The TETRAD Project: Constraint Based Aids to Causal Model Specification

by Richard Scheines , Peter Spirtes , Clark Glymour , Christopher Meek , Thomas Richardson
Venue:MULTIVARIATE BEHAVIORAL RESEARCH
Citations:12 - 0 self

Active Bibliography

10 Causal Inference – Peter Spirtes, Richard Scheines, Clark Glymour, Thomas Richardson, Christopher Meek
36 Learning Probabilistic Networks – Paul J Krause - 1998
48 Chain Graph Models and their Causal Interpretations – Steffen L. Lauritzen, Thomas S. Richardson - 2001
2 LEARNING THE STRUCTURE OF BAYESIAN NETWORKS WITH CONSTRAINT SATISFACTION – Andrew S. Fast - 2010
17 A Scoring Function for Learning Bayesian Networks based on Mutual Information and Conditional Independence Tests – Luis M. de Campos - 2006
913 Learning Bayesian networks: The combination of knowledge and statistical data – David Heckerman, David M. Chickering - 1995
unknown title – Learning Bayesian
849 A tutorial on learning with Bayesian networks – David Heckerman - 1995
44 Graphs, Causality, And Structural Equation Models – Judea Pearl - 1998
19 Learning Causal Networks from Data: A survey and a new algorithm for recovering possibilistic causal networks – Ramon Sangüesa, Ulises Cortés - 1997
172 A Guide to the Literature on Learning Probabilistic Networks From Data – Wray Buntine - 1996
731 Using Bayesian networks to analyze expression data – Nir Friedman, Michal Linial, Iftach Nachman - 2000
37 Improved learning of Bayesian networks – Robert Castelo, Craig Boutilier - 2001
1 Causality in the Social and Behavioral Sciences – Judea Pearl - 2009
The Foundations of Causal Inference: A Review – Judea Pearl - 2010
6 The Foundations of Causal Inference – Judea Pearl - 2010
29 An Introduction to Causal Inference – Judea Pearl - 2009
58 A Bayesian approach to learning causal networks – David Heckerman - 1995
MINIMAL SUFFICIENT CAUSATION AND DIRECTED ACYCLIC GRAPHS – Tyler J. V, James M. Robins - 906