Optimal Experiment Design, Fisher Information
The Fisher information is a measure for the amount of information about parameters provided by experimental data (Fisher 1912). It is a well-established characteristic of an experimental design used to assess and optimize the design for maximizing the expected accuracy of parameter estimates (Kreutz 2009). The Fisher information is calculated for each pair of parameters and is in this notation denoted as the Fisher information matrix.
In the following, the Fisher information is introduced in some commonly used notations. Some calculations require additional assumptions in a strict mathematical derivation. Because the assumptions are usually fulfilled for models applied in systems biology, these restrictions are not stated explicitly.
- Atkinson AC (1982) Developments in the design of experiments. Int Stat Rev 50(2):161–177Google Scholar
- Efron B, Hinkley DV (1978) Assessing the accuracy of the maximum likelihood estimator: observed versus expected fisher information. Biometrika 65(3):457–482Google Scholar
- Fisher RA (1912) On an absolute criterion in systems of nonlinear equations. Messenger Math 41:155–160Google Scholar
- Honerkamp J (2002) Statistical physics. An advanced approach with applications. Springer, HeidelbergGoogle Scholar
- Kiefer J (1959) Optimum experimental designs. JR Stat Soc Ser B 21:272–319Google Scholar