arXiv:cond-mat/0211437AbstractReferencesReviewsResources
Generalized entropy optimized by an arbitrary distribution
Published 2002-11-20Version 1
We construct the generalized entropy optimized by a given arbitrary statistical distribution with a finite linear expectation value of a random quantity of interest. This offers, via the maximum entropy principle, a unified basis for a great variety of distributions observed in nature, which can hardly be described by the conventional methods. As a simple example, we explicitly derive the entropy associated with the stretched exponential distribution. To include the distributions with the divergent moments (e.g., the Levy stable distributions), it is necessary to modify the definition of the expectation value.
Comments: 10 pages, no figures
Categories: cond-mat.stat-mech
Keywords: generalized entropy, arbitrary distribution, finite linear expectation value, maximum entropy principle, levy stable distributions
Tags: journal article
Related articles: Most relevant | Search more
arXiv:1808.01172 [cond-mat.stat-mech] (Published 2018-08-03)
Maximum Entropy Principle in statistical inference: case for non-Shannonian entropies
arXiv:2312.13762 [cond-mat.stat-mech] (Published 2023-12-21)
Microscopic Legendre Transform, Canonical Distribution and Jaynes' Maximum Entropy Principle
Jaynes' Maximum Entropy Principle, Riemannian Metrics and Generalised Least Action Bound