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We have presented a new axiomatic derivation of Shannon Entropy for a discrete probability distribution on the basis of the postulates of additivity and concavity of the entropy function.We have then modified shannon entropy to take account…

Quantum Physics · Physics 2007-05-23 C. G. Chakrabarti , Indranil Chakrabarty

Starting from the model of continuous time random walk, we focus our interest on random walks in which the probability distributions of the waiting times and jumps have fat tails characterized by power laws with exponent between 0 and 1 for…

Probability · Mathematics 2008-01-03 Rudolf Gorenflo , Entsar A. A. Abdel-Rehim

Numerous entropy-type characteristics (functionals) generalizing R\'enyi entropy are widely used in mathematical statistics, physics, information theory, and signal processing for characterizing uncertainty in probability distributions and…

Statistics Theory · Mathematics 2011-03-28 David Källberg , Nikolaj Leonenko , Oleg Seleznjev

Properties of networks are often characterized in terms of features such as node degree distributions, average path lengths, diameters, or clustering coefficients. Here, we study shortest path length distributions. On the one hand, average…

Social and Information Networks · Computer Science 2015-01-20 Christian Bauckhage , Kristian Kersting , Fabian Hadiji

In many applications, the curvature of the space supporting the data makes the statistical modelling challenging. In this paper we discuss the construction and use of probability distributions wrapped around manifolds using exponential…

Methodology · Statistics 2022-10-11 Emmanuel Chevallier , Didong Li , Yulong Lu , David B. Dunson

We consider the problem of approximating the empirical Shannon entropy of a high-frequency data stream under the relaxed strict-turnstile model, when space limitations make exact computation infeasible. An equivalent measure of entropy is…

Computation · Statistics 2013-04-18 Peter Clifford , Ioana Ada Cosma

Statistical system models provide the basis for the examination of various sorts of distributions. Classification distributions are a very common and versatile form of statistics in e.g. real economic, social, and IT systems. The…

Computation · Statistics 2019-12-20 Uwe Petersohn , Thomas Dedek , Sandra Zimmer , Hans Biskupski

Many common probability distributions in statistics like the Gaussian, multinomial, Beta or Gamma distributions can be studied under the unified framework of exponential families. In this paper, we prove that both R\'enyi and Tsallis…

Information Theory · Computer Science 2012-02-01 Frank Nielsen , Richard Nock

After Shannon, entropy becomes a fundamental quantity to describe not only uncertainity or chaos of a system but also information carried by the system. Shannon's important discovery is to give a mathematical expression of the mutual…

Quantum Physics · Physics 2007-05-23 Masanori Ohya

Stochastic thermodynamics extends classical thermodynamics to small systems in contact with one or more heat baths. It can account for the effects of thermal fluctuations and describe systems far from thermodynamic equilibrium. A basic…

Statistical Mechanics · Physics 2018-01-04 Momčilo Gavrilov , Raphaël Chétrite , John Bechhoefer

Particle azimuth distributions are widely studied in heavy-ion collisions. They are often expanded in Fourier series to extract anisotropic flow harmonics simultaneously. It was recently proposed that the different orders of flows could…

Nuclear Theory · Physics 2024-01-23 Yicheng Feng

We represent affine sub-manifolds of exponential family distributions as minimum relative entropy sub-manifolds. With such representation we derive analytical formulas for the inference from partial information on expectations and…

Machine Learning · Statistics 2020-07-14 Marcello Colasante , Attilio Meucci

The renormalization group transformation for extreme value statistics of independent, identically distributed variables, recently introduced to describe finite size effects, is presented here in terms of a partial differential equation…

Statistical Mechanics · Physics 2011-01-06 Eric Bertin , Géza Györgyi

We introduce novel information-entropic variables -- a Point Divergence Gain (${\Omega}^{(l \rightarrow m)}_\alpha$), a Point Divergence Gain Entropy ($I_\alpha$), and a Point Divergence Gain Entropy Density ($P_\alpha$) -- which are…

Data Analysis, Statistics and Probability · Physics 2018-02-07 Renata Rychtáriková , Jan Korbel , Petr Macháček , Dalibor Štys

A $\phi$-exponential distribution is a generalization of an exponential distribution associated to functions $\phi$ in an appropriate class, and the space of $\phi$-exponential distributions has a dually flat structure. We study features of…

Metric Geometry · Mathematics 2011-10-03 Asuka Takatsu

The mathematical properties of a family of generalized beta distribution, including beta-normal, skewed-t, log-F, beta-exponential, beta-Weibull distributions have recently been studied in several publications. This paper applies these…

Methodology · Statistics 2007-10-26 J. H. Sepanski , Lingji Kong

Uncertainty relations are central to quantum physics. While they were originally formulated in terms of variances, they have later been successfully expressed with entropies following the advent of Shannon information theory. Here, we…

Quantum Physics · Physics 2019-05-01 Anaelle Hertz , Nicolas J. Cerf

We study the Shannon entropy of the probability distribution resulting from the ground-state wave function of a one-dimensional quantum model. This entropy is related to the entanglement entropy of a Rokhsar-Kivelson-type wave function…

Strongly Correlated Electrons · Physics 2009-11-25 Jean-Marie Stéphan , Shunsuke Furukawa , Grégoire Misguich , Vincent Pasquier

Aim of this short note is to study Shannon's entropy power along entropic interpolations, thus generalizing Costa's concavity theorem. We shall provide two proofs of independent interest: the former by $\Gamma$-calculus, hence applicable to…

Information Theory · Computer Science 2020-12-23 Luca Tamanini

This letter reports two moment extensions of the entropy of a distribution. By understanding the traditional entropy as the average of the original distribution up to a random variable transformation, the traditional moments equation become…

Statistical Mechanics · Physics 2008-03-25 Luciano da Fontoura Costa