Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Open Access
- 11 January 2010
- journal article
- research article
- Published by Springer Nature in BMC Bioinformatics
- Vol. 11 (1) , 18
- https://doi.org/10.1186/1471-2105-11-18
Abstract
Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example Kruskal's algorithm. The efficiency of the algorithm makes it tractable for high-dimensional problems.Keywords
This publication has 35 references indexed in Scilit:
- A Graphical Model Formulation of the DNA Base-Calling ProblemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Dependency trees in sub-linear time and bounded memoryThe VLDB Journal, 2006
- A Guide to the Literature on Inferring Genetic Networks by Probabilistic Graphical ModelsPublished by Wiley ,2005
- A formal approach to using data distributions for building causal polytree structuresInformation Sciences, 2004
- Embedded Trees: Estimation of Gaussian Processes on Graphs with CyclesIEEE Transactions on Signal Processing, 2004
- Inferring Cellular Networks Using Probabilistic Graphical ModelsScience, 2004
- Maximum likelihood bounded tree-width Markov networksArtificial Intelligence, 2003
- 10.1162/153244301753344605Applied Physics Letters, 2000
- Approximating discrete probability distributions with dependence treesIEEE Transactions on Information Theory, 1968
- On the shortest spanning subtree of a graph and the traveling salesman problemProceedings of the American Mathematical Society, 1956