Exact(36)
There, the linear noise approximation is used to calculate Fisher information matrices for stochastic models, primarily to inform experimental design, e.g. by examining the information content of different experimental samples.
B i Sum of information matrices.
We present tables of elemental information matrices for distributions that are often used in statistical work.
The remaining two matrices M are the information matrices M ∗ and M ∗∗.
The corresponding non-equivalent information matrices M ∗=(X ∗ TX ∗ and M ∗∗=(X ∗∗ TX ∗∗ have the maximum determinant.
It is known that some optimality criteria of experimental designs are functionals of the eigenvalues of their information matrices.
Similar(24)
U i Information matrix.
Fisher information matrix.
where J is the Fisher information matrix.
The matrix J is the 2L+P×2L+P Fisher information matrix.
which is sometimes referred to as the observed information matrix.
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