Semiparametric Bayes conditional graphical models for imaging genetics applications
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Publication:6539192
DOI10.1002/sta4.119MaRDI QIDQ6539192
Publication date: 14 May 2024
Published in: Stat (Search for Journal in Brave)
variable selectionmodularityimaging geneticssemiparametric Bayesbrain functional networkconditional graphical model
Cites Work
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- A sparse conditional Gaussian graphical model for analysis of genetical genomics data
- Sparse inverse covariance estimation with the graphical lasso
- Hyper Markov laws in the statistical analysis of decomposable graphical models
- Estimation in Dirichlet random effects models
- Joint High‐Dimensional Bayesian Variable and Covariance Selection with an Application to eQTL Analysis
- An Integrative Bayesian Modeling Approach to Imaging Genetics
- A General Probabilistic Model for Group Independent Component Analysis and Its Estimation Methods
- The Bayesian Lasso
- Sparse Estimation of Conditional Graphical Models With Application to Gene Networks
- Bayesian Generalized Low Rank Regression Models for Neuroimaging Phenotypes and Genetic Markers
- Covariate-adjusted precision matrix estimation with an application in genetical genomics
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