Is there a function in r that let's you efficiently invert a positive
definite symmetric Block Toeplitz matrix? My matrices are the covariance
matrices of observations of a multivariate time series and can be
1000*1000 or larger.
I know the package 'ltsa' which seems to use the Trench algorithm to
compute the inverse of a Toeplitz matrix. I am looking for a so to say
"multivariate" version of that. I found the Block Levinson algorithm in
Matlab, but didn't find any version of it in R.
My problem is part of a bigger problem, which is first computing the
log-likelihood of the observations Y_T=(Y_1, ..., Y_T) of an
n-dimensional time-series (Y_t) and second, finding an approximation of
the MLE by using e.g. the BFGS algorithm.
As this algorithm does not function properly (no convergence), I thought
that maybe the inversion of the big covariance matrix EY_T Y_T' may be a
source a trouble.
Thanks for inputs in advance!
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
