Updating the posterior
The posterior model of your underlying election support \(p\) is informed by both the prior model of \(p\) and polling data \(X\). Run the script to the right to remind yourself of the posterior that evolved from your original prior (Beta(45, 55)) and original poll data (\(X = 6\) of \(n = 10\) polled voters support you). The defined vote_model is in your workspace.
In a 3-step exercise, you will explore how using a different prior model or observing new data (or a combination of the two!) might impact the posterior.
本练习是课程的一部分
Bayesian Modeling with RJAGS
交互式实操练习
通过完成这段示例代码来试试这个练习。
# COMPILE the model
vote_jags <- jags.model(textConnection(vote_model),
data = list(a = 45, b = 55, X = 6, n = 10),
inits = list(.RNG.name = "base::Wichmann-Hill", .RNG.seed = 100))
# SIMULATE the posterior
vote_sim <- coda.samples(model = vote_jags, variable.names = c("p"), n.iter = 10000)
# PLOT the posterior
plot(vote_sim, trace = FALSE, xlim = c(0,1), ylim = c(0,18))