similar to: error code 1 from Lapack routine 'dsyevr'

On 31/01/2015 14:15, eigen wrote: > Hi, > > I got an error message in my program saying > > "Error in eigen(gene_intersection.kernel) : > error code 1 from Lapack routine 'dsyevr' > Execution halted". > > As you see, I was trying to compute the eigenvalues of a matrix but got this > error. Is there anyone who knows what this error means and how I

Thank you for your reply. Do you have any idea of how to get rid of the errors? I tried Null function to calculate eigenvectors and nearPD to get approximate positive definite matrix first but they also had errors. -- View this message in context: http://r.789695.n4.nabble.com/error-code-1-from-Lapack-routine-dsyevr-tp4702571p4702639.html Sent from the R devel mailing list archive at

Dear all I am so glad the R can provide the efficient calculate about eigenvector and eigenvalue. However, i have some puzzle about the procedure of eigen. Fristly, what kind of procedue does the R utilize such that the eigen are obtained? For example, A=matrix(c(1,2,4,3),2,2) we can define the eigenvalue lamda, such as det | 1-lamda 4 | =0 | 2 3-lamda | then

On 2 February 2015 at 10:07, William Dunlap <wdunlap at tibco.com> wrote: <snip> > > If all goes well then > eigen(lastEigenX) > will cause the same error and you or someone on this list can see what > is odd about that matrix (e.g., by looking at its singular values). Preferably *not* this list as this doesn't really seem to be about developing R or with/for

While using the rmvnorm function, I get the error: Error in eigen(sigma, sym = TRUE) : error code 5 from Lapack routine 'dsyevr' The same thing happens when I try the eigen() function on my covariance matrix. The matrix is a symmetric 111x111 matrix. Well, it is almost symmetric; there are slight deviations from symmetry (the largest is 3e-18). I have this in an MCMC loop, and it

hello, i want to compute the top k eigenvalues+eigenvectors of a (large) real symmetric matrix. since it doesn't look like any top-level R function does this, i'll call LAPACK from a C shlib and then use .Call. the only LAPACK function i see to do this in R_ext/Lapack.h is dsyevx. however, i know that in LAPACK dsyevr can also return a partial eigendecomposition. why is dsyevr not

hello, i want to compute the top k eigenvalues+eigenvectors of a (large) real symmetric matrix. since it doesn't look like any top-level R function does this, i'll call LAPACK from a C shlib and then use .Call. the only LAPACK function i see to do this in R_ext/Lapack.h is dsyevx. however, i know that in LAPACK dsyevr can also return a partial eigendecomposition. why is dsyevr not

Professor Ripley commented on LAPACK error codes: https://stat.ethz.ch/pipermail/r-help/2007-March/127702.html and says "Internal LAPACK errors are usually problems with arithmetic accuracy, and as such are compiler- and CPU-specific." Is there a listing for the error codes from Lapack routine 'dsyevr'? Especially I am interested about the meaning and handling of error codes 1

On 02 Feb 2015, at 04:08 , eigen <liguowei1991 at gmail.com> wrote: > Thank you for your reply. Do you have any idea of how to get rid of the > errors? I tried Null function to calculate eigenvectors and nearPD to get > approximate positive definite matrix first but they also had errors. > How could we? All we know is that you are having trouble running some unspecified code

You can start diagnosing the problem by capturing the matrix that caused eigen() to stop. You can do this in a variety of ways; here is one trace(eigen, quote(lastEigenX <<- x)) After setting the trace, make your offending function call and after the error the global variable 'lastEigenX' will contain the bad matrix. Take the trace off of eigen untrace(eigen) If all goes

DeaR list, I happily use eigen() to compute the eigenvalues and eigenvectors of a fairly large matrix (200x200, say), but it seems over-killed as its rank is limited to typically 2 or 3. I sort of remember being taught that numerical techniques can find iteratively decreasing eigenvalues and corresponding orthogonal eigenvectors, which would provide a nice alternative (once I have the

I noticed that there is some redundant text in eigen.Rd (both the patched and the devel version). "whereas" appears to be a leftover of previous versions. \source{ By default \code{eigen} uses the LAPACK routines \code{DSYEVR}, \code{DGEEV}, \code{ZHEEV} and \code{ZGEEV} whereas LAPACK is from \url{http://www.netlib.org/lapack} and its guide is listed in the references. }

Dear all R users, Can anyone tell me to calculate Eigen value of any real symmetric matrix which algorithm R uses? Is it Jacobi method ? If not is it possible to get explicit algorithm for calculating it? Thanks and regards, Arun [[alternative HTML version deleted]]

Hi all, I've got a basic question regarding package documentation and rd.sty. I wrote my first own package, and now I would like to place the documentation into the appendix of another LaTex document. Seemingly I cannot simply \usepackage{Rd}, as this will modify the page-settings of my document. Is there a minimum style file which will just define the environments and commands needed for

Hi, http://llvm.org/doxygen/classllvm_1_1MemoryBuffer.html shows "the file, and that this character will read as '\0'. " as a "verbatim text" box. This looks ugly and is probably a mistake. The attached patch removes this extra @verbatim ... @endverbatim from comments. -------------- next part -------------- A non-text attachment was scrubbed... Name:

Hello everyone. I am doing a logistic gam (package mgcv) on a pretty large dataframe (130.000 cases with 100 variables). Because of that, the gam is fitted on a random subset of 10000. Now when I want to predict the values for the rest of the data, I get the following error: > gam.basis_alleakti.1.pr=predict(gam.basis_alleakti.1, +

I'm using R 1.9.1 on suse server v9 enterprise with the gee package version 4.13-10. I have code that runs in an automated script. It uses the gee function from the gee package. The script is run quite often without error. I have a problem where the script locks up R when calling this function (it starts execution and never finishes). I was able to track down the offending data and determine

Hi, It is my understanding that the eigenvectors of a circulant matrix are given as follows: 1,omega,omega^2,....,omega^{p-1} where the matrix has dimension given by p x p and omega is one of p complex roots of unity. (See Bellman for an excellent discussion on this). The matrix created by the attached row and obtained using the following commands indicates no imaginary parts for the

--Apple-Mail-1-507788993 Content-Transfer-Encoding: 7bit Content-Type: text/plain; charset=US-ASCII; format=flowed Here is the same thing as before, now done a bit more systematically. The rather bad performance of R-patched on eigen is a mystery (to me), the gain in La.eigen when using ATLAS is probably not Altivec, but using threaded level 3 BLAS on a dual processor machine.

Hi all, when testing the new improvements in the new 1.7.0-version I stumbled over the following: >eigen(matrix(c(0,.3,2,.9),2,2)) Error in eigen(matrix(c(0,.3,2,.9),2,2)) : LAPACK routine DGEEV gave error code -13 >eigen(matrix(c(0,.3,2,.9),2,2),EISPACK=TRUE) $values [1] 1.3458236 -0.4458236 $vectors [,1] [,2] [1,] -1.1436890 -0.9760443 [2,] -0.7696018