dataSim200 is a
list with the adjacency matrix of a randomly generated DAG with 200 nodes and 100 edges, 10 samples generated from the DAG and 5 permutations of the nodes.
dataSim200 contains the following objects:
List of 10 matrices (100x200) each of which with 100 observations simulated from the DAG.
List of 5 matrices (1x200) each of which with a permutation of the nodes.
Matrix (200x200) with the adjacency matrix of the DAG.
D. Altomare, G. Consonni and L. La Rocca (2012). Objective Bayesian search of gaussian directed acyclic graphical models for ordered variables with non-local priors. Article submitted to Biometric Methodology.
Shojaie, A. and Michailidis, G. (2010). Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs. Biometrika 97, 519-538.
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