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TITLE:
Bayesian estimation of information-theoretic metrics for sparsely sampled distributions - imarina:9386996

URV's Author/s:Font Pomarol, Lluc / Guimera Manrique, Roger / Piga, Angelo / Sales Pardo, Marta
Author, as appears in the article.:Piga, Angelo; Font-Pomarol, Lluc; Sales-Pardo, Marta; Guimera, Roger
Author's mail:marta.sales@urv.cat
lluc.fonti@estudiants.urv.cat
lluc.fonti@estudiants.urv.cat
roger.guimera@urv.cat
Author identifier:0000-0002-8140-6525
0000-0002-3597-4310
Journal publication year:2024
Publication Type:Journal Publications
APA:Piga, Angelo; Font-Pomarol, Lluc; Sales-Pardo, Marta; Guimera, Roger (2024). Bayesian estimation of information-theoretic metrics for sparsely sampled distributions. Chaos Solitons & Fractals, 180(), 114564-. DOI: 10.1016/j.chaos.2024.114564
Papper original source:Chaos Solitons & Fractals. 180 114564-
Abstract:Estimating the Shannon entropy of a discrete distribution from which we have only observed a small sample is challenging. Estimating other information-theoretic metrics, such as the Kullback-Leibler divergence between two sparsely sampled discrete distributions, is even harder. Here, we propose a fast, semi-analytical estimator for sparsely sampled distributions. Its derivation is grounded in probabilistic considerations and uses a hierarchical Bayesian approach to extract as much information as possible from the few observations available. Our approach provides estimates of the Shannon entropy with precision at least comparable to the benchmarks we consider, and most often higher; it does so across diverse distributions with very different properties. Our method can also be used to obtain accurate estimates of other information-theoretic metrics, including the notoriously challenging Kullback-Leibler divergence. Here, again, our approach has less bias, overall, than the benchmark estimators we consider.
Article's DOI:10.1016/j.chaos.2024.114564
Link to the original source:https://www.sciencedirect.com/science/article/pii/S0960077924001152?via%3Dihub
Papper version:info:eu-repo/semantics/publishedVersion
licence for use:https://creativecommons.org/licenses/by/3.0/es/
Department:Enginyeria Química
Licence document URL:https://repositori.urv.cat/ca/proteccio-de-dades/
Thematic Areas:Applied mathematics
Astronomia / física
Ciência da computação
Ciências biológicas i
Ciências biológicas ii
Direito
Economia
Engenharias i
Engenharias ii
Engenharias iii
Engenharias iv
General mathematics
General physics and astronomy
Geociências
Interdisciplinar
Matemática / probabilidade e estatística
Materiais
Mathematical physics
Mathematics (all)
Mathematics (miscellaneous)
Mathematics, applied
Mathematics, interdisciplinary applications
Physics
Physics and astronomy (all)
Physics and astronomy (miscellaneous)
Physics, mathematical
Physics, multidisciplinary
Química
Statistical and nonlinear physics
Keywords:Bayesian estimation
Entropy estimation
Inferenc
Information theor
Information theory
Kullback-leibler divergence
Kullback–leibler divergence
Shannon entropy
Sparse sampling
Entity:Universitat Rovira i Virgili
Record's date:2024-10-19
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