A weakly informative prior for Bayesian dynamic model selection with applications in fMRI

DOI10.1080/02664763.2017.1363161OpenAlexW2624320126MaRDI QIDQ5035723

Jairo Alberto Fúquene Patiño, Brenda Betancourt, João B. M. Pereira

Publication date: 22 February 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1603.08602

zbMATH Keywords

sparsitydynamic linear modelsbeta prime priorfunctional magnetic imaging data

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• R
• astsa

Cites Work

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• An alternative to the inverted gamma for the variances to modelling outliers and structural breaks in dynamic models
• Bayesian sparsity-path-analysis of genetic association signal using generalized \(t\) priors
• Mixtures of \(g\)-priors for Bayesian model averaging with economic applications
• The statistical analysis of functional MRI data
• Model uncertainty
• An exploration of aspects of Bayesian multiple testing
• Good, great, or lucky? Screening for firms with sustained superior performance using heavy-tailed priors
• On the half-Cauchy prior for a global scale parameter
• Inference with normal-gamma prior distributions in regression problems
• The horseshoe estimator for sparse signals
• Mixtures of g Priors for Bayesian Variable Selection
• DATA AUGMENTATION AND DYNAMIC LINEAR MODELS
• Statistical Issues in fMRI for Brain Imaging
• Generalized double Pareto shrinkage
• Priors and Component Structures in Autoregressive Time Series Models
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

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