search for: pseudovariance

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 contain code for Gill-Murray and Schnabel-Eskow algorithms for standard, dense, base-R matrices. But my Matrix is large (k=30000), and sparse (block-arrow structure, stored as a dsCMatrix class from the Matrix...