On the Studentisation of Random Vectors

We give general matrix Studentisation results for random vectors converging in distribution to a spherically symmetric random vector, which have wide applicability to the asymptotic properties of estimators obtained from estimating equations, for example. Appropriate matrix “square roots,” required for normalisation of the random vectors, are shown to be the Cholesky square root and the symmetric positive definite square root.