Maximally Informative Statistics

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dc.creatorWolf, David R.
dc.creatorGeorge, Edward I.
dc.date2000-10-15
dc.date.accessioned2026-07-07T05:44:55Z
dc.date.available2026-07-07T05:44:55Z
dc.descriptionIn this paper we propose a Bayesian, information theoretic approach to dimensionality reduction. The approach is formulated as a variational principle on mutual information, and seamlessly addresses the notions of sufficiency, relevance, and representation. Maximally informative statistics are shown to minimize a Kullback-Leibler distance between posterior distributions. Illustrating the approach, we derive the maximally informative one dimensional statistic for a random sample from the Cauchy distribution.
dc.description13 pages. Presented Bayesian Statistics 6, Valencia, 1998. Arxiv version asserts bold vectors dropped in print
dc.identifierhttps://arxiv.org/abs/physics/0010039
dc.identifierhttp://arxiv.org/abs/physics/0010039
dc.identifierMonograph on Bayesian Methods in the Sciences, Rev. R. Acad. Sci. Exacta. Fisica. Nat. Vol. 93, No. 3, pp. 381--386, 1999
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/83830
dc.subjectData Analysis, Statistics and Probability
dc.titleMaximally Informative Statistics
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