A very important property of the ML estimators is that asymptotically (i.e., for a signal-to-noise ratio tending to infinity) they are (i) unbiased, and (ii) they have a Gaussian distribution with covariance matrix equal to the inverse of the Fisher information matrix.
In the case of Gaussian noise the components of the Fisher matrix are given by
where the scalar product
http://www.livingreviews.org/lrr-2012-4 |
Living Rev. Relativity 15, (2012), 4
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