An algebraic generalization of the entropy and its application to statistics

We define a general notion of entropy in elementary, algebraic terms. Based on that, weak forms of a scalar product and a distance measure are derived. We give basic properties of these quantities, generalize the Cauchy-Schwarz inequality, and relate our approach to the theory of scoring rules. Many supporting examples illustrate our approach and give new perspectives on established notions, such as the likelihood, the Kullback-Leibler divergence, the uncorrelatedness of random variables, the scalar product itself, the Tichonov regularization and the mutual information.

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Publication Details

Journal
Journal of Applied Statistics
Published
2026-08-20
DOI
https://doi.org/10.1080/02664763.2026.2711746
Citations
1
Primary Topic
Statistical Mechanics and Entropy
Type
article
Field-Weighted Citation Impact
5.48
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article

An algebraic generalization of the entropy and its application to statistics

Martin Schlather
1 citations
Journal of Applied Statistics
Statistical Mechanics and Entropy
5.48
article

An algebraic generalization of the entropy and its application to statistics

Martin Schlather
article en
1 citations

Abstract

We define a general notion of entropy in elementary, algebraic terms. Based on that, weak forms of a scalar product and a distance measure are derived. We give basic properties of these quantities, generalize the Cauchy-Schwarz inequality, and relate our approach to the theory of scoring rules. Many supporting examples illustrate our approach and give new perspectives on established notions, such as the likelihood, the Kullback-Leibler divergence, the uncorrelatedness of random variables, the scalar product itself, the Tichonov regularization and the mutual information.

Journal of Applied Statistics
University of Mannheim (DE)
Openalex Percentile: Top 9%
Statistical Mechanics and Entropy
5.48
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