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The document discusses Fisher information, which measures the amount of information that an observable random variable carries about an unknown parameter. It defines Fisher information for a parametric family of distributions and provides two examples - for an exponential family and a Bernoulli distribution parameterized in two different ways. It then discusses how Fisher information relates to estimation, noting that the Cramér-Rao bound implies that the mean squared error of any unbiased estimator is lowe

Author

dim ifk

Language

EN