Fisher information

The Fisher information in a univariate model is given by:

$I (θ) = - E_{Y | θ} [\frac{\partial^{2}}{\partial θ^{2}} \log p (y | θ)]$

for data $Y$ . In a multivariate model, the Fisher information matrix, has $i j$ entry:

$I_{i j} (θ) = - E_{Y | θ} [\frac{\partial^{2}}{\partial θ_{i} \partial θ_{j}} \log p (y | θ)]$