gibbs_mean: Gibbs Sample for Single Mean and Variance

In iNZightVIT/iNZightBayes: Bayesian Inference with 'iNZight'

Description

Gibbs sampler to sample mean and variance of one numeric variable

Usage

gibbs_mean(
  y,
  steps = 1000L,
  burnin = 1000L,
  thin = 1L,
  mu_0 = 0,
  sigma2_0 = 1e+06,
  alpha = 0.001,
  beta = 0.001
)

Arguments

y	a vector of values
steps	number of iterations to run Gibbs sampler for
burnin	number of burn-in iterations to discard before proper steps
thin	thinning factor (default 1)
mu_0	prior mean for mu (default 0)
sigma2_0	prior variance for mu (default 1e6)
alpha	prior shape parameter for sigma2 (default 1e-3)
beta	prior scale parameter for sigma2 (default 1e-3)

Details

Assumes conjugate Normal-Inverse-Gamma priors on mean and variance:

y \sim \mathrm{Normal}(μ, σ^2)

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