Simulations of the parameters of a hierarchical model
Using the radon example in Gelman & Hill (2007), the list contains several elements to show the possibilities of ggmcmc for applied Bayesian Hierarchical/multilevel analysis.
data(radon)
A list containing several elements (data and outputs of the analysis):
A data frame with the country label, ids and radon level.
A vector identifying counties in the data.
The outcome variable.
A coda object with simulated values from the posterior distribution of all parameters, with few iterations for each one.
A coda object containing simulated values from the posterior predictive distribution.
A coda object with simulated values from the posterior distribution of few parameters, with reasonable chain length.
data(radon)
names(radon)
# Generate a data frame suitable for matching with the generated samples
# through the "par_labels" function:
L.radon <- plab("alpha", match = list(County = radon$counties$County))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.