Algorithm for Searching the Space of Gaussian Directed Acyclic Graph Models Through Moment Fractional Bayes Factors
Cell signalling pathway data
Publishing productivity data
DAG model with 100 nodes and 100 edges
DAG model with 200 nodes and 100 edges
DAG model with 50 nodes and 100 edges
DAG model with 6 nodes and 5 edges
Simulated cell signalling pathway data
Moment Fractional Bayes Factor Stochastic Search with Global Prior for...
Moment Fractional Bayes Factor Stochastic Search with Local Prior for ...
Moment Fractional Bayes Factor Stochastic Search for Regression Models
We propose an objective Bayesian algorithm for searching the space of Gaussian directed acyclic graph (DAG) models. The algorithm uses moment fractional Bayes factors (MFBF) and is suitable for learning sparse graphs. The algorithm is implemented using Armadillo, an open-source C++ linear algebra library.