Pages that link to "Item:Q1952170"
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The following pages link to A Metropolis-Hastings based method for sampling from the \(G\)-Wishart distribution in Gaussian graphical models (Q1952170):
Displaying 15 items.
- Bayesian state space models for dynamic genetic network construction across multiple tissues (Q309414) (← links)
- Bayesian graphical models for differential pathways (Q516442) (← links)
- High dimensional posterior convergence rates for decomposable graphical models (Q902216) (← links)
- Exact formulas for the normalizing constants of Wishart distributions for graphical models (Q1747734) (← links)
- Modeling correlated marker effects in genome-wide prediction via Gaussian concentration graph models (Q1752364) (← links)
- Bayesian method for causal inference in spatially-correlated multivariate time series (Q1757655) (← links)
- Efficient Gaussian graphical model determination under \(G\)-Wishart prior distributions (Q1950810) (← links)
- Hierarchical Gaussian graphical models: beyond reversible jump (Q1950899) (← links)
- Simulation of hyper-inverse Wishart distributions for non-decomposable graphs (Q1952111) (← links)
- Statistical inference of reliability of generalized Rayleigh distribution under progressively type-II censoring (Q2315846) (← links)
- Bayesian Approaches for Large Biological Networks (Q2800194) (← links)
- A Bayesian Subset Specific Approach to Joint Selection of Multiple Graphical Models (Q6069494) (← links)
- Bayesian sparse graphical models and their mixtures (Q6537781) (← links)
- Efficient sampling of Gaussian graphical models using conditional Bayes factors (Q6537807) (← links)
- A direct sampler for G-Wishart variates (Q6537842) (← links)
