Time-varying dynamic Bayesian network learning for an fMRI study of emotion processing
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Publication:6615922
DOI10.1002/SIM.10096zbMATH Open1546.62721MaRDI QIDQ6615922
Aiying Zhang, Lizhe Sun, Faming Liang
Publication date: 8 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
variable selectionsparse graphical modeldynamic Bayesian networkbrain connectivityMarkov neighborhood regression
Cites Work
- Title not available (Why is that?)
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- Sure independence screening in generalized linear models with NP-dimensionality
- On asymptotically optimal confidence regions and tests for high-dimensional models
- Nearly unbiased variable selection under minimax concave penalty
- Sparse inverse covariance estimation with the graphical lasso
- Statistics for high-dimensional data. Methods, theory and applications.
- Learning Bayesian networks for discrete data
- The stochastic EM algorithm: Estimation and asymptotic results
- High-dimensional graphs and variable selection with the Lasso
- Confidence Intervals and Hypothesis Testing for High-Dimensional Regression
- A scalable multi-resolution spatio-temporal model for brain activation and connectivity in fMRI data
- Estimating the false discovery rate using the stochastic approximation algorithm
- Learning Causal Bayesian Network Structures From Experimental Data
- Stochastic versions of the em algorithm: an experimental study in the mixture case
- Empirical Bayes Analysis of a Microarray Experiment
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- An Imputation–Regularized Optimization Algorithm for High Dimensional Missing Data Problems and Beyond
- Sure Independence Screening for Ultrahigh Dimensional Feature Space
- A Direct Approach to False Discovery Rates
- A Bayesian Approach for Estimating Dynamic Functional Network Connectivity in fMRI Data
- The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes
- Learning Moral Graphs in Construction of High-Dimensional Bayesian Networks for Mixed Data
- Regularization and Variable Selection Via the Elastic Net
- Bayesian Inference of Multiple Gaussian Graphical Models
- An Equivalent Measure of Partial Correlation Coefficients for High-Dimensional Gaussian Graphical Models
- Joint Estimation of Multiple Graphical Models from High Dimensional Time Series
- Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
- Markov Neighborhood Regression for High-Dimensional Inference
- Joint estimation of multiple mixed graphical models for pan-cancer network analysis
- Bayesian models for functional magnetic resonance imaging data analysis
- Markov neighborhood regression for statistical inference of high-dimensional generalized linear models
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