The fisher information matrix for multivariate normal distribution is said at many places to be simplified as:(adsbygoogle = window.adsbygoogle || []).push({});

[tex]\mathcal{I}_{m,n} = \frac{\partial \mu^\mathrm{T}}{\partial \theta_m} \Sigma^{-1} \frac{\partial \mu}{\partial \theta_n}.\ [/tex]

even on

http://en.wikipedia.org/wiki/Fisher_information#Multivariate_normal_distribution

I am trying to come up with the derivation, but no luck so far. Does anyone have any ideas / hints / references, how to do this?

Thank you

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# Fisher matrix for multivariate normal distribution

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