library(bnlearn)

net = model2network("[smoke][lung|smoke][bronc|smoke][xrays|lung][dysp|lung:bronc]")

cpt1.smoke = matrix(c(0.25, 0.75), ncol = 2, 
		   dimnames = list(NULL, c('true', 'false')))
cpt2.smoke = matrix(c(0.5, 0.5), ncol = 2, 
		   dimnames = list(NULL, c('true', 'false')))

cpt1.lung = c(0.15, 0.85, 0.05, 0.95)
dim(cpt1.lung) = c(2, 2)
dimnames(cpt1.lung) = list("lung" = c("true", "false"), 
					"smoke" =  c("true", "false"))
cpt2.lung = c(0.4, 0.6, 0.1, 0.9)
dim(cpt2.lung) = c(2, 2)
dimnames(cpt2.lung) = list("lung" = c("true", "false"), 
					"smoke" =  c("true", "false"))
cpt1.bronc = c(0.3, 0.7, 0.2, 0.8)
dim(cpt1.bronc) = c(2, 2)
dimnames(cpt1.bronc) = list("bronc" = c("true", "false"), 
					 "smoke" =  c("true", "false"))
cpt2.bronc = c(0.55, 0.45, 0.3, 0.7)
dim(cpt2.bronc) = c(2, 2)
dimnames(cpt2.bronc) = list("bronc" = c("true", "false"), 
					 "smoke" =  c("true", "false"))
cpt1.xrays = c(0.9, 0.1, 0.01, 0.99)
dim(cpt1.xrays) = c(2, 2)
dimnames(cpt1.xrays) = list("xrays" = c("true", "false"), 
					 "lung" =  c("true", "false"))
cpt2.xrays = c(0.99, 0.01, 0.05, 0.95)
dim(cpt2.xrays) = c(2, 2)
dimnames(cpt2.xrays) = list("xrays" = c("true", "false"), 
					 "lung" =  c("true", "false"))