Fisherinformationen
Fisherinformationen, also known as Fisher information, is a concept in statistics and information theory that quantifies the amount of information that an observable random variable carries about an unknown parameter upon which the probability of the variable depends. It is named after the statistician Ronald A. Fisher.
Fisher information is a measure of the amount of information that an observable random variable X carries
Fisher information is widely used in statistical inference, particularly in the context of maximum likelihood estimation.
In Bayesian statistics, Fisher information is used in the context of the Fisher information matrix to construct
Fisher information is also used in the context of information theory, where it is used to quantify
In summary, Fisher information is a fundamental concept in statistics and information theory that quantifies the