@Bibtex-file{Math/habook.bib,
  title =        "References for Least Squares Methods",
  author =       "{\AA}ke Bj{\"o}rck",
  email =        "akbjo@math.liu.se",
  abstract =     "This is the BibTeX reference base which I have used
                 for the book Numerical Methods for Least Squares, SIAM,
                 1996 (reference {bjor:96}).",
  keywords =     "approximate methods (appr), augmented system (augms),
                 backward perturbation (pert), banded least squares
                 (band), blas (blas), block angular system (basys),
                 block methods (block), Chebyshev approximation (cheb),
                 Cholesky (chol), condition (cond), conjugate gradients
                 (cg), constrained least squares (constr), control
                 theory (contr), covariance matrix (covar), CS
                 decomposition (csd), downdating (downd), eigenvalue
                 problem (eigv) equilibration (scale), error estimate
                 (err), fast Fourier transform (fft), fill-in (fill),
                 generalized eigenvalue problems (geig), generalized
                 inverse (ginv), generalized linear model (glsq),
                 generalized QR decomposition (gqrd), geodesy (geod),
                 geometric elements, fitting (geom), generalized
                 singular value decomposition (gsvd), Givens rotation
                 (rot), graph theory (graph), Gram-Schmidt (grsch),
                 history of least squares (hist), Householder (house),
                 hyperbolic rotation (hyp), ill-posed (illp), interior
                 point methods (intpoint), interval analysis (err),
                 iterative method (iter), iterative refinement (ir),
                 Kronecker product (kron), Lanczos (lanczos), linear
                 algebra general (la), LU decomposition (lud), matrix
                 approximation (max), nested dissection (nestdis),
                 nonlinear least squares (nlsq), normal equations (ne),
                 numerical linear algebra (nla) optimization (opt),
                 ordering for sparsity (perm), orthogonalization (orth),
                 orthogonal regression (orthreg), precision (err),
                 preconditioning (precond), pseudo-inverse (ginv),
                 parallel computation (prll), perturbation theory
                 (pert), polynomial approximation (poly), projection
                 (orth), QR decomposition (qrd), quadratic programming
                 (quadpr), random matrix (rand), rank degenerate
                 problems (rank), rank revealing QR factorization
                 (rrqrd), recursive least squares (rls), regularization
                 (regul), regression (regr), robust estimation (rob),
                 scaling (scale), signal processing (sigp), singular
                 value decomposition (svd), software (soft), sparse
                 (sparse), spline approximation (spline), statistics
                 (stat), survey paper/book (survey), systolic (syst),
                 test matrix (test), Toeplitz (toep), total least
                 squares (tls), underdetermined systems (uds), updating,
                 downdating (upd, downd), Vandermonde systems (vand),
                 variable projection (varpro), vector processing (prll),
                 weighted least squares (wlsq)",
}