gibbs_anova: Gibbs sampler for one-way ANOVA

In iNZightVIT/iNZightBayes: Bayesian Inference with 'iNZight'

Description

Gibbs sampler for one-way ANOVA

Usage

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

Details

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

Value

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

Examples

## Not run: 
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)

## End(Not run)

iNZightVIT/iNZightBayes documentation built on Dec. 20, 2021, 5:56 p.m.