similar to: Updating to nlme 3.1-62 failing from source (OS X)

Dear All, I have just updated R to the version 2.6.2 on F8 (with the official F8 rpm). However, when running as root the following command: update.packages(checkBuilt=T) I get a bunch of errors like the ones below. Any ideas? Thanks in advance, Paul ----------------------------------------------- * Installing *source* package 'nlme' ... ** libs gcc -m32 -std=gnu99 -I/usr/include/R

dear list, I am wondering if one can find examples and/or more detailed descriptions of modifications needed when going beyond standard corStruct classes (i.e. those already provided for use in lme/nlme)? When I looked at pages 238-239 of Pinheiro/Bates (2000): Mixed-effects models in S and S-plus, I found that I would need a bit more explicit guidance what to do for implementing a new

>From http://bugs.r-project.org/cgi-bin/R: If you are not sure whether you have observed a bug or not, it is a good idea to ask on the mailing list R-Help by sending an e-mail to r-help at stat.math.ethz.ch rather than submitting a bug report. I'm wondering whether to submit a bug report on this: ============================================================== >

Hi LLVM and GCC developers, My sincere thanks will goto: * Duncan, the core developer of llvm-gcc and dragonegg http://llvm.org/devmtg/2009-10/Sands_LLVMGCCPlugin.pdf * David, the innovator and developer of GCC https://dmalcolm.fedorapeople.org/gcc/global-state/requirements.html and others who give me kind response for teaching me patiently and carefully about how to migrate GCC v4.8.x to

Dear R users, I fitted a repeated measure model without random effects by using lme. I will use the estimates from that model as an initial estimates to do multiple imputation for missing values of the response variable in the model. I am trying to extract the within group correlation matrix or covariance matrix. here is my code: f = lme(y ~x0+x1+trt+tim+x1:tim +tim:trt,random=~-1|subj,

Hi, I have been using the function lme() of the package nlme to model grouped data that is auto-correlated in time and in space (the data was collected on different days via a moving monitor). I am aware that I can use the correlation classes corCAR1 and corExp (among other options) to model the temporal and spatial components of the auto-correlation. However, as far as I can tell, I can only

Hi, I have a question on why gcc and llvm-gcc compile the following simple code snippet differently: extern int a; extern int *b; void foo() { int i; for (i = 1; i < 100; ++i) a += b[i]; } gcc compiles this function hoisting the load of the global variable "b" outside of the loop, while llvm-gcc keeps it inside the loop. This results in slower code on the part of

I don't understand your point. Which version is better does NOT depend on what inputs are passed to the function. The compiled code for (as per llvm) f1 will always take less time to execute than f2. for x > 0 => T(f1) < T(f2) for x <= 0 => T(f1) = T(f2) where T() is the time to execute the given function. So always T(f1) <= T(f2). I would call this a missed

Dear R-Users I have a problem accessing some values in the output from the summary of an lme fit. I fit the model below: ggg <- lme (ST~ -1 + as.factor(endp):Z.sas + as.factor(endp), data=dat4a, random=~-1 + as.factor(endp) + as.factor(endp):Z.sas|as.factor(trials), correlation = corSymm(form=~1|as.factor(trials)/as.factor(id)), weights=varIdent(form=~1|endp)) hh

Good day R-Users, I have a problem accessing some values in the output from the summary of an lme fit. The structure of my data is as shown below (I have attached a copy of the full data). id trials endp Z.sas ST 1 1 -1 -1 42.42884 1 1 1 -1 48.12007 2 1 -1 -1 43.42878 2 1 1 -1

Hi, I've got a problem that sounds a lot like this, http://r.789695.n4.nabble.com/Re-R-R-2-12-0-hangs-while-loading-RGtk2-on-FreeBSD-td3005929.html under windoze 7. but it seems to hang with this stack trace, #0? 0x77830190 in ntdll!LdrFindResource_U () ?? from /cygdrive/c/Windows/system32/ntdll.dll building goes as follows, $ ./R CMD INSTALL --no-test-load nlme_3.1-97.tar.gz *

Hello Mentors, I am currently finding bug in Local Function related optimization due to which runtime failures are observed in some test cases, as those test cases are containing very large function with recursion and object oriented code so I am not able to find a pattern which is causing failure. So I tried following simple case to understand expected behavior from this optimization. Consider

Hi, I think that Clang erroneously discards a function annotated with __attribute__((constructor)) when flags -Os -fno-common are given. Test case below. What do you think? Thanks. ----8<--------8<--------8<--------8<--------8<--------8<-------- $ cat ctor.c int val; static void __attribute__((constructor)) init_fn(void) { val = 1; } int main(int argc, char *argv[])

Thank You, It means vmovdqa64 zmm22, zmmword ptr [rip + .LCPI0_0] # zmm22 = [8,9,10,11,12,13,14,15] zmm22 will contain 64 bit constant values which are indexes here zmm22=8, 9, 10, 11, 12,13,14,15. not the values loaded from these locations. and zmm2 contains constant 4000. so, vpmuludq zmm14, zmm10, zmm2 ; will multiply the indexes values with 4000, as for array b the stride is 4000. zmm14=

Let's say I would like to look inside the function corBrownian in library (ape). When I type in the function name I get the following, which is not nearly the detail that goes into this function. I am wondering how to begin cracking this function open (and others) so I can learn more about it and perhaps code my own corClass one day. Thanks. > corBrownian function (value = 1, phy, form

with some dirty hack , I've made xray runtime 'built' on windows , but unfortunately I haven't enough knowledge about linker and the runtime, and finally built executable didn't run. I'd like to share my changes here , hopes somebody help me to make it run on windows. in AsmPrinter, copy/paster xray for coff target InstMap =

Hi, I have a benchmark (mcf) that is currently slower when compiled with clang compared to gcc 8 (~10%). It seems that a hot loop has a few differences, where one interesting one is that while clang stores an incremented value in each iteration, gcc waits and just stores the final value just once after the loop. The value is a global variable. I wonder if this is something clang does not do

Hi, On Wed, Jul 12, 2017 at 2:21 AM, Rui Ueyama via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > Thanks, Bruce. This is a very interesting optimization. > > lld doesn't currently have code to support that kind of code shrinking > optimization, but we can definitely add it. It seems that essentially we > need to iterate over all relocations while rewriting

A customer has reported a performance problem, which I have eventually tracked down to the following situation: Consider this program: int foo(int *p, volatile int *q, int n) { int i, s = 0; for (i = 0; i < n; ++i) s += *p + *q; return s; } LLVM's analysis indicates that *p and *q can alias, even though *p is non-volatile whereas *q is volatile. I don't have the

Full_Name: Benjamin Tyner Version: 2.6.0 RC 2007-10-01 r43043 OS: WinXP Submission from: (NULL) (171.161.224.10) platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status RC major