An implementation of the iterative proportional fitting procedure by propagation trees

Computational Statistics and Data Analysis

Volumn 37, Issue 3, 2001, Pages 297-322

  Badsberg, J H ^a   Malvestuto, F M ^b  

^a AARHUS UNIVERSITY   (Denmark)

^b SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

Acyclic hypergraph; Iterative proportional fitting procedure; Markov extension; Probabilistic database; Propagation tree

Indexed keywords

CURVE FITTING; ITERATIVE METHODS; OPTIMIZATION; TREES (MATHEMATICS);

MARKOVIAN PROPAGATION TREES;

MARKOV PROCESSES;

NUMERICAL METHOD;

EID: 0035964959     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9473(01)00013-5     Document Type: Article

References (50)

1. Complexity of finding embeddings in a k-tree
2. Decomposition of graphs and hypergraphs with identification of conformal hypergraphs
3. A Sufficiently Fast Algorithm for Finding Close to Optimal Junction Trees
4. On the desirability of acyclic database schemes
5. A linear-time algorithm for finding tree-decompositions of small treewidth
6. I-divergence geometry of probability distributions and minimization problems
7. Markov fields and log-linear interaction models for contingency tables
8. Applications of a general propagation algorithm for probabilistic expert systems
9. On a least squares adjustment of a sampled frequency table when the expected marginal totals are known
10. A fast algorithm for iterative proportional fitting in log-linear models
11. Optimal junction trees
12. Solution of the marginal problem and decomposable distributions
13. On the effective implementation of the iterative proportional fitting procedure
14. Verteilungsfunktionen mit gegebenen Marginalverteilungen
15. Optimal decomposition of probabilistic networks by simulated annealing
16. Treewidth: Computations and approximations
17. Decomposing Bayesian networks: Triangulation of the moral graph with genetic algorithms
18. Propagation of probabilities
19. Decomposable graphs and hypergraphs
20. Local computations with probabilities on graphical structures and their application to expert systems
21. Optimal decompositions by clique-separators
22. Existence of extensions and product extensions for discrete probability distributions
23. Computing the maximum-entropy extension of given discrete probability distributions
24. Computing marginals in graphical log-linear models
25. A hypergraph-theoretic analysis of collapsibility and decomposability for extended log-linear models
26. A fast algorithm for query optimization in universal-relation databases
27. Decomposition of a hypergraph by partial-edge separators
28. Algorithmic aspects of vertex elimination on graphs
29. On linear recognition of tree-width at most four
30. Probabilistic expert systems
31. On the tree representation of chordal graphs
32. Probabilistic reasoning in predictive expert systems
33. Decomposition by clique-separators
34. Simple linear-time algorithms to test chordality of graphs, test acyclicity of hypergraphs, and selectively reduce acyclic hypergraphs
35. Consistent families of measures and their extensions
36. Markov measures and Markov extensions
37. Optimal decomposition of belief networks
38. Computing the minimum fill-in is NP-complete