similar to: "LAPACK routine DGESDD gave error code -12" with Debian (PR#2822)

Hi, I'm just wondering if it is planned to include the Lapack routine DGESDD (and friends) in R-1.4.0? This is faster (supposedly by a factor of ~6 for large matrices) than DGESVD which is currently (R-1.3.1) called by La.svd. And if it is not in the plans yet, is there a chance it could be? I've added it to my local version of R-1.3.1 and so far see a factor of 4 improvement over

Lately I'm getting this error quite a bit: Error in La.svd(x, nu, nv) : error code 1 from Lapack routine 'dgesdd' I'm running R 2.5.0 on a 64 bit Intel machine running Fedora (8 I think). Maybe the 64 bit platform is more fragile about declaring convergence. I'm seeing way more of these errors than I ever have before. From R-Help I see that this issue comes up from time to

Error in La.svd(x, nu, nv) : error code 1 from Lapack routine ‘dgesdd’ what resources are there to track down errors like this [[alternative HTML version deleted]]

Dear R helpers, I am working with R 2.4.1 GUI 1.18 (4038) for MacOSX. I have a matrix of 10 000 genes and try to run the following commands: > model.mix<-makeModel (data=data, formula=~Dye+Array+Sample+Time, random=~Array+Sample) > anova.mix<-fitmaanova (data, model.mix) > test.mix<-matest (data, model=model.mix, term="Time", n.perm=100, test.method=c(1,0,1,1))

Hello R-users, during one of my analyses that involve a SVD, I get the following error message: Error in La.svd(x, nu, nv, method) : error code 1 from Lapack routine dgesdd With a search on the R web site, I only found references to error codes 17 and 3 for this particular routine. I also found the Lapack web site, but could not find a list of the possible error messages. If somebody knows what

Dear all I have a big matrix of standardized values (dimensions 285x5829) and R fails to calculate the principal components using prcomp() with the following error message: pc <- prcomp(my.matrix) Error in La.svd(x, nu, nv, method) : error code 1 from Lapack routine dgesdd Is the matrix too big? I'm using R-1.8.1 under Unix (Solaris8) and Linux(Suse 8.2). I tried to perform a principal

Well, CentOS 5.3, which amounts to the same thing. I recently decided to upgrade my main research machine from Fedora Core 8 -> CentOS 5.3. Basically, I was looking to move to a distro with longer 'term-of-life' than the release schedule for Fedora currently allows. The machine is a multi-Opteron box, so both 32- and 64-bit apps natively supported. Since I do a lot of 'linear

Dear Philipp, this is just a tentative answer because debugging is really not possible without a reproducible example (or, at a very bare minimum, the output from traceback()). Anyway, thank you for reporting this interesting numerical issue; I'll try to replicate some similar behaviour on a similarly dimensioned artificial dataset when I have some time (which might not be soon). As for now,

Hi, I know this is not a problem comming from R, but maybe you can still help me. I installed R 1.4.1 on Debian Woody, but I can't start it. I get this message: ~$ R /usr/lib/R/bin/R.bin: error while loading shared libraries: libblas.so.2: cannot open shared object file: No such file or directory Any thoughts? S?bastien Plante

I have installed the binary packages for Debian GNU/Linux release 2.3 (woody) in the U.S. mirror of the CRAN archive. They should propagate to the main CRAN archive within a day and to the other mirrors within two days. These packages have been compiled with gcc-3.0 and g77-3.0. I believe the testing distribution currently provides only a snapshot of gcc-3.0, not the latest released version, so

I have installed the binary packages for Debian GNU/Linux release 2.3 (woody) in the U.S. mirror of the CRAN archive. They should propagate to the main CRAN archive within a day and to the other mirrors within two days. These packages have been compiled with gcc-3.0 and g77-3.0. I believe the testing distribution currently provides only a snapshot of gcc-3.0, not the latest released version, so

I am attempting to perform a pca on a data frame of dimension 5000x19, but when I execute pcapres<-prcomp(pres,center=TRUE) the following error message is returned: Error in La.svd(x, nu, nv, method) : error code 18 from Lapack routine dgesdd Where am I going wrong? I am running R-1.8.0 on Debian. Regards, Laura

Dear all, Has anyone seen the same problem? I tried compiling R-1.9.0 alpha (2004-03-16) on our Opteron box running SUSE Linux ES8. I ran: ./configure --enable-R-shlib --with-blas=goto and got: Source directory: . Installation directory: /usr/local C compiler: gcc -m64 -O2 -g -msse2 -march=k8 -Wall --pedantic C++ compiler: g++ -m64 -O2 -g

Generator Microsoft Word 11 (filtered medium) Hi, I'm the mannova package maintainer. We used La.svd(X, method="dgesvd") in maanova package before. After R-2.3.0, the old La.svd() method was deprecated for option method="dgesvd". I changed maanova code correspondingly, which will call method="dgesdd" instead. But after that, we keep getting below error message

Dear all, The 'make check' step fails for the pacakge mva on IBM AIX. The tail of the Rout log file looks like: > for(factors in 2:4) print(update(Harman23.FA, factors = factors)) Call: factanal(factors = factors, covmat = Harman23.cor) Uniquenesses: height arm.span forearm lower.leg weight 0.170 0.107 0.166

Hi, Over the past six months we have had a few problems with deprecation and Seth Falcon and I want to propose a few additions to the mechanism that will help deal with cases other than the deprecation of functions. In the last release one of the arguments to La.svd was deprecated, but the warning message was very unclear and suggested that in fact La.svd was deprecated. Adding a

Dear all Some computations gave a matrix. The single value decomposition of it worked fine previously, after an system upgrade I get the following error: ----- > La.svd(x,256,256) Error in La.svd(x, nu, nv) : BLAS/LAPACK routine 'DLASCL' gave error code -4 ----- Erroneous Matrix: ftp://usys-ftp.ethz.ch/ITES/STEP/nussbaum/R/matrix-lapack-error4.RData /.csv Operating System: Debian 8

Hi, I wonder where I can find an example of using a function in LAPACK library in a user's own C code. I wrote a C program which will be compiled and linked to produce a DLL file and then loaded into R. I hope to use a function from LAPACK library, for example, dgesdd, in the program. Following R manual, I call the function by F77_CALL(dgesdd) in the program. The program can be compiled

Dear R-lister, is there any function for Meta Analysis in R? (like homogeneity an, risk differences, relative riskm amd odds ratios? Many thanks, Edwin

Dear R'ers, when I e.g. install the integrate2.2-2 package under R1.1.1 (debian2.2) atlas is linked into the library: Installing package `integrate' ... libs gcc -shared -lc -shared -o /usr/lib/R/library/integrate/libs/integrate.so adapt.o adapt_callback.o bsrl.o flfm.o nxprt.o symrl.o wht.o -L/usr/local/lib -lf77blas -lcblas -latlas -lg2c -lm -L/usr/lib/gcc-lib/i386-linux/2.95.2