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.
Latihan ini adalah bagian dari kursus
Bayesian Modeling with RJAGS
Latihan interaktif praktis
Cobalah latihan ini dengan menyelesaikan kode contoh berikut.
# 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))