Conditional Logic Nodes about hydenet HOT 5 CLOSED

craps <- hydeNetwork(~ d1 + d2 + outcome | d1*d2)

craps <- setNode(craps, d1, nodeType="dcat", pi = vectorProbs(p = rep(1/6,6), d1))
craps <- setNode(craps, d2, nodeType="dcat", pi = vectorProbs(p = rep(1/6,6), d2))

craps <- setNode(craps, outcome, ????????????)

craps

g <- hydeNetwork(~ disease | comorbidityScore
     + test1 | disease
     + test2 | disease
     + surgery  |  test1*test2*insurance
     + surgicalComp | comorbidityScore*disease*surgery
     + death | disease*treatment*surgicalComp)

g <- hydeNetwork(~ disease | comorbidityScore
     + test1 | disease
     + test2 | disease
     + surgery  |  test1*test2*insurance  #stochastic Bernoulli
     + hypotheticalSurgicalComp | comorbidityScore  #stochastic Bernoulli (based on logistic reg.)
     + surgicalComp | surgery*hypotheticalSurgicalComp  #deterministic node
     + death | disease*treatment*surgicalComp)

#* Define the probability distributions for rolling two dice
rolls <- expand.grid(r1 = 1:6,
                     r2 = 1:6)
rolls$d1 <- with(rolls, r1 + r2)
rolls$d2 <- with(rolls, r1 + r2)

#* Define the network
craps <- HydeNetwork(~ d1 + 
                       roll_again | d1 + 
                       d2 | roll_again + 
                       eval_roll | d2 * roll_again + 
                       result | eval_roll)

plot(craps)

craps <- setNode(craps, d1, "dcat", 
                 pi=writeJagsFormula(xtabs(~ d1, data=rolls)))
craps <- setNode(craps, d2, "dcat",
                 pi=writeJagsFormula(xtabs(~ d2, data=rolls)))
craps <- setNode(craps, roll_again, "determ",
                 define = "ifelse(d1 == 2 || d1 == 3 || d1 == 7 || d1 == 11 || d1 == 12, 0, 1)",
                 validate=FALSE)
craps <- setNode(craps, eval_roll, "determ",
                 define = "ifelse(roll_again == 0, d1, d2)",
                 validate=FALSE)
craps <- setNode(craps, result, "determ",
                 define = "ifelse(eval_roll == 7 || eval_roll == 11, 1, 0)",
                 validate=FALSE)

compiledCraps <- compileJagsModel(craps)
codaCraps <- coda.samples(compiledCraps$jags, 
                          craps$nodes,
                          n.iter=1000)

#* Probability of winning if we observe a 6 on the first roll
compiledCraps <- compileJagsModel(craps, data=list(d1=6))
codaCraps <- coda.samples(compiledCraps$jags, 
                          "result",
                          n.iter=1000)