similar to: eigen segfaults on 0-diml matrices (PR#882)

R-3.0.1 rev 62743, binary downloaded from CRAN just now; macosx 10.8.3 Hello, eigen(symmetric=TRUE) behaves strangely when given complex matrices. The following two lines define 'A', a 100x100 (real) symmetric matrix which theoretical considerations [Bochner's theorem] show to be positive definite: jj <- matrix(0,100,100) A <- exp(-0.1*(row(jj)-col(jj))^2) A's being

At 01:37 PM 5/10/00 +0200, ralle wrote: >Hi, >I have a problem understanding what is going on with eigen() for >nonsymmetric matrices. >Example: >h<-rnorm(6) >> dim(h)<-c(2,3) >> c<-rnorm(6) "c" is not a great choice of identifier! >> dim(c)<-c(3,2) >> Pi<-h %*% c >> eigen(Pi)$values >[1] 1.56216542 0.07147773 These could

Hello List, i need help for eigen and svd functions. I have a non-symmetric square matrix. These matrix is not positive (some eigenvalues are negative). I want to diagonalise these matrix. So, I use svd and eigen and i compare the results. eigen give me the "good" eigenvalues (positive and negative). I compare with another software and the results are the same. BUT, when i use svd,

Full_Name: Sharon Kuhlmann Version: 0.99 OS: solaris2.6 Submission from: (NULL) (129.16.167.231) When I use the function > eigen(x), it gives me a "Process R bus error", and the program quits. I'm running the following R version: platform sparc-sun-solaris2.6 arch sparc os solaris2.6 system sparc, solaris2.6 status Patched

Full_Name: Sundar Dorai-Raj Version: 1.8.1 OS: Windows 2000 Professional Submission from: (NULL) (12.64.199.173) I discovered this problem when trying to use princomp in package:mva when a column in my matrix was all zeros and I set cor = TRUE (thus division by 0). Doing so hangs R, never to return. I have to shut down Rterm in the Task Manager and lose all work from the current image. I tracked

hi all i have a question that about the eigen analysis found in R and in eviews. i used the same data set in the two packages and found different answers. which is incorrect? the data is: aa ( a correlation matrix) 1 0.9801 0.9801 0.9801 0.9801 0.9801 1 0.9801 0.9801 0.9801 0.9801 0.9801 1 0.9801 0.9801 0.9801 0.9801 0.9801 1 0.9801 0.9801 0.9801 0.9801 0.9801 1 now > svd(aa) $d [1] 4.9204

Dear R-helpers, could anybody explain me briefly what is the difference between eigenvectors returned by 'eigen' and 'svd' functions and how they are related? Thanks in advance Ondrej Mikula

Hi all, As a molecular biologist by training, I'm fairly new to R (and statistics!), and was hoping for some advice. First of all, I'd like to apologise if my question is more methodological rather than relating to a specific R function. I've done my best to search both in the forum and elsewhere but can't seem to find an answer which works in practice. I am carrying out

Hi all, Recently our statistics students noticed that their Gibbs samplers were crashing due to some NaNs in some parameters. The NaNs came from mvrnorm (Ripley & Venables' MASS package multivariate normal sampling function) and with some more investigation it turned out that they were generated by function eigen, the eigenvalue computing function. The problem did not seem to happen

Hi, with small matrices eigen works as expected: > eigen(cbind(c(1,4),c(4,7)), only.values = TRUE) $values [1] 9 -1 $vectors NULL > eigen(cbind(c(1,4),c(4,7))) $values [1] 9 -1 $vectors [,1] [,2] [1,] 0.4472136 -0.8944272 [2,] 0.8944272 0.4472136 > eigen(cbind(c(1,-1),c(1,-1))) $values [1] -3.25177e-17+1.570092e-16i -3.25177e-17-1.570092e-16i $vectors

Full_Name: Patrick Burns Version: 1.8.1 OS: Windows 2000 Submission from: (NULL) (81.129.3.151) The command: eigen(matrix(Inf, 2, 2)) causes version 1.8.1 to hang in both Windows 2000 and SuSe 8.2. (Hang defined as apparently needing to kill the process in order to get a prompt back.) This is similar to bug #4366 where the same command used NaN instead of Inf.

Hi, I get the wrong eigen values on an AIX machine with R-devel of 5/3/00. Here are the results: R> m <- matrix (c(6.8, 2.4, 2.4, 8.2), nrow=2) R> m [,1] [,2] [1,] 6.8 2.4 [2,] 2.4 8.2 R> eigen(m) $values [1] 19.281403 6.337993 $vectors [,1] [,2] [1,] 0.1918866 0.9967987 [2,] 0.9967987 -0.1918866 And for comparison, here is what I get on a Sun (with

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

I would like to deprecate La.eigen. It is used in a few packages (ade4, fpc, gss, mvtnorm and smoothSurv on CRAN), but only in usages where replacing `La.eigen' by `eigen' would call exactly the same code. The reason for wanting to deprecate it is that little-used interfaces tend to get overlooked, e.g. PR#5406, a report on eigen, needed to be applied to La.eigen as well. We have also

> x11() > dev.off() null device 1 > x11() > plot.new() Warning messages: 1: X11 protocol error: BadAccess (attempt to access private resource denied) 2: X11 protocol error: BadAccess (attempt to access private resource denied) This only happens if all x11 devices are shut down, so the X11 connection is restarted. We had problems with this when the event handlers were

Dear R-users, Recently, I have come across a weird problem. I run a large number of iterations and at one of the step within each iteration, I calculate the eigen values of a updated covariance matrix. From all my intermediate output, the code freezes after printing out the covariance matrix but before printing out the eigen values. So, obviously it stops at the only step, the eigen() function

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]

Sorry to bother everyone, but I've looked in all of the help files and manuals I have and I can't find the answer to this question. I'm doing principle component analysis by calculating the eigen vectors of a correlation matrix that I have that is composed of 21 parameters. I have the eigen vectors and their values that R produced for me but I'm not sure how to tell which

I'm using R version 2.0.1 on a Windows 2000 operating system. Here is some actual code I executed: > test [,1] [,2] [1,] 1000 500 [2,] 500 250 > eigen(test, symmetric=T)$values [1] 1.250000e+03 -3.153033e-15 > eigen(test, symmetric=T)$values[2] >= 0 [1] FALSE > eigen(test, symmetric=T, only.values=T)$values [1] 1250 0 > eigen(test, symmetric=T,

I'm using R 1.7.1 under linux redhat it seems that the eigen values produced by eigen() do not follow a consistant order; I mean either ascending or discending e.g for one system: eigenV<-eigen(V) > print(eigenV$values) [1] -7.706828e+13 -4.702980e+13 -3.267579e+13 -1.701297e+13 -8.041677e+12 [6] -5.707311e+12 -5.053941e+12 -4.774652e+12 -4.280423e+12 -3.798905e+12