Linear algebra

Schur complement

In linear algebra and the theory of matrices, the Schur complement of a block matrix is defined as follows. Suppose p, q are nonnegative integers, and suppose A, B, C, D are respectively p × p, p × q, q × p, and q × q matrices of complex numbers. Let so that M is a (p + q) × (p + q) matrix. If D is invertible, then the Schur complement of the block D of the matrix M is the p × p matrix defined by If A is invertible, the Schur complement of the block A of the matrix M is the q × q matrix defined by In the case that A or D is singular, substituting a generalized inverse for the inverses on M/A and M/D yields the generalized Schur complement. The Schur complement is named after Issai Schur who used it to prove Schur's lemma, although it had been used previously. Emilie Virginia Haynsworth was the first to call it the Schur complement. The Schur complement is a key tool in the fields of numerical analysis, statistics, and matrix analysis. (Wikipedia).

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Related pages

Linear algebra | Block matrix | Generalized inverse | Identity matrix | Multivariate normal distribution | Laplacian matrix | Condition number | Gaussian elimination | Schur's lemma | Woodbury matrix identity | Total least squares | Emilie Virginia Haynsworth | Quasi-Newton method | Issai Schur | Wishart distribution | Gaussian process | Matrix (mathematics) | Rank (linear algebra) | Haynsworth inertia additivity formula | Conditional variance