R/gen_asia.R

In BNDataGenerator: Data Generator based on Bayesian Network Model

# Written by Jae-seong Yoo 20141101

gen_asia = function()
{
	arcs_mat = rbind(
			#	A	S	T	L	B	E	X	D
			c(0,	0,	1,	0,	0,	0,	0,	0),	#A
			c(0,	0,	0,	1,	1,	0,	0,	0),	#S
			c(0,	0,	0,	0,	0,	1,	0,	0),	#T
			c(0,	0,	0,	0,	0,	1,	0,	0),	#L
			c(0,	0,	0,	0,	0,	0,	0,	1),	#B
			c(0,	0,	0,	0,	0,	0,	1,	1),	#E
			c(0,	0,	0,	0,	0,	0,	0,	0),	#X
			c(0,	0,	0,	0,	0,	0,	0,	0)		#D
			)
	
	nodename = c("A", "S", "T", "L", "B", "E", "X", "D")
	dimnames(arcs_mat)[[1]] = nodename
	dimnames(arcs_mat)[[2]] = nodename

	
	input_Probs = list(
							c(0.01),						# P(A)
							c(0.5), 						# P(S)
							c(0.05, 0.01),				# P(T|A), P(T|~A)
							c(0.1, 0.01),				# P(L|S), P(L|~S)
							c(0.6, 0.3),				# P(B|S), P(B|~S)
							c(1, 1, 1, 0),				# P(E|T,L), P(E|~T,L), P(E|T,~L), P(E|~T,~L)
							c(0.98, 0.05),				# P(X|E), P(X|~E)
							c(0.9, 0.7, 0.8, 0.1)		# P(D|B,E), P(D|~B,E), P(D|B,~E), P(D|~B,~E)
							)
							
	num_of_nodes = length(nodename)
	cardinality = rep(2, num_of_nodes)
	
	
	result = list(	arcs_mat = arcs_mat,
						Probs = input_Probs,
						nodename = nodename,
						cardinality = cardinality,
						num_of_nodes = num_of_nodes
					)
	return(result)
}