Large Networks (50–100 nodes)



Number of nodes: 56
Number of arcs: 66
Number of parameters: 2656
Average Markov blanket size: 3.54
Average degree: 2.36
Maximum in-degree: 4

BIF (8.9kB)
DSC (7.8kB)
NET (5.6kB)
RDA ( (7.9kB)
RDS ( (7.9kB)

B. Abramson, J. Brown, W. Edwards, A. Murphy, and R. L. Winkler. Hailfinder: A Bayesian system for forecasting severe weather. International Journal of Forecasting, 12(1):57-71, 1996.


Number of nodes: 70
Number of arcs: 123
Number of parameters: 1453
Average Markov blanket size: 4.51
Average degree: 3.51
Maximum in-degree: 6

BIF (12kB)
DSC (11kB)
NET (9.7kB)
RDA ( (15.7kB)
RDS ( (15.7kB)

A. Onisko. Probabilistic Causal Models in Medicine: Application to Diagnosis of Liver Disorders. Ph.D. Dissertation, Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Science, Warsaw, March 2003.


Number of nodes: 76
Number of arcs: 112
Number of parameters: 574
Average Markov blanket size: 5.92
Average degree: 2.95
Maximum in-degree: 7

BIF (4.2kB)
DSC (3.2kB)
NET (2.2kB)
RDA ( (3.9kB)
RDS ( (3.9kB)

Last updated on Tue Nov 29 13:13:24 2022 with bnlearn 4.9-20221107 and R version 4.2.2 Patched (2022-11-10 r83330).