// Bayesian Network // Elvira format bnet "Continuous1" { // Network Properties kindofgraph = "directed"; visualprecision = "0.00"; version = 1.0; default node states = (absent , present); // Variables node X1(continuous) { title = "NodeX1"; kind-of-node = chance; type-of-variable = continuous; pos_x =201; pos_y =118; relevance = 7.0; purpose = ""; min = 0.0; max = 2.0; precision = 2; } node X2(finite-states) { kind-of-node = chance; type-of-variable = finite-states; pos_x =278; pos_y =390; relevance = 7.0; purpose = ""; num-states = 2; states = ("absent" "present"); } node X3(continuous) { kind-of-node = chance; type-of-variable = continuous; pos_x =591; pos_y =277; relevance = 7.0; purpose = ""; min = -2.0; max = 3.0; precision = 2; } // Links of the associated graph: link X1 X2; link X2 X3; //Network Relationships: relation X1 { comment = ""; kind-of-relation = potential; deterministic=false; values= continuous-tree ( case X1(0.0, 1.0, 2.0) { 0 = 2.0000003252356366-1.0000001626178183* exp( 0.5 * X1); 1 = 0.0+0.06368161035576286* exp( 1.0 * X1); } ); } relation X2 X1 { comment = ""; kind-of-relation = potential; deterministic=false; values= continuous-tree ( case X1(0.0, 1.0, 2.0) { 0 = case X2 { "absent" = 0.3; "present" = 0.7; } 1 = 0.5; } ); } relation X3 X2 { comment = ""; kind-of-relation = potential; deterministic=false; values= continuous-tree ( case X2 { "absent" = 0.0+0.3989422804014327* exp( -0.5 * X3^2+0.0 * X3); "present" = 0.0+0.24197072451914337* exp( -0.5 * X3^2+1.0 * X3); } ); } }