similar to: eigen segfault with GCC 3 on Solaris (PR#1272)

I have now tested R 1.3.1 compiled with GCC 3.0.2 on Solaris and the example I previously posted (repeated below) still gives a segmentation fault, as it does with GCC 3.0.1 but not with 2.95.2. The eigen calculation sometimes needs to be repeated several times before the segmentation fault occurs. La.eigen does not cause a problem. (The problem occurred with R-devel too, but I have not tested

Hi everyone, It's a very minor point, but could we ensure that eigen and La.eigen return a *matrix* for the "vectors" component of the list by including a "drop = FALSE", as specified in the help file, ie put list(values = z$values[ord], vectors = if (!only.values) z$vectors[, ord, drop = FALSE]) Thanks, Jonathan. --please do not edit the information

Dear all, It is not a R related problem rather than statistical/mathematical. However I am posting this query hoping that anyone can help me on this matter. My problem is to get the Geometrical Interpretation of Eigen value and Eigen vector of any square matrix. Can anyone give me a light on it? Thanks and regards, Arun [[alternative HTML version deleted]]

Dear R-users, I'm estimating a two- dimensional state-space model using the FKF package. The resulting log likelihood function is maximized using auglag from the Alabama package. The procedure works well for a subset of my data, but if I try to use the entire data set I get the following error message. Error in eigen(a$hessian) : infinite or missing values in 'x' What's even

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

Hi. I was comparing the components from princomp's loadings and the eigen given the same input. I found that the sign of componenets (+/-) are opposite between the two components (from princmop and eigen) but the magnitudes are identical. Why? Thanks! [[alternative HTML version deleted]]

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, Can anyone please point to how to decompose BCCB (Block-Circulant-Circulant-Block) matrices? I am interested in the derivations: I do know that this can be numerically done using 2-dimensional FFTs. Many thanks and best wishes!

Hi all. I got a question about eigenvector. I've tried input a symmetric matrix to both R (using eigen function) and minitab, but the result is really different. Can anyone tell me what's wrong with that? Thanks. [[alternative HTML version deleted]]

Dear all, I am running an Ecological Niche Factor Analysis in R but I am stuck with a problem. As soon as I ask the software to compute the ENFA, I get the following error message: Error in eigen(Se) : infinite or missing values in 'x' Does anyone know what could be wrong. I do not have missing values in my dataset. Please follow the codes I used for my analysis so far: library

Dear, My problems are; 1. Simulate a P-variate multivariate data set (N by P) 2. Draw samples of size n from N (with or without replacement) 3. Obtain eigen values of the variance-covariance matrix of each sample drawn in (2) above. 4. print out the matrix of eigen values as well as the identity of sample generating them. Thanks ---------------------------------

Hi everyone, I am using eigen() to extract the 2 major eigenpairs from a large real square symmetric matrix. The procedure is already rather efficient, but becomes somehow slow for real time needs with moderately large matrices (few thousand lines). The R implementation statically extracts all eigenvalues (and optionally associated eigenvectors). I heard about optimizations of the eigen

Sorry if this bug is fixed in the meantime, but what is this?? > m [,1] [,2] [,3] [1,] 1 2 1 [2,] 0 2 0 [3,] 1 2 1 > eigen(m) $values [1] 2 2 0 $vectors [,1] [,2] [,3] [1,] -4.194304e+06 0.7071068 -0.7071068 [2,] -4.656613e-10 0.0000000 0.0000000 [3,] -4.194304e+06 0.7071068 0.7071068 > eigen(m, symmetric=T) $values [1]

Dear Sir, I am an R user. I am in problem to find eigen vectors in R. For the following matrix eigen vectors are not right. I can not understand why?? For the 1st eigen value and 2nd eigen value are same, but the eigen vectors are not same. *HOW CAN I RESOLVE THE PROBLEM??* *>c=matrix(c(1,0,0,1,2,0,-3,5,2),nrow=3,byrow=T)> eigen(c)$values[1] 2 2 1$vectors [,1] [,2]

eigen() seems to work for symmetric matrices only. This is out of sync with the help file. > trpr.37 0 1 2 3 4 0 1.00000000 0.0000000 0.0000000 0.0000000 0.0000000 1 0.44444444 0.5555556 0.0000000 0.0000000 0.0000000 2 0.02439024 0.2439024 0.7317073 0.0000000 0.0000000 3 0.00000000 0.0000000 0.2307692 0.7692308 0.0000000 4 0.00000000 0.0000000

I don't have time to track this down right now -- if no-one does it in the next few days before I finish the current piece of work I will try to find it myself. R gets the wrong answer for the eigensystem of a (particular) 4x4 matrix (SunOS 4.1.4). Running these commands: x _ matrix( c(-10, 0 ,0 ,0, 0 ,-0.3 ,0 ,0, 1 , 0.03 ,-0.594,0.0020,

eigen(matrix(rep(1,9),ncol=3),only.values=T) works repeatedly but eventually (after 3 or 4 goes) gave a core dump of 11mb (I think only the first answer was right). if I type gc() immediately after the first call, I get a core dump right away (this might possibly be related to my huge core dumps with nlm) eigen(matrix(rep(1,9),ncol=3)) core dumps immediately after the first call Jim

Eigen seems to be giving different results in 0.64 : eigen(matrix( c(0.00000000, 0.0000000, 0.00000000, 1.000000000, 0.01262442, -0.1141633, 0.04989433, 0.006112607, 0.04781087, 0.4177869, -0.15569656, 0.074242237, 0.20167331, 0.2531109, -0.04973573, 0.034046467) ,4,4))$values R: [1] 0.35519256 -0.29294606 -0.26637369 -0.03168619 S: [1] 0.4689288205 -0.4246063863 -0.2810596564

>From one of my students' simulations: m <- matrix(1, 0, 0) # 1 to force numeric not logical eigen(m) and segfault in TRED2 in src/appl/eigen.f Easy to fix, but I wonder what else might have been overlooked? (svd is protected). --please do not edit the information below-- Version: platform = sparc-sun-solaris2.7 arch = sparc os = solaris2.7 system = sparc, solaris2.7 status =

Consider this matrix: > sg X1 X2 X3 X4 X5 1 3.240 2.592 2.592 2.592 2.592 2 2.592 3.240 2.592 2.592 2.592 3 2.592 2.592 3.240 2.592 2.592 4 2.592 2.592 2.592 3.240 2.592 5 2.592 2.592 2.592 2.592 3.240 If I compute the eigenvalues of the 'sg' matrix using R Version 1.5.0 (2002-04-29) under Linux (or using Version 1.4.0 (2001-12-19) under Solaris), I obtain: >