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- MARY E. BROADBENT, MARTIN BROWN, KEVIN PENNER, Ilse Ipsen, Rizwana Rehman
- 2010

Subset selection is a method for selecting a subset of columns from a real matrix, so that the subset represents the entire matrix well and is far from being rank deficient. We begin by extending a deterministic subset selection algorithm to matrices that have more columns than rows. Then we investigate a two-stage subset selection algorithm that utilizes a… (More)

This paper concerns the computation of the coefficients c k of the characteristic polynomial of a real or complex matrix A. We analyze the forward error in the coefficients c k when they are computed from the eigenvalues of A, as is done by MATLAB's poly function. In particular, we derive absolute and relative perturbation bounds for elementary symmetric… (More)

We derive absolute perturbation bounds for the coefficients of the characteristic polynomial of a n × n complex matrix. The bounds consist of elementary symmetric functions of singular values, and suggest that coefficients of normal matrices are better conditioned with regard to absolute perturbations than those of general matrices. When the matrix is… (More)

Identification of epilepsy patients from administrative data in large managed healthcare organizations is a challenging task. The objectives of this report are to describe the implementation of an established algorithm and different modifications for the estimation of epilepsy prevalence in the Veterans Health Administration (VHA). For the prevalence… (More)

The purpose of this report is to describe the demographics of Veterans diagnosed with seizures and taking antiepileptic drugs (AEDs) within the Veterans Health Administration (VHA) during fiscal year (FY) 2011 (October 1, 2010, to September 30, 2011), particularly with regard to comorbid traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD).… (More)

- RIZWANA REHMAN, Donald La Budde
- 2010

La Budde's method computes the characteristic polynomial of a real matrix A in two stages: first it applies orthogonal similarity transformations to reduce A to upper Hessenberg form H, and second it computes the characteristic polynomial of H from characteristic polynomials of leading principal submatrices of H. If A is symmetric, then H is symmetric… (More)

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