Support for the Woodbury matrix identity for Julia
21 Stars
Updated Last
1 Year Ago
Started In
February 2015


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This package provides support for the Woodbury matrix identity for the Julia programming language. This is a generalization of the Sherman-Morrison formula. Note that the Woodbury matrix identity is notorious for floating-point roundoff errors, so be prepared for a certain amount of inaccuracy in the result.


Woodbury Matrices

using WoodburyMatrices
W = Woodbury(A, U, C, V)

creates a Woodbury matrix from the A, U, C, and V matrices representing A + U*C*V. These matrices can be dense or sparse (or generally any type of AbstractMatrix), with the caveat that inv(inv(C) + V*(A\U)) will be calculated explicitly and hence needs to be representable with the available resources. (In many applications, this is a fairly small matrix.)

Here are some of the things you can do with a Woodbury matrix:

  • Matrix(W) converts to its dense representation.
  • W\b solves the equation W*x = b for x.
  • W*x computes the product.
  • det(W) computes the determinant of W.
  • α*W and W1 + W2.

It's worth emphasizing that A can be supplied as a factorization, which makes W\b and det(W) more efficient.

SymWoodbury Matrices

using WoodburyMatrices
W = SymWoodbury(A, B, D)

creates a SymWoodbury matrix, a symmetric version of a Woodbury matrix representing A + B*D*B'. In addition to the features above, SymWoodbury also supports "squaring" W*W.

Required Packages