SOME NEW PROPERTIES OF HELLINGER DISTANCE FOR VALIDATING APPROXIMATIONS IN BAYESIAN ANALYSIS

DOI10.17654/AS051040261zbMath1387.62035MaRDI QIDQ4635417

Ali S. Gargoum

Publication date: 17 April 2018

Published in: Advances and Applications in Statistics (Search for Journal in Brave)

zbMATH Keywords

Bayesian networksHellinger distanceinformation distancegraphical modellingKullback-Leibler (K-L) measure

Mathematics Subject Classification ID

Bayesian inference (62F15) Statistical aspects of information-theoretic topics (62B10) Graphical methods in statistics (62A09)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Approximate distributions of order statistics. With applications to nonparametric statistics
• Bayesian forecasting and dynamic models
• Fast Bayes and the dynamic junction forest
• Bayesian analysis in expert systems. With comments and a rejoinder by the authors
• On the notion of affinity of several distributions and some of its applications
• Propagation of Probabilities, Means, and Variances in Mixed Graphical Association Models
• On Using Hellinger Distance in Checking the Validity of Dynamic Approximations
• A Hellinger distance approach to MCMC diagnostics

This page was built for publication: SOME NEW PROPERTIES OF HELLINGER DISTANCE FOR VALIDATING APPROXIMATIONS IN BAYESIAN ANALYSIS