Abstract
Maximum entropy is presented as a universal method of finding a “best” positive distribution constrained by incomplete data. The generalised entropy ∑(f - m - f log(f/m))) is the only form which selects acceptable distributions f in particular cases. It holds even if f is not normalised, so that maximum entropy applies directly to physical distributions other than probabilities. Furthermore, maximum entropy should also be used to select “best” parameters if the underlying model m has such freedom.
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© 1988 Kluwer Academic Publishers
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Skilling, J. (1988). The Axioms of Maximum Entropy. In: Erickson, G.J., Smith, C.R. (eds) Maximum-Entropy and Bayesian Methods in Science and Engineering. Fundamental Theories of Physics, vol 31-32. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3049-0_8
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DOI: https://doi.org/10.1007/978-94-009-3049-0_8
Publisher Name: Springer, Dordrecht
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