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.

Bu egzersiz

Bayesian Modeling with RJAGS

kursunun bir parçasıdır

Kursu Görüntüle

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# 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))

Kodu Düzenle ve Çalıştır