similar to: eigen-decomposition of symmetric BCCB matrices

Looks like the files did not go through again. In any case, here is the kinv: please cut and paste and save to a file: -1.16801E-03 -2.24310E-03 -1.16864E-03 -2.24634E-03 -1.17143E-03 -2.25358E-03 -1.17589E-03 -2.26484E-03 -1.18271E-03 -2.27983E-03 -1.19124E-03 -2.29896E-03 -1.20164E-03 -2.32206E-03 -1.21442E-03 -2.34911E-03 -1.22939E-03 -2.38073E-03

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

Hi to everyone, Something quite strange occured to me this weekend as we wanted to switch our network to w2k ads structure with a sambaserver as main fileserver running winbind. The windowsprofiles are supposed to reside on the sambaserver and the client successfully loads the initial profile. The first time the user logs on to his machine, he gets some default .msi-softwarepackages assigned by

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

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

Sorry, forgot to switch the header to the R group.... --- Globe Trotter <itsme_410 at yahoo.com> wrote: > Date: Thu, 2 Mar 2006 19:35:21 -0800 (PST) > From: Globe Trotter <itsme_410 at yahoo.com> > Subject: Re: [R] calling R's library using C > To: Dirk Eddelbuettel <edd at debian.org> > > Hi, Dirk: > > Thanks for all the help. I thought I would

I would presume this is another manifestation of what I reported (reproduced below) on 2003-12-01. cajo.terbraak at wur.nl wrote: >Full_Name: cajo ter Braak >Version: 2.1.1 >OS: Windows >Submission from: (NULL) (137.224.10.105) > > ># I would like to attach the matrix C in the Rdata file; it is 50x50 and comes >from a geostatistical problem (spherical covariogram) >

Say a matrix of size of thousands? I am looking for an eigen-value decomposition algo in R to give good eigenvalues... Is that a hopeful thing? Thank you! [[alternative HTML version deleted]]

>> I had the idea of implementing a lot of the operations in FFTs. ( for >> example, it is possible to do auto-correlation and FIR filtering using >> FFTs.) There are two advantages to this. >> 1. It's almost always faster >> 2. By swapping fft implementations, it could be easy to recompile for >> fixed or floating point versions. > > No. FFT's

Full_Name: cajo ter Braak Version: 2.1.1 OS: Windows Submission from: (NULL) (137.224.10.105) # I would like to attach the matrix C in the Rdata file; it is 50x50 and comes from a geostatistical problem (spherical covariogram) > rm(list=ls(all=TRUE)) > load(file= "test.eigen.Rdata") > ls() [1] "C" "eW" > > sym.check = max(abs(C - t(C))) # should

I have an irregular time series in a Zoo object, and I've been unable to find any way to do an FFT on it. More precisely, I'd like to do an NFFT (non-equispaced / non-uniform time FFT) on the data. The data is timestamped samples from a cheap self-logging accelerometer. The data is weakly regular, with the following characteristics: - short gaps every ~20ms - large gaps every ~200ms

Hi, I am wondering where the library file for R's nmath routines are? Doing a search on libR gave me the following: /usr/lib/libRKC16.so.1.2.0 /usr/lib/libRKC.so.1.2.0 /usr/lib/R/lib/libRlapack.so /usr/lib/R/lib/libR.so /usr/lib/libRKC.so.1 /usr/lib/libRKC16.so.1 None of these have the functions in nmath. Any help? Many thanks and best wishes! GT

I'm trying to get these cleaned up and landed, but I'm running into some trouble with this patch. Using commit a08b29d88e3c (July 21) of Ne10, I'm seeing test failures for 60-point FFTs: nfft=60 inverse=0,snr = -3.312408 ** poor snr: -3.312408 ** nfft=60 inverse=1,snr = -16.079597 ** poor snr: -16.079597 ** All other sizes tested appear to work fine (84 to 140 dB of SNR). This

Hi R users, I have a time series variable that is only available at a monthly level for 1 years that I need to decompose to a weekly time series level - can anyone recommend a R function that I can use to decompose this series? eg. if month1 = 1200 I would to decompose so that the sum of the weeks for month1 equals 1200, etc.. Many thanks in advance for any help. -- View this message in

Here's an easy question: I'd like to convert a symmetric matrix to a vector composed of the upper.tri() part of it plus the diagonal, and convert it back again. What's the best way to achieve this? I'm wondering if there are some built in functions to do this easily. I can encode fine: v <- c(diag(A),A[upper.tri(A)]) but I don't see an easy way to recover A from v

> I had the idea of implementing a lot of the operations in FFTs. ( for > example, it is possible to do auto-correlation and FIR filtering using > FFTs.) There are two advantages to this. > 1. It's almost always faster > 2. By swapping fft implementations, it could be easy to recompile for > fixed or floating point versions. No. FFT's require higher precision than

Hello Timothy, Great to hear from you! Fired up my hardware today and this issue looks like a regression in Ne10 library. The commit in Ne10 [1] that I tested to be working successfully back in May 5b63074db45000f9688460990ee3f5e147d93782 which is the Patch Phil at ARM added to fix the overflow issue in nfft=60 case. After git-bisect, looks like the culprit patch in Ne10 [1] is

> > <with Prof. Farnsworth voice> "Good News, everyone". > > I've just kicked off project "Sphinx". Which is supposed to > sound like "Speex" merged with "INT". ;) Meaning I am working > on an integer encoder and decoder. > Great. I looked into converting speex to fixed point a while ago, but my job has gotten much busier

Dear list users, I have a problem when joining an Active Directory domain. In this project we have one Main Dc in capital city and one read only dc in one remote city. We join to main DC succesfully. However, we can not join to local Replicate (rodc14). We are using this method for winbind / squid ntlm authentication purposes not a full samba server. ?nternet conection is not fast and we have

I am trying to estimate a covariance matrix from the Hessian of a posterior mode. However, this Hessian is indefinite (possibly because of numerical/roundoff issues), and thus, the Cholesky decomposition does not exist. So, I want to use a modified Cholesky algorithm to estimate a Cholesky of a pseudovariance that is reasonably close to the original matrix. I know that there are R packages that