Bayesian measures of leverage and influence

Fuente: arXiv
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Main Author: Plummer, Martyn
Format: Preprint
Published: 2025
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author Plummer, Martyn
author_facet Plummer, Martyn
contents Local sensitivity diagnostics for Bayesian models are described that are analogues of frequentist measures of leverage and influence. The diagnostics are simple to calculate using MCMC. A comparison between leverage and influence allows a general purpose definition of an outlier based on local perturbations. These outliers may indicate areas where the model does not fit well even if they do not influence model fit. The sensitivity diagnostics are closely related to predictive information criteria that are commonly used for Bayesian model choice. A diagnostic for prior-data conflict is proposed that may also be used to measure cross-conflict between different parts of the data.
format Preprint
id arxiv_https___arxiv_org_abs_2503_19996
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Bayesian measures of leverage and influence
Plummer, Martyn
Methodology
62J20 (Primary) 62F15 (Secondary)
Local sensitivity diagnostics for Bayesian models are described that are analogues of frequentist measures of leverage and influence. The diagnostics are simple to calculate using MCMC. A comparison between leverage and influence allows a general purpose definition of an outlier based on local perturbations. These outliers may indicate areas where the model does not fit well even if they do not influence model fit. The sensitivity diagnostics are closely related to predictive information criteria that are commonly used for Bayesian model choice. A diagnostic for prior-data conflict is proposed that may also be used to measure cross-conflict between different parts of the data.
title Bayesian measures of leverage and influence
topic Methodology
62J20 (Primary) 62F15 (Secondary)
url https://arxiv.org/abs/2503.19996