Schur Complement - Applications To Probability Theory and Statistics

Applications To Probability Theory and Statistics

Suppose the random column vectors X, Y live in Rn and Rm respectively, and the vector (X, Y) in Rn+m has a multivariate normal distribution whose variance is the symmetric positive-definite matrix

where A is n-by-n and C is m-by-m.

Then the conditional variance of X given Y is the Schur complement of C in V:

If we take the matrix V above to be, not a variance of a random vector, but a sample variance, then it may have a Wishart distribution. In that case, the Schur complement of C in V also has a Wishart distribution.

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