Sylvester's determinant theorem

In matrix theory, Sylvester's determinant theorem is a theorem useful for evaluating certain types of determinants. It is named after James Joseph Sylvester.

The theorem states that if A, B are matrices of size p × n and n × p respectively, then

\det(I_p %2B AB) = \det(I_n %2B BA),\

where Ia is the identity matrix of order a.[1]

It is closely related to the Matrix determinant lemma and its generalization.

This theorem is useful in developing a Bayes estimator for multivariate Gaussian distributions.

Sylvester (1857) stated this theorem without proof.

External links

References

  1. ^ David A. Harville. Matrix Algebra From a Statistician's Perspective. Springer, 2008, Pages 416