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.

Deze oefening maakt deel uit van de cursus

Bayesian Modeling with RJAGS

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Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# 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))

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