Spatial modeling of brain connectivity data via latent distance models with nodes clustering

DOI10.1002/sam.11412OpenAlexW2936854052MaRDI QIDQ4970244

Daniele Durante, Emanuele Aliverti

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10278/3740791

zbMATH Keywords

latent space modelspatial effectmixture of gaussians priorstructural brain network

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Related Items (1)

Stratified Stochastic Variational Inference for High-Dimensional Network Factor Model

Uses Software

• latentnet
• Label.switching
• Brain Connectivity Toolbox

Cites Work

• Asymptotic Behaviour of the Posterior Distribution in Overfitted Mixture Models
• How Bayesian analysis cracked the red-state, blue-state problem
• The Pólya-gamma Gibbs sampler for Bayesian logistic regression is uniformly ergodic
• Latent space models for multiview network data
• Bayesian inference and testing of group differences in brain networks
• Mixed membership stochastic blockmodels
• Sampling-Based Approaches to Calculating Marginal Densities
• Markov Graphs
• Estimation and Prediction for Stochastic Blockstructures
• Latent Space Approaches to Social Network Analysis
• Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables

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