similar to: fast partial spectral decompositions.

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

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 can fix it? Theoretically the eigenvalues should be nonnegative, if it helps.

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

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

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

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

Hi: I create a hermitian matrix and then perform its singular value decomposition. But when I put it back, I don't get the original hermitian matrix. I am having the same problem with spectral value decomposition as well. I am using R 1.7.0 on Windows. Here is my code: X <- matrix(rnorm(16)+1i*rnorm(16),4) X <- X + t(X) X[upper.tri(X)] <- Conj(X[upper.tri(X)]) Y <-

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

Full_Name: Laurent Gautier Version: 1.3.0-patched OS: IRIX 6.5 Submission from: (NULL) (130.225.67.199) Hello, The function La.eigen, called by cmdscale in the package mva behaves an unexplicable way (for me). The following lines show what happened. I tried the very same on linux, and it worked fine. >a <- matrix(c(1,2,3,2),3,3) >a [,1] [,2] [,3] [1,] 1 2 3 [2,]

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

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

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]]

Using the 64-bit Solaris compilers make check dumps core in La_rs at 73 F77_CALL(dsyev)(jobv, uplo, &n, rx, &n, rvalues, work, &lwork, &info); I can't reproduce it easily, but example(eigen) occasionally stops with Error: abs(sm - V %*% diag(lam) %*% t(V)) < 60 * Meps is not TRUE which might be connected. The tiny rounding errors in example(eigen) aren't

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

I'm looking for a routine in R to do Blinder-Oaxaca (and related) decompositions. A very nice one has been written (by Jann) for Stata (and I'm evaluating whether I can switch over to R). I'm having a hard time finding any reference in R documentation to this pretty ubiquitous tool (in labour economics) for decomposing differences between two groups into differences in means and

Hi list, Does anyone know if there is a library in R that does MTM-SVD method for spectral analysis? Thanks ----- Yasir H. Kaheil Columbia University -- View this message in context: http://www.nabble.com/Spectral-analysis-with-mtm-svd-Multi-Taper-Method-Combined-with-Singular-Value-Decomposition-tp21671934p21671934.html Sent from the R help mailing list archive at Nabble.com.

Hello all, I have the square symetric matrix A: 2 1 1 1 2 1 1 1 2 My first question is what is the easiest way to enter this matriz in R? Second, matrix A has an eigenvalue with multiplicity 2, in this case, how could I find the two related ortogonal eigenvectors given below by R, without the help of R, I mean, I want to know how R calculate this eigenvectors related to the same eigenvalue.

All of my resources for numerical analysis show that the spectral decomposition is A = CBC' Where C are the eigenvectors and B is a diagonal matrix of eigen values. Now, using the eigen function in R # Original matrix aa <- matrix(c(1,-1,-1,1), ncol=2) ss <- eigen(aa) # This results yields back the original matrix according to the formula above ss$vectors %*% diag(ss$values) %*%

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. }