Information Geometry of Generalized Bayesian Prediction Using $\alpha$ -Divergences as Loss Functions

DOI10.1109/TIT.2017.2774820zbMath1390.94645OpenAlexW2769340239MaRDI QIDQ4566746

Ruibing Wang, Hon Keung Tony Ng, Yimin Shi, Fode Zhang

Publication date: 27 June 2018

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

Full work available at URL: https://doi.org/10.1109/tit.2017.2774820

Mathematics Subject Classification ID

Bayesian inference (62F15) Measures of information, entropy (94A17) Statistical aspects of information-theoretic topics (62B10)

Related Items (7)

Information geometry on the curved \(q\)-exponential family with application to survival data analysis ⋮ Geometry on degradation models and mis-specification analysis by using \(\alpha\)-divergence ⋮ Convergence of estimative density: criterion for model complexity and sample size ⋮ Optimal shrinkage estimation of predictive densities under \(\alpha\)-divergences ⋮ The geometric structure on a degradation model with application to optimal design under a cost constraint ⋮ Minimax predictive density for sparse count data ⋮ Geometry on the statistical manifold induced by the degradation model with soft failure data

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