Bayesian influence diagnostics using normalized functional Bregman divergence

DOI10.1080/03610926.2020.1764583OpenAlexW2931392955MaRDI QIDQ5079887

Ian M. Danilevicz, Ricardo S. Ehlers

Publication date: 30 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1904.03717

zbMATH Keywords

Bayesian inferenceinfluential observationsHamiltonian Monte Carlofunctional Bregman divergence

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• R
• Stan
• BayesDA
• NUTS

Cites Work

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• Primal-dual subgradient methods for convex problems
• The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
• A flexible prior distribution for Markov switching autoregressions with Student-\(t\) errors
• Bayesian case influence analysis for GARCH models based on Kullback-Leibler divergence
• Bayesian model diagnostics using functional Bregman divergence
• Spatial statistics and modeling. Translated from the French by Kevin Bleakley.
• Generalized autoregressive conditional heteroscedasticity
• Reconciling Curvature and Importance Sampling Based Procedures for Summarizing Case Influence in Bayesian Models
• Simulating Hamiltonian Dynamics
• Functional Bregman Divergence and Bayesian Estimation of Distributions
• Bayesian Case Influence Diagnostics for Survival Models
• Importance-Weighted Marginal Bayesian Posterior Density Estimation
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

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