For other uses of "Maximum entropy", see Maximum entropy (disambiguation).
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Posterior = Likelihood × Prior ÷ Evidence
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The principle of maximum entropy states that the probability distribution which best represents the current state of knowledge about a system is the one with largest entropy, in the context of precisely stated prior data (such as a proposition that expresses testable information).
Another way of stating this: Take precisely stated prior data or testable information about a probability distribution function. Consider the set of all trial probability distributions that would encode the prior data. According to this principle, the distribution with maximal information entropy is the best choice.
and 23 Related for: Principle of maximum entropy information
The principleofmaximumentropy states that the probability distribution which best represents the current state of knowledge about a system is the one...
the principleofmaximumentropy, if nothing is known about a distribution except that it belongs to a certain class (usually defined in terms of specified...
in Shannon information theory, Bayesian probability, and the principleofmaximumentropy. These techniques are relevant to any situation requiring prediction...
state of disorder, randomness, or uncertainty. Maximumentropy thermodynamics Maximumentropy spectral estimation PrincipleofmaximumentropyMaximum entropy...
The principleofmaximum caliber (MaxCal) or maximum path entropyprinciple, suggested by E. T. Jaynes, can be considered as a generalization of the principle...
(negative entropy) Phase space Principleofmaximumentropy Residual entropy Thermodynamic potential The overdots represent derivatives of the quantities...
construction of logical principles for assigning prior probability distributions; see the principleofmaximumentropy, the principleofmaximum caliber,...
E.T. Jaynes, 1988, "The evolution of Carnot's principle," in G. J. Erickson and C. R. Smith (eds.)Maximum-Entropy and Bayesian Methods in Science and...
namely the principleof transformation groups as in the Jeffreys prior, and the principleofmaximumentropy. More generally, one speaks of uninformative...
Jaynes, based mainly on the consequences of symmetries and on the principleofmaximumentropy. As an example of an a priori prior, due to Jaynes (2003)...
system. To restate: The maximumentropyprinciple: For a closed system with fixed internal energy (i.e. an isolated system), the entropy is maximized at equilibrium...
known; one can then use the principleofmaximumentropy to determine a single distribution, the one with the greatest entropy given the constraints. (Analogously...
accordingly to the principleofmaximumentropy, which says that the probability distribution which best represents the current state of knowledge is the...
the principleofmaximumentropy or the principleof least action, it is true on mathematical grounds. To attempt to falsify the free energy principle is...
principle Likelihood-ratio test Likelihoodist statistics Maximum likelihood Principleofmaximumentropy Pseudolikelihood Score (statistics) See Exponential...
behavior are still debatable. One of the guiding principles for these systems is the principleofmaximumentropy production. It states that nonequilibrium...
redirects to PrincipleofmaximumentropyMaximumentropy probability distribution Maximumentropy spectral estimation Maximum likelihood Maximum likelihood...
Bayesian statistics, a maximum a posteriori probability (MAP) estimate is an estimate of an unknown quantity, that equals the mode of the posterior distribution...
relative "objectivity" of the priors proposed under these methods): Maximumentropy Transformation group analysis Reference analysis Each of these methods contributes...
method depends on the principle that one can sample from a distribution by sampling uniformly from the region under the plot of its density function....
to the holographic principle. Bekenstein's topical overview "A Tale of Two Entropies" describes potentially profound implications of Wheeler's trend, in...
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