Robustification of the PC-algorithm for directed acyclic graphs
M Kalisch, P Bühlmann - Journal of Computational and Graphical …, 2008 - Taylor & Francis
Journal of Computational and Graphical Statistics, 2008•Taylor & Francis
The PC-algorithm was shown to be a powerful method for estimating the equivalence class
of a potentially very high-dimensional acyclic directed graph (DAG) with the corresponding
Gaussian distribution. Here we propose a computationally eficient robustification of the PC-
algorithm and prove its consistency. Furthermore, we compare the robustified and standard
version of the PC-algorithm on simulated data using the new corresponding R package
pcalg.
of a potentially very high-dimensional acyclic directed graph (DAG) with the corresponding
Gaussian distribution. Here we propose a computationally eficient robustification of the PC-
algorithm and prove its consistency. Furthermore, we compare the robustified and standard
version of the PC-algorithm on simulated data using the new corresponding R package
pcalg.
The PC-algorithm was shown to be a powerful method for estimating the equivalence class of a potentially very high-dimensional acyclic directed graph (DAG) with the corresponding Gaussian distribution. Here we propose a computationally eficient robustification of the PC-algorithm and prove its consistency. Furthermore, we compare the robustified and standard version of the PC-algorithm on simulated data using the new corresponding R package pcalg.
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