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Related papers: Existence and Uniqueness of Proper Scoring Rules

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For certain groups, parabolic subgroups appear as stabilizers of flags of sets or vector spaces. Quotients by these parabolic subgroups represent orbits of flags, and their cardinalities asymptotically reveal entropies (as rates of…

Information Theory · Computer Science 2025-12-03 Ryan Leal , Jingtong Sun , Juan Pablo Vigneaux

This paper introduces an objective metric for evaluating a parsing scheme. It is based on Shannon's original work with letter sequences, which can be extended to part-of-speech tag sequences. It is shown that this regular language is an…

cmp-lg · Computer Science 2008-02-03 Caroline Lyon , Stephen Brown

A scoring rule is a loss function measuring the quality of a quoted probability distribution $Q$ for a random variable $X$, in the light of the realized outcome $x$ of $X$; it is proper if the expected score, under any distribution $P$ for…

Statistics Theory · Mathematics 2012-06-01 A. Philip Dawid , Steffen Lauritzen , Matthew Parry

A consistent generalization of statistical mechanics is obtained by applying the maximum entropy principle to a trace-form entropy and by requiring that physically motivated mathematical properties are preserved. The emerging…

Statistical Mechanics · Physics 2009-11-10 G. Kaniadakis , M. Lissia , A. M. Scarfone

Entropic independence is a structural property of measures that underlies modern proofs of functional inequalities, notably (modified) log-Sobolev inequalities, via ``annealing'' or local-to-global schemes. Existing sufficient criteria for…

Information Theory · Computer Science 2026-04-14 Vishesh Jain , Huy Tuan Pham , Thuy-Duong Vuong

We construct model sets arising from cut and project schemes in Euclidean spaces whose associated Delone dynamical systems have positive toplogical entropy. The construction works both with windows that are proper and with windows that have…

Dynamical Systems · Mathematics 2018-06-26 Tobias Jäger , Daniel Lenz , Christian Oertel

We introduce the (private) entropy of a directed graph (in a new network coding sense) as well as a number of related concepts. We show that the entropy of a directed graph is identical to its guessing number and can be bounded from below…

Combinatorics · Mathematics 2007-11-28 Soren Riis

This paper investigates functions from $\mathbb{R}^d$ to $\mathbb{R} \cup \{\pm \infty\}$ that satisfy axioms of linearity wherever allowed by extended-value arithmetic. They have a nontrivial structure defined inductively on $d$, and…

Statistics Theory · Mathematics 2025-04-25 Bo Waggoner

Here we deconstruct, and then in a reasoned way reconstruct, the concept of "entropy of a system," paying particular attention to where the randomness may be coming from. We start with the core concept of entropy as a COUNT associated with…

General Physics · Physics 2017-05-10 Tommaso Toffoli

Sparsity and entropy are pillar notions of modern theories in signal processing and information theory. However, there is no clear consensus among scientists on the characterization of these notions. Previous efforts have contributed to…

Information Theory · Computer Science 2015-12-18 Giancarlo Pastor , Inmaculada Mora-Jiménez , Riku Jäntti , Antonio J. Caamaño

We determine the explicit universal form of the entanglement and Renyi entropies, for regions with arbitrary boundary on a null plane or the light-cone. All the entropies are shown to saturate the strong subadditive inequality. This Renyi…

High Energy Physics - Theory · Physics 2018-06-13 Horacio Casini , Eduardo Teste , Gonzalo Torroba

We discuss weighted scoring rules for forecast evaluation and their connection to hypothesis testing. First, a general construction principle for strictly locally proper weighted scoring rules based on conditional densities and scoring…

Methodology · Statistics 2017-01-12 Hajo Holzmann , Bernhard Klar

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

Entropy and differential entropy are important quantities in information theory. A tractable extension to singular random variables-which are neither discrete nor continuous-has not been available so far. Here, we present such an extension…

Information Theory · Computer Science 2017-01-04 Günther Koliander , Georg Pichler , Erwin Riegler , Franz Hlawatsch

A marginal problem asks whether a given family of marginal distributions for some set of random variables arises from some joint distribution of these variables. Here we point out that the existence of such a joint distribution imposes…

Information Theory · Computer Science 2013-01-25 Tobias Fritz , Rafael Chaves

In many applications, the probability density function is subject to experimental errors. In this work the continuos dependence of a class of generalized entropies on the experimental errors is studied. This class includes the C. Shannon,…

Data Analysis, Statistics and Probability · Physics 2016-05-20 György Steinbrecher , Giorgio Sonnino

Within a framework of utmost generality, we show that the entropy maximization procedure with linear constraints uniquely leads to the Shannon-Boltzmann-Gibbs entropy. Therefore, the use of this procedure with linear constraints should not…

Statistical Mechanics · Physics 2018-05-01 Thomas Oikonomou , G. Baris Bagci

The closure of the set of entropy functions associated with n discrete variables, Gammar*n, is a convex cone in (2n-1)- dimensional space, but its full characterization remains an open problem. In this paper, we map Gammar*n to an…

Information Theory · Computer Science 2009-04-14 Qi Chen , Chen He , Lingge Jiang , Qingchuan Wang

Upper and lower bounds are obtained for the joint entropy of a collection of random variables in terms of an arbitrary collection of subset joint entropies. These inequalities generalize Shannon's chain rule for entropy as well as…

Information Theory · Computer Science 2024-05-07 Mokshay Madiman , Prasad Tetali

Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distribution and on the event or value that materializes. A scoring rule is proper if it encourages truthful reporting. It…

Statistics Theory · Mathematics 2012-06-01 Werner Ehm , Tilmann Gneiting