# test input file for graph_sampler
# directed acyclic graph (BN) inference with 3 nodes,
# basic edge prior and concordance prior, normal-gamma data model,
# imported Bernoulli prior, imported data file with missing data
# =========================================================================

my_var = 4; # user-defined variable (for testing the parser)

n_runs    = 1E5 + my_var - 4;
n_burn_in = 0.25E4 * my_var;

random_seed = 49740;

n_nodes = my_var - 1;

bayesian_network = true;

initial_adjacency = matrix
{0, 1, 0,
 0, 0, 1,
 0, 0, 0};

hyper_pB = import_file {"prior_BN_7.dat"};

concordance_prior = true;            
lambda_concordance = 1.0;                
edge_requirements = matrix           
{-1,-1,-1,
  1,-1,-1,
  1,-1,-1};     

likelihood = normal_gamma;

n_data = 4;

n_data_levels = array {2, 2, 2};

data = import_file {"data_BN_7.dat"};

save_chain = true;
n_saved_adjacency = 20;
save_best_graph = true;  
save_edge_probabilies = true;

# End.
