Statistical inference under multiterminal rate restrictions: a differential geometric approach

DOI10.1109/18.32118zbMath0673.62008OpenAlexW2157579481WikidataQ115268263 ScholiaQ115268263MaRDI QIDQ3827379

T. S. Han, Shun-ichi Amari

Publication date: 1989

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/18.32118

zbMATH Keywords

Shannon informationtesting hypothesesasymptotically complete data compressione-affinee-flatnessm-affine connectionsm-flatnessmanifold of all probability distributionstwo-terminal information source

Mathematics Subject Classification ID

Statistical aspects of information-theoretic topics (62B10) Local differential geometry (53B99)

Related Items (8)

Information-Geometric Measure for Neural Spikes ⋮ Gradient systems in view of information geometry ⋮ Detecting higher-order interactions among the spiking events in a group of neurons ⋮ Multiterminal Statistical Inference: An Unsolved Problem ⋮ Information geometry and statistical manifold. ⋮ Fisher information under restriction of Shannon information in multi-terminal situations ⋮ The asymptotic equipartition property in reinforcement learning and its relation to return maximization ⋮ Information Geometry of Interspike Intervals in Spiking Neurons

This page was built for publication: Statistical inference under multiterminal rate restrictions: a differential geometric approach