Gibbs sampler for one-way ANOVA

gibbs_anova(y, steps, burnin, thin = 1, mu.0 = 0, sigma2.0 = 1e+06)

Arguments

y	a matrix with two columns (column 1 is the data, column 2 is the group)
steps	number of iterations to run Gibbs sampler for after burn-in
burnin	number of burn-in iterations
thin	thinning factor (default = 1)
mu.0	mean hyperparameter for grand mean
sigma2.0	variance hyperparameter for grand mean

Value

a list of posterior samples for group means, grand mean, variance within, and variance between

Details

Assumes Normal likelihood, Normal and log Uniform priors, Normal and log Uniform hyperpriors

Examples

if (FALSE) {
set.seed(1234)
# Starling weight data
y = data.frame(obs = c(78, 88, 87, 88, 83, 82, 81, 80, 80, 89,
                       78, 78, 83, 81, 78, 81, 81, 82, 76, 76,
                       79, 73, 79, 75, 77, 78, 80, 78, 83, 84,
                       77, 69, 75, 70, 74, 83, 80, 75, 76, 75),
               group = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
                         2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
                         3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
                         4, 4, 4, 4, 4, 4, 4, 4, 4, 4))
mcmc = gibbs_anova(y, 10000, 5000)
}