DAGs are diagrams used to represent causal questions. They serve as a visual aid to summarize assumptions about causal and non-causal associations between a given exposure and an outcome. DAGs are ...

Recent clinical trials in oncology have used increasingly complex methodologies, such as causal inference methods for intercurrent events, external control, and covariate adjustment, posing challenges ...

Michael S. Haigh, David A. Bessler, Causality and Price Discovery: An Application of Directed Acyclic Graphs, The Journal of Business, Vol. 77, No. 4 (October 2004 ...

Chain graphs are a natural generalization of directed acyclic graphs and undirected graphs. However, the apparent simplicity of chain graphs belies the subtlety of the conditional independence ...

"MANM is based on Directed Acyclic Graphs (DAGs), which can identify a multi-nodal causal structure. MANM can estimate every possible causal direction in complex feature sets, with no missing or ...

On Thursday the 21st of November 2019, M.Sc. Topi Talvitie will defend his doctoral thesis on Counting and Sampling Directed Acyclic Graphs for Learning Bayesian Networks. The thesis is a part of ...