Bayesian Joint Modeling of Multiple Brain Functional Networks

DOI10.1080/01621459.2020.1796357zbMath1464.62460arXiv1708.02123OpenAlexW3043202398MaRDI QIDQ4999125

Giuseppe Pagnoni, Joshua Lukemire, Ying Guo, Suprateek Kundu

Publication date: 6 July 2021

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1708.02123

zbMATH Keywords

Dirichlet processbrain networksspike-and-slab priormultiple graphical modelsstroop task

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Neural biology (92C20) Probabilistic graphical models (62H22)

Related Items (3)

A random covariance model for bi‐level graphical modeling with application to resting‐state fMRI data ⋮ An Expectation Conditional Maximization Approach for Gaussian Graphical Models ⋮ Semi-parametric Bayes regression with network-valued covariates

Uses Software

• glasso
• AFNI
• Brain Connectivity Toolbox
• GHS

Cites Work

• Unnamed Item
• Unnamed Item
• Sparsity information and regularization in the horseshoe and other shrinkage priors
• Sparse inverse covariance estimation with the graphical lasso
• Brain Connectivity Toolbox
• A Dirichlet process mixture model for the analysis of correlated binary responses
• Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
• Bayesian graphical Lasso models and efficient posterior computation
• Distribution of the Estimators for Autoregressive Time Series With a Unit Root
• Emergence of Scaling in Random Networks
• Joint estimation of multiple graphical models
• Bayesian Kernel Mixtures for Counts
• Bayesian Multivariate Logistic Regression
• Sampling the Dirichlet Mixture Model with Slices
• Model selection and estimation in the Gaussian graphical model
• The horseshoe estimator for sparse signals
• Bayesian curve fitting using multivariate normal mixtures
• Structural Pursuit Over Multiple Undirected Graphs
• The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes
• Nonparametric Priors for Ordinal Bayesian Social Science Models: Specification and Estimation
• Collective dynamics of ‘small-world’ networks
• Bayesian Inference of Multiple Gaussian Graphical Models
• Joint Estimation of Multiple Graphical Models from High Dimensional Time Series
• Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables
• On Joint Estimation of Gaussian Graphical Models for Spatial and Temporal Data

This page was built for publication: Bayesian Joint Modeling of Multiple Brain Functional Networks