Markov chain density plots

Whereas a trace plot captures a Markov chain's longitudinal behavior, a density plot illustrates the final distribution of the chain values. In turn, the density plot provides an approximation of the posterior model. You will construct and examine density plots of the \(m\) Markov chain below. The mcmc.list object sleep_sim and sleep_chains data frame are in your workspace:

sleep_sim <- coda.samples(model = sleep_jags, variable.names = c("m", "s"), n.iter = 10000)
sleep_chains <- data.frame(sleep_sim[[1]], iter = 1:10000)

Deze oefening maakt deel uit van de cursus

Bayesian Modeling with RJAGS

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Oefeninstructies

Apply plot() to sleep_sim with trace = FALSE to construct density plots for the \(m\) and \(s\) chains.
Apply ggplot() to sleep_chains to re-construct a density plot of the \(m\) chain.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# Use plot() to construct density plots of the m and s chains


# Use ggplot() to construct a density plot of the m chain
ggplot(___, aes(x = ___)) + 
    ___()

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