611 citations · 1.4k across the 9 of their papers we have counts for
4 papers · 1 filter
Interpreting and using CPDAGs with background knowledge
Emilija Perković, Markus Kalisch, Maloes H. Maathuis
We develop terminology and methods for working with maximally oriented partially directed acyclic graphs (maximal PDAGs). Maximal PDAGs arise from imposing restrictions on a Markov…
Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs
Emilija Perković, Johannes Textor, Markus Kalisch +1
We present a graphical criterion for covariate adjustment that is sound and complete for four different classes of causal graphical models: directed acyclic graphs (DAGs), maximum…
A Complete Generalized Adjustment Criterion
Emilija Perković, Johannes Textor, Markus Kalisch +1
Covariate adjustment is a widely used approach to estimate total causal effects from observational data. Several graphical criteria have been developed in recent years to identify…
Estimating high-dimensional directed acyclic graphs with the PC-algorithm
Markus Kalisch, Peter Buehlmann
We consider the PC-algorithm Spirtes et. al. (2000) for estimating the skeleton of a very high-dimensional acyclic directed graph (DAG) with corresponding Gaussian distribution. Th…