Bregman divergence to generalize Bayesian influence measures for data analysis

DOI10.1016/J.JSPI.2020.11.010zbMath1465.62167OpenAlexW3110806027MaRDI QIDQ830727

Melaine C. De Oliveira, Debajyoti Sinha, Dey, Dipak K., Luis Mauricio Castro

Publication date: 7 May 2021

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2020.11.010

zbMATH Keywords

Kullback-Leibler divergenceBayesian robustnessBregman divergencemeta-analysisMCMC algorithmdiagnostic measures

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Robustness and adaptive procedures (parametric inference) (62F35) Monte Carlo methods (65C05)

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Cites Work

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• Bayesian model diagnostics using functional Bregman divergence
• Estimative influence measures for the multivariate general linear model
• Bayesian marginal influence assessment
• Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review
• Statistical Robustness: One View of Its Use in Applications Today
• Detection of Influential Observation in Linear Regression
• The Hat Matrix in Regression and ANOVA
• Robust methods of estimation of regression coefficients¹
• Bayesian Approach for Nonlinear Random Effects Models
• Bayesian analysis of outlier problems using divergence measures
• $\alpha$-Divergence Is Unique, Belonging to Both $f$-Divergence and Bregman Divergence Classes

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