i386 os linux-gnu system i386, linux-gnu

> > On 9 Feb 2017, at 16:00, G?ran Brostr?m <goran.brostrom at umu.se> wrote: > > > > In my package 'glmmML' I'm using old C code and linpack in the optimizing procedure. Specifically, one part of the code looks like this: > > > > F77_CALL(dpoco)(*hessian, &bdim, &bdim, &rcond, work, info); > > if (*info == 0){ > >

Frank Harrell suggested I re-post with information about the version of R Heres's the information: > > version > _ > platform powerpc-apple-darwin6.8 > arch powerpc > os darwin6.8 > system powerpc, darwin6.8 > status > major 2 > minor 0.1 > year 2004 > month 11 > day 15 > language R Here's what happens

> On 10 Feb 2017, at 14:53, G?ran Brostr?m <goran.brostrom at umu.se> wrote: > > Thanks to all who answered my third question. I learned something, but: > > On 2017-02-09 17:44, Martin Maechler wrote: >> >>>> On 9 Feb 2017, at 16:00, G?ran Brostr?m <goran.brostrom at umu.se> wrote: >>>> >>>> In my package 'glmmML'

I am running Ubuntu 7.10 and R-2.6.0, and I am having trouble updating packages. There appears to be a problem involving gfortran. For example, here is the output of an attempt to update the Hmisc package. * Installing *source* package 'Hmisc' ... ** libs gfortran -fpic -g -O2 -c cidxcn.f -o cidxcn.o gfortran -fpic -g -O2 -c cidxcp.f -o cidxcp.o gfortran -fpic -g -O2 -c

Hello, I need to plot multiple confidence intervals for the same model parameter e.g. so for the same value of the parameter in point x_1 I would like to see four different confidence intervals so that I can compare the accuracy e.g. boot basic vs normal vs my own vs classic lm CI etc. I like very very much the plotCI implemented here: http://cran.r-project.org/web/packages/plotrix/index.html

Dear developers, I am trying to reproduce the results of applying opt -O3 to a source file in the form of LLVM IR. I want to get the same IR by manually ordering the passes used by O3 and passing them to opt. To illustrate what I am doing on an example, as an input I use linpack benchmark from the LLVM test suite[1]: 1. First I produce the intermediate representation using clang: clang -O3

I think this has to do with how the pass manager is populated when we give -O3 vs when we give particular pass names. Some passes have multiple createXYZPass() methods that accept arguments too. These methods call non-default pass constructors, which in turn cause the passes to behave in a different manner. eg: Pass *llvm::createLICMPass() { return new LegacyLICMPass(); } Pass

The first one failed on a diff: ******************** TEST (simple) 'sse.expandfft' FAILED! ******************** Execution Context Diff: /home/rkotler/llvmpb3/build/projects/test-suite/tools/fpcmp: Compared: 1.139094e-07 and 1.159249e-07 abs. diff = 2.015500e-09 rel.diff = 1.738626e-02 Out of tolerance: rel/abs: 1.600000e-02/0.000000e+00 ******************** TEST (simple)

I'm getting three failures. TEST-FAIL: exec /home/rkotler/llvmpb3/build/projects/test-suite/SingleSource/UnitTests/Vector/SSE/sse.expandfft TEST-RESULT-exec-time: user 0.3200 TEST-RESULT-exec-real-time: real 0.3172 TEST-FAIL: exec /home/rkotler/llvmpb3/build/projects/test-suite/SingleSource/UnitTests/Vector/SSE/sse.stepfft TEST-RESULT-exec-time: user 0.4000

man for `qr` says that the function uses LINPACK's DQRDC, while it in fact uses DQRDC2. ``` The QR decomposition of the matrix as computed by LINPACK or LAPACK. The components in the returned value correspond directly to the values returned by DQRDC/DGEQP3/ZGEQP3 ```

Hello. I am trying to invert a matrix, and I am finding that I can get different answers depending on whether I set LAPACK true or false using "qr". I had understood that LAPACK is, in general more robust and faster than LINPACK, so I am confused as to why I am getting what seems to be invalid answers. The matrix is ostensibly the Hessian for a function I am optimizing. I want to get

I'm probably misunderstanding something in "Writing R Extensions" version 1.0.0. In the chapter on the R API, section 4.7, it is stated that the functions listed in R_ext/Linpack.h are available to users' Fortran code. I am developing a developing a library of ode solvers, based on lsoda and ddassl, and which in turn call some routines from linpack and double precision blas. I

Ordinary functions should not alter their inputs but in R-2.15.2 svd(LINPACK=TRUE,X) does. (It worked in 2.15.0 but not in 2.15.1 or 2.15.2 and became deprecated in 2.15.2.) > X <- matrix(c(1,2,3, 5,7,11, 13,17,19), 3, 3) > X [,1] [,2] [,3] [1,] 1 5 13 [2,] 2 7 17 [3,] 3 11 19 > svd(X, LINPACK=TRUE)$d [1] 31.9718214 2.3882717 0.3143114 Warning message: