radon: Simulations of the parameters of a hierarchical model

In ggmcmc: Tools for Analyzing MCMC Simulations from Bayesian Inference

Description

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.

Usage

data(radon)

Format

A list containing several elements (data and outputs of the analysis):

counties

A data frame with the country label, ids and radon level.

id.county

A vector identifying counties in the data.

y

The outcome variable.

s.radon

A coda object with simulated values from the posterior distribution of all parameters, with few iterations for each one.

s.radon.yhat

A coda object containing simulated values from the posterior predictive distribution.

s.radon.short

A coda object with simulated values from the posterior distribution of few parameters, with reasonable chain length.

Source

http://www.stat.columbia.edu/~gelman/arm/examples/radon/

Examples

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))

ggmcmc documentation built on Feb. 10, 2021, 5:10 p.m.