Nothing
# create jags, BUGS and Stan mocked
# cost and eff posterior samples
# to test bcea() methods
##TODO: why doesn't this MC forward sampling work?
# cat("model {
# eff ~ dunif(0, 1)
# cost ~ dnorm(0, 1)
# }", file = "ce_mock.txt")
## ... a work-around
cat("model {
for (i in 1:2) {
cost[i] ~ dunif(0, 1)
eff[i] ~ dunif(0, 1)
x[i] ~ dnorm(cost[i], 1)
y[i] ~ dnorm(eff[i], 1)
}
}", file = "ce_mock.txt")
writeLines(
"data {
real x[2];
real y[2];
}
parameters {
real cost[2];
real eff[2];
}
model {
for (i in 1:2) {
cost[i] ~ uniform(0, 1);
eff[i] ~ uniform(0, 1);
x[i] ~ normal(cost[i], 1);
y[i] ~ normal(eff[i], 1);
}
}
", con = "ce_mock.stan")
model.params <- c("cost", "eff")
model.data <- list(x = c(1,1), y = c(1,1))
jagsfit <- jags(data = model.data,
parameters.to.save = model.params,
n.iter = 10,
n.chains = 1,
model.file = "ce_mock.txt")
bugsfit <- openbugs(data = model.data,
parameters.to.save = model.params,
n.iter = 10,
n.chains = 1,
inits = list(list(cost = 0, eff = 0)),
model.file = "ce_mock.txt")
# stanfit <- stan(data = model.data,
# pars = model.params,
# chains = 1,
# iter = 10,
# init = 0,
# file = "ce_mock.stan")
save(jagsfit, file = test_path("data", "jagsfit.RData"))
save(bugsfit, file = test_path("data", "bugsfit.RData"))
# save(stanfit, file = test_path("data", "stanfit.RData"))
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