search for: tridiagon

Dear R Users, I am trying to solve a tridiagonal matrix in R. I am wondering if there is an inbuilt R function or package to solve that. I tried looking on google but couldn't find something that would help directly. Any help is highly appreciated. Thanks. Janesh [[alternative HTML version deleted]]

I need to find solutions to a tridiagonal system. By this I mean a set of linear equations Ax = d where A is a square matrix containing elements A[i,i-1], A[i,i] and A[i,i+1] for i in 1:nrow, and zero elsewhere. R is probably not the ideal way to do this, but this is part of a larger problem that requires R. In my application it is much...

Good day, I would like to know if there is an efficient and accurate method for computing the power of a tridiagonal matrix in R? The "obvious" method would be eigen-decomposition, but I find that this is not very accurate, probably because the dimensions of the matrix I am considering are large and the eigenvectors are not well approximated. Here is an example of what I am trying to do: set.seed(123...

Hi, I am generating large Kac matrices (also known as Clement matrix). This a tridiagonal matrix. I was wondering whether there is a vectorized solution that avoids the `for' loops to the following code: n <- 1000 Kacmat <- matrix(0, n+1, n+1) for (i in 1:n) Kacmat[i, i+1] <- n - i + 1 for (i in 2:(n+1)) Kacmat[i, i-1] <- i-1 The above code is fast, but I am curi...

...am trying to solve a model that consists of rather stiff ODEs in R. I use the package ODEsolve (lsoda) to solve these ODEs. To speed up the integration, the jacobian is also specified. Basically, the model is a one-dimensional advection-diffusion problem, and thus the jacobian is a tridiagonal matrix. The size of this jacobian is 100*100. In the original package LSODA it is possible to specify that the jacobian is banded, which makes its inversion very efficient. However, this feature seems to have been removed in the R version. Is there a way to overcome this limitatio...

Hi, I have sparse (tridiagonal) matrices, and I use the Matrix package for handling them. For certain computations, I need to either set the first row to zero, or double the last row. I find that neither operation preserves sparsity, eg > m <- Diagonal(5) > m 5 x 5 diagonal matrix of class "ddiMatrix"...

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]]

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