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Erschienen in:
2001 | OriginalPaper | Buchkapitel
Maximum entropy estimation
verfasst von : Dr.-Ing. Christoph Arndt
Erschienen in: Information Measures
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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The maximum entropy estimation is a method that enables us to estimate the distribution density function of one or more random variables, if our previous knowledge is restricted by a limited number of samples or by other limitations. The basic idea of this method can be described with the Laplacian ‘principle of insufficient reasoning’. This principle states that we may only use a priori knowledge, which we get from measurements or other known restrictions. All other information, which is, for instance, implicated by an estimation algorithm, leads to a limitation of the results obtained.